OLI Psychology is not your typical course. Our goal is for you to work through the course materials online on your own time and in the way that is most efficient given your prior knowledge.

While you will have more flexibility than you do in a traditional course, you will also have more responsibility for your own learning. You will need to:

• Plan how to work through each unit.
• Determine how to use the various features of the course to help you learn.
• Decide when you need to seek additional support.

You've now read through the explanatory content in this unit, and you've had a chance to practice the concepts. Take a moment to reflect on your understanding. Do you feel like you are "getting it"? Use these next two activities to find out.

Strong metacognitive skills are essential for independent learning, so use the experience of monitoring your own learning in OLI Psychology as an opportunity to hone these skills for other classes and tasks.

This Introduction to Psychology course was developed as part of the Community College Open Learning Initiative. Using an open textbook from Flatworld Knowledge as a foundation, Carnegie Mellon University's Open Learning Initiative has built an online learning environment designed to enact instruction for psychology students.

The Open Learning Initiative (OLI) is a grant-funded group at Carnegie Mellon University, offering innovative online courses to anyone who wants to learn or teach. Our aim is to create high-quality courses and contribute original research to improve learning and transform higher education by: Supporting better learning and instruction with high-quality, scientifically-based, classroom-tested online courses and materials. Sharing our courses and materials openly and freely so that anyone can learn. Developing a community of use, research, and development.

Flatworld Knowledge is a college textbook publishing company on a mission. By using technology and innovative business models to lower costs, Flatword is increasing access and personalizing learning for college students and faculty worldwide. Text, graphics and video in this course are built on materials by Flatworld Knowledge, made available under a CC-BY-NC-SA license. Interested in a companion text for this course? Flatworld provides access to the original textbook online and makes digital and print copies of the original textbook available at a low cost.

Welcome to world of psychology. This course will introduce you to some of the most important ideas, people, and research methods from the field of Psychology. You probably already know about some people, perhaps Sigmund Freud or B. F. Skinner, who contributed to our understanding of human thought and behavior, and you may have learned about important ideas, such as personality testing or methods of psychotherapy. This course will give you the opportunity to refine and organize the knowledge you bring to the class, and we hope that you will learn about theories, phenomena, and research results that give you new insight into the human condition.

This first module is your opportunity to explore the field of psychology for a while before moving into material that will be assessed and tracked. Let’s start with an obvious question:

The word psychology is based on two words from the Greek language: psyche, which means “life” or, in a more restricted sense “mind,” or “spirit,” and logia, which is the source for the current meaning, “the study of…”

Whatever the origin of the word, over the years, philosophers, scientists, and other interested people have debated about the “proper” subject matter for psychology. Should we focus on actual behavior, which we can observe and even measure, or on the mind, which includes the rich inner experience we all have of the world and of our own thoughts and motives, or on the brain, which is the centerpiece of the physical systems that make thought and behavior possible? And psychology is not just a bunch of fancy theories. Psychology is a vibrant, growing field because psychologists’ ideas and skills are used every day in thousands of ways to solve real-world problems.

To start your introduction to psychology, first survey the range of topics you will be studying in this course. The section on “What do psychologists study?” reviews the scope of topics covered in this course and allows you to see some of the general themes the various units develop. When you are finished with your survey of topics, the section on “What do psychologists do?” gives you some sense of the scope of psychological work and professional fields where psychological training is essential.

Your work in the rest of this module will also introduce you to one of the essential features of this course: Learning by Doing. Research and experience tell us that active involvement in learning is far more effective than mere passive reading or listening. Learning by Doing doesn’t need to be complicated or difficult. It simply requires that you get out of automatic mode and think a bit about the ideas you are encountering. We will get you to participate a bit in your introduction to the online materials and to the field of psychology, so you can Learn by Doing.

You will also encounter another type of activity: Did I Get This? These brief quizzes allow you to determine if you are on track in your understanding of the material. Take the Did I Get This? quiz after each section of the module. If you do well, you might decide that you have mastered the material enough to go on. However, keep in mind that you, not the quiz, should decide if you are ready. The quiz is just there to help you.

Before you leave a particular section of a module, you will usually have the opportunity to check your knowledge. The activities called Did I Get This? are brief quizzes about the material you have just been studying. Use them to monitor your understanding of the material before moving on.

You now know that psychology is a big field and psychologists are interested in a great variety of issues. In order to introduce you to so much material, we will often have to focus on specific issues or problems and on an experiment or theory that addresses issue or problem. Much of this research is conducted in university laboratories. This may give you the impression that psychologists only work in universities, conducting experiments with undergraduate psychology students. It is true that a lot of research takes place in university labs, but the majority of psychologists work outside of the university setting.

The next Learn by Doing will give you a chance to consider different ways that people with training in psychology use their skills. In the second module of this introductory unit, we will explore the various areas of psychology more systematically, so this is just a first look at the scope of the work psychologists do.

In the next module of this introductory unit you will learn a bit about the history of psychology and some of the major issues that influence psychological thinking.

In this module we review some of the important philosophical questions that psychologists attempt to answer, the evolution of psychology from ancient philosophy and how psychology became a science. You will learn about the early schools (or approaches) of psychological inquiry and some of the important contributors to each of these early schools of psychology. You will also learn how some of these early schools influenced the newer contemporary perspective of psychology.

The approaches that psychologists originally used to assess the issues that interested them have changed dramatically over the history of psychology. Perhaps most importantly, the field has moved steadily from speculation about the mind and behavior toward a more objective and scientific approach as the technology available to study human behavior has improved. There has also been an increasing influx of women into the field. Although most early psychologists were men, now most psychologists, including the presidents of the most important psychological organizations, are women.

Female Psychologists

Although most of the earliest psychologists were men, women are increasingly contributing to psychology. The first female president of the American Psychological Association was Mary Whiton Calkins (861–1930; lower right). Calkins made significant contributions to the study of memory and the self-concept. Mahzarin Banaji (upper left), Marilynn Brewer (upper right), and Linda Bartoshuk (lower left) all have been recent presidents of the American Psychological Association. From Flat World Knowledge, Introduction to Psychology, v1.0: Bartoshuk photo courtesy of Linda Bartoshuk, http://www.psychologicalscience.org/?s=bartoshuk. Banaji photocourtesy of Mahzarin Rustum Banaji, http://banaji.socialpsychology.org. Brewer photo courtesy of Marilynn Brewer, http://brewer.socialpsychology.org. Calkins photo courtesy of Vlad Sfichi, http://www.flickr.com/photos/24110800@N08/2779490726.

As you may have noticed in the six early schools of psychology, each attempted to answer psychological questions with a single approach. While some attempted to build a big theory around their approach (and some did not even attempt), no one school was successful. By the mid-20th century, the field of psychology was still a very young science, but it was gaining a lot of diverse attention and popularity. Psychologists began to study mental processes and behavior from their own specific points of interests and views. Thus, some of the specific viewpoints became known as perspectives from which to investigate a specific psychological topic.

Today, contemporary psychology reflects several major perspectives such biological/neuroscience, cognitive, behavioral, social, developmental, clinical, and individual differences/personality. These are not a complete list of perspectives and your instructor may introduce others. What’s important to know is that today all psychologists believe that there is no one specific perspective with which to study psychology, but rather any given topic can be approached from a variety of perspectives. For example, investigating how an infant learns language can be studied from all of the different perspectives that could provide information from a different viewpoint about the child’s learning. Also as perspectives become more specific, we see that the perspectives are interconnected with each other, meaning that it is difficult to study any topic on human thought or behavior from just one perspective without considering the complex influence of information from other perspectives.

Social psychologists investigate the cultural differences between those living in Western cultures which value the self (individualism) and those living in Eastern cultures which value families and social groups (collectivism). From Flatworld Knowledge Introduction to Psychology, v1.0: © Thinkstock.

As our world becomes more global, sociocultural research will become more interconnected with the research of other psychological perspectives such as biological, cognitive, personality, developmental and clinical.

Psychology is not one discipline but rather a collection of many subdisciplines that all share at least some common perspectives that work together to exchange knowledge to form a coherent discipline. Because the field of psychology is so broad, students may wonder which areas are most suitable for their interests and which types of careers might be available to them. The following figure will help you consider the answers to these questions. Click on any of the labeled, blue circles to learn more about each discipline.

Photo courtesy of longislandwins (CC-BY-2.0).

Psychologists aren’t the only people who seek to understand human behavior and solve social problems. Philosophers, religious leaders, and politicians, among others, also strive to provide explanations for human behavior. But psychologists believe that research is the best tool for understanding human beings and their relationships with others. Rather than accepting the claim of a philosopher that people do (or do not) have free will, a psychologist would collect data to empirically test whether or not people are able to actively control their own behavior. Rather than accepting a politician’s contention that creating (or abandoning) a new center for mental health will improve the lives of individuals in the inner city, a psychologist would empirically assess the effects of receiving mental health treatment on the quality of life of the recipients. The statements made by psychologists are based on an empirical study. An empirical study is results of verifiable evidence from a systematic collection and analysis of data that has been objectively observed, measured, and undergone experimentation.

In this unit you will learn how psychologists develop and test their research ideas; how they measure the thoughts, feelings, and behavior of individuals; and how they analyze and interpret the data they collect. To really understand psychology, you must also understand how and why the research you are reading about was conducted and what the collected data mean. Learning about the principles and practices of psychological research will allow you to critically read, interpret, and evaluate research.

In addition to helping you learn the material in this course, the ability to interpret and conduct research is also useful in many of the careers that you might choose. For instance, advertising and marketing researchers study how to make advertising more effective, health and medical researchers study the impact of behaviors such as drug use and smoking on illness, and computer scientists study how people interact with computers. Furthermore, even if you are not planning a career as a researcher, jobs in almost any area of social, medical, or mental health science require that a worker be informed about psychological research.

Psychologists study behavior of both humans and animals, and the main purpose of this research is to help us understand people and to improve the quality of human lives. The results of psychological research are relevant to problems such as learning and memory, homelessness, psychological disorders, family instability, and aggressive behavior and violence. Psychological research is used in a range of important areas, from public policy to driver safety. It guides court rulings with respect to racism and sexism as in the 1954 case of Brown v. Board of Education, as well as court procedure, in the use of lie detectors during criminal trials, for example. Psychological research helps us understand how driver behavior affects safety such as the effects of texting while driving, which methods of educating children are most effective, how to best detect deception, and the causes of terrorism.

Some psychological research is basic research. Basic research is research that answers fundamental questions about behavior. For instance, bio-psychologists study how nerves conduct impulses from the receptors in the skin to the brain, and cognitive psychologists investigate how different types of studying influence memory for pictures and words. There is no particular reason to examine such things except to acquire a better knowledge of how these processes occur. Applied research is research that investigates issues that have implications for everyday life and provides solutions to everyday problems. Applied research has been conducted to study, among many other things, the most effective methods for reducing depression, the types of advertising campaigns that serve to reduce drug and alcohol abuse, the key predictors of managerial success in business, and the indicators of effective government programs, such as Head Start.

Basic research and applied research inform each other, and advances in science occur more rapidly when each type of research is conducted. For instance, although research concerning the role of practice on memory for lists of words is basic in orientation, the results could potentially be applied to help children learn to read. Correspondingly, psychologist-practitioners who wish to reduce the spread of AIDS or to promote volunteering frequently base their programs on the results of basic research. This basic AIDS or volunteering research is then applied to help change people’s attitudes and behaviors.

One goal of research is to organize information into meaningful statements that can be applied in many situations.

A theory is an integrated set of principles that explains and predicts many, but not all, observed relationships within a given domain of inquiry. One example of an important theory in psychology is the stage theory of cognitive development proposed by the Swiss psychologist Jean Piaget. The theory states that children pass through a series of cognitive stages as they grow, each of which must be mastered in succession before movement to the next cognitive stage can occur. This is an extremely useful theory in human development because it can be applied to many different content areas and can be tested in many different ways.

Good theories have four important characteristics. A good theory is:

• General, meaning it summarizes different outcomes.
• Parsimonious, meaning it provides the simplest possible account of those outcomes.
• Provides ideas for future research.
• Falsifiable, meaning that the variables of interest can be adequately measured and the relationships between the variables that are predicted by the theory can be shown through research to be incorrect.

Piaget’s stage theory of cognitive development meets all four characteristics of a good theory. First, it is general in that it can account for developmental changes in behavior across a wide variety of domains, and second, it does so parsimoniously—by hypothesizing a simple set of cognitive stages. Third, the stage theory of cognitive development has been applied not only to learning about cognitive skills but also to the study of children’s moral and gender development. And finally, the stage theory of cognitive development is falsifiable because the stages of cognitive reasoning can be measured and because if research discovers, for instance, that children learn new tasks before they have reached the cognitive stage hypothesized to be required for that task, then the theory will be shown to be incorrect.

No single theory is able to account for all behavior in all cases. Rather, theories are each limited in that they make accurate predictions in some situations or for some people but not in other situations or for other people. As a result, there is a constant exchange between theory and data: Existing theories are modified on the basis of collected data, and the new modified theories then make new predictions that are tested by new data, and so forth. When a better theory is found, it will replace the old one. This is part of the accumulation of scientific knowledge as a result of research.

One of the questions that all scientists must address concerns the ethics of their research. Research in psychology may cause some stress, harm, or inconvenience for the people who participate in that research. For instance, researchers may require introductory psychology students to participate in research projects and then deceive these students, at least temporarily, about the nature of the research. Psychologists may induce stress, anxiety, or negative moods in their participants, expose them to weak electrical shocks, or convince them to behave in ways that violate their moral standards. And researchers may sometimes use animals in their research, potentially harming them in the process.

Decisions about whether research is ethical are made using established ethical codes and standards developed by scientific organizations, such as the American Psychological Association, and the federal government, such as the U.S. Department of Health and Human Services (DHHS). In addition, there is no way to know ahead of time what the effects of a given procedure will be on every person or animal who participates or what benefit to society the research is likely to produce. What is ethical is defined by the current state of thinking within society, and thus perceived costs and benefits change over time. The DHHS regulations require that all universities receiving funds from the department set up an Institutional Review Board (IRB) to determine whether proposed research meets department regulations. The Institutional Review Board is a committee of at least five members whose goal it is to determine the cost-benefit ratio of research conducted within an institution. The IRB approves the procedures of all the research conducted at the institution before the research can begin. The board may suggest modifications to the procedures, or (in rare cases) it may inform the scientist that the research violates DHHS guidelines and thus cannot be conducted at all.

The following table presents some of the most important factors that psychologists take into consideration when designing their research using people.

The most direct ethical concern of the scientist is to prevent harm to the research participants. One example is the well-known research, conducted in 1961 by Stanley Milgram, which investigated obedience to authority. Participants were induced by an experimenter to administer electric shocks to another person so that Milgram could study the extent to which they would obey the demands of an authority figure. Most participants evidenced high levels of stress resulting from the psychological conflict they experienced between engaging in aggressive and dangerous behavior and following the instructions of the experimenter. Studies such as those by Milgram are no longer conducted because the scientific community is now much more sensitized to the potential of such procedures to create emotional discomfort or harm.

Another goal of ethical research is to guarantee that participants have free choice regarding whether they wish to participate in research. Students in psychology classes may be allowed, or even required, to participate in research, but they are also always given an option to choose a different study to be in, or to perform other activities instead. And once an experiment begins, the research participant is always free to leave the experiment if he or she wishes to. Concerns about free choice also occur in institutional settings, such as in schools, hospitals, corporations, and prisons, when individuals are required by the institutions to take certain tests or when employees are told or asked to participate in research.

Researchers must also protect the privacy of the research participants. In some cases data can be kept anonymous by not having the respondents put any identifying information on their questionnaires. In other cases the data cannot be anonymous because the researcher needs to keep track of which respondent contributed the data. In this case one technique is to have each participant use a unique code number to identify his or her data, such as the last four digits of the student ID number. In this way the researcher can keep track of which person completed which questionnaire, but no one will be able to connect the data with the individual who contributed them.

Perhaps the most widespread ethical concern to the participants in behavioral research is the extent to which researchers employ deception. Deception occurs whenever research participants are not completely and fully informed about the nature of the research project before participating in it. Deception may occur in an active way, such as when the researcher tells the participants that he or she is studying learning when in fact the experiment really concerns obedience to authority. In other cases the deception is more passive, such as when participants are not told about the hypothesis being studied or the potential use of the data being collected.

Some researchers have argued that no deception should ever be used in any research. ^[2] They argue that participants should always be told the complete truth about the nature of the research they are in, and that when participants are deceived there will be negative consequences, such as the possibility that participants may arrive at other studies already expecting to be deceived. Other psychologists defend the use of deception on the grounds that it is needed to get participants to act naturally and to enable the study of psychological phenomena that might not otherwise get investigated. They argue that it would be impossible to study topics such as altruism, aggression, obedience, and stereotyping without using deception because if participants were informed ahead of time what the study involved, this knowledge would certainly change their behavior. The codes of ethics of the American Psychological Association and other organizations allow researchers to use deception, but these codes also require them to explicitly consider how their research might be conducted without the use of deception.

Nevertheless, an important tool for ensuring that research is ethical is the use of a written informed consent form. Informed consent, conducted before a participant begins a research session, is designed to explain the research procedures and inform the participant of his or her rights during the investigation. An informed consent form explains as much as possible about the true nature of the study, particularly everything that might be expected to influence willingness to participate, but it may in some cases withhold some information that allows the study to work.

Finally, participating in research has the potential for producing long-term changes in the research participants. Therefore, all participants should be fully debriefed immediately after their participation. The debriefing is a procedure designed to fully explain the purposes and procedures of the research and remove any harmful aftereffects of participation.

Psychologists agree that if their ideas and theories about human behavior are to be taken seriously, they must be backed up by data collected through research. The research goals that a psychologist wants to study determine the use of one of three types of research approaches. These varying approaches, summarized in the table below, are known as research designs. A research design is the specific method a researcher uses to collect, analyze, and interpret data. Psychologists use three major types of research designs in their research, and each provides an essential avenue for scientific investigation.

• Descriptive research is research designed to provide a snapshot of the current state of affairs.
• Correlational research is research designed to discover relationships among variables and to allow the prediction of future events from present knowledge.
• Experimental research is research in which there is random assignment of research participants into two groups. This is followed by a manipulation of a given experience for one group while the other is not manipulated. The two groups are then compared to determine the influence of the manipulation.

Each of the three research designs varies according to its strengths and limitations, and it is important to understand how each differs.

Descriptive research is designed to create a snapshot of the current thoughts, feelings, or behavior of individuals. There are three types of descriptive research: case studies, surveys, and naturalistic observation.

Sometimes the data in a descriptive research project is based on only a small set of individuals, often only one person or a single small group. These research designs are known as case studies—descriptive records of one or more individuals’ experiences and behavior. Sometimes case studies involve ordinary individuals, as when developmental psychologist Jean Piaget used his observation of his own children to develop his stage theory of cognitive development. More frequently, case studies are conducted on individuals who have unusual or abnormal experiences or characteristics or who find themselves in particularly difficult or stressful situations. The assumption is that we can learn something about human nature by carefully studying individuals who are socially marginal, experiencing unusual situations, or going through a difficult phase in their lives.

Sigmund Freud was a master of using the psychological difficulties of individuals to draw conclusions about basic psychological processes. Freud wrote case studies of some of his most interesting patients and used these careful examinations to develop his important theories of personality. One classic example is Freud’s description of “Little Hans,” a child whose fear of horses the psychoanalyst interpreted in terms of repressed sexual impulses and the Oedipus complex.

Political polls reported in newspapers and on the Internet are descriptive research designs that provide snapshots of the likely voting behavior of a population. From Flatworld Knowledge Introduction to Psychology, v1.0: © Thinkstock.

The second type of descriptive research is the survey—a measure administered through either a face-to-face or telephone interview, or a written or computer-generated questionnaire—to get a picture of the beliefs or behaviors of a sample of people of interest. The people chosen to participate in the research, called a sample, are selected to be representative of all the people that the researcher wishes to know about, called the population. In election polls, for instance, a sample is taken from the population of all “likely voters” in the upcoming elections.

The results of surveys may sometimes be rather mundane, such as “nine out of ten doctors prefer Tymenocin,” or “the median income in Montgomery County is $36,712.” Yet other times (particularly in discussions of social behavior), the results can be shocking: “more than 40,000 people are killed by gunfire in the United States every year,” or “more than 60% of women between the ages of 50 and 60 suffer from depression.” Descriptive research is frequently used by psychologists to get an estimate of the prevalence (or incidence) of psychological disorders.

The third type of descriptive research—known as naturalistic observation—is research based on the observation of everyday events occurring in the natural environment of people or animals. For instance, a developmental psychologist who watches children on a playground and describes how they interact is conducting descriptive research. Another example of naturalistic research is a bio-psychologist who observes animals in their natural habitats.

A famous example of this type of research is the work of Dr. Jane Goodall at her primate research facility in Gombe Stream National Park, Tanzania (on the continent of Africa). Goodall and her staff have observed and recorded the social interactions and family life of the Kasakela chimpanzee community for over 50 years. Their work is considered groundbreaking and has revealed aspects of chimpanzee life that may have gone undiscovered. For instance, Goodall described human-like socializing behaviors in that members of the group would show affection and encouragement to one another. It was discovered that the chimpanzees were toolmakers and users—stripping leaves from twigs and poking the twig into termite holes to retrieve a meal. Goodall also described the carnivore side of chimpanzees, reporting that hunting groups from the chimpanzee community would stalk, isolate, and kill smaller primates for food and then divide their kill for distribution to other group members.

A chimpanzee uses a twig as a tool to get termites. Photo by suneko, courtesy of Animal Photos! CC-BY-2.0.

Two parts of Dr. Goodall’s research methods are representative of the disadvantages of naturalistic observational research. First, she decided to name the chimpanzees she studied instead of using the scientific convention of numbering subjects. The numbering technique hypothetically promotes objective observation that is devoid of attachment and bias on the part of the observer. Dr. Goodall identified members of her chimpanzee community by name, and discussed their behavior in terms of emotion, personality, intelligence, and family relationships; she was criticized by some for becoming overly involved and thus more subjective in her interpretations. This is known as observer bias, which happens when the individual observing behavior is influenced by their own experiences, expectations, or knowledge about the purpose of the observation or study.

Second, the Gombe research team utilized feeding stations to attract the animals for observation, thus potentially altering the natural feeding patterns and behaviors of the troop. This may have promoted artificial competition and increased aggression among the chimpanzees when the observers meaningfully interacted with the chimpanzees. This is called the observer effect. Indeed, the observer effect (interference with or modification of the subject’s behaviors by the process of observation) can lead to a distorted picture of a natural phenomenon, thus defeating the point of “naturalistic” observational research. It is difficult to know how influential the presence of a stranger can be in an established social situation or for the subject being observed.

In many observational studies, particularly those conducted with children, the observers are hidden away from the subjects. Some researchers use two-way mirrors, others use hidden cameras with monitors located in a separate room. Subjects can also be recorded on video from several angles as they interact socially or within their environment; the video recordings can then be observed and data recorded at a later time. A major advantage to this method is the ability to have two or more observers observe and record the behavior, followed by calculating a score for interrater reliability. This score can estimate how much agreement there is between the two observers about what the subjects were doing. This type of test can also identify observer bias.

An advantage of descriptive research is that it attempts to capture the complexity of everyday behavior. Specifically, case studies provide detailed information about a single person or a small group of people and surveys capture the thoughts or reported behaviors of a large population of people. Naturalistic observation, meanwhile, objectively record the behavior of people or animals as it naturally occurs. In sum, descriptive research is used to provide a relatively complete understanding of what is currently happening.

Despite these advantages, descriptive research has a distinct disadvantage in that, although it allows us to get an idea of what is currently happening, it is usually limited to static pictures. Although descriptions of particular experiences may be interesting, they are not always transferable to other individuals in other situations, nor do they tell us exactly why specific behaviors or events occurred. For instance, descriptions of individuals who have suffered a stressful event, such as a war or an earthquake, can be used to understand the individuals’ reactions to the event but cannot tell us anything about the long-term effects of the stress. And because there is no comparison group that did not experience the stressful situation, we cannot know what these individuals would be like if they hadn’t had the stressful experience.

In contrast to descriptive research, which is designed primarily to provide static pictures, correlational research involves measuring the relationship between or among two or more relevant variables. For instance, the variables of height and weight are systematically related (correlated) because taller people generally weigh more than shorter people. In the same way, study time and memory errors are also related, because the more time a person is given to study a list of words, the fewer errors he or she will make. When there are two variables in the research design, one of them is called the predictor variable and the other the outcome variable.

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

One way of organizing the data from a correlational study with two variables is to graph the values of each of the measured variables using a scatter plot. As you can see in figure below, a scatter plot is a visual image of the relationship between two variables. A point is plotted for each individual at the intersection of his or her scores for the two variables. When the association between the variables on the scatter plot can be easily approximated with a straight line, as in parts (a) and (b), the variables are said to have a linear relationship.

When the straight line indicates that individuals who have above-average values for one variable also tend to have above-average values for the other variable, as in part (a), the relationship is said to be positive linear. Examples of positive linear relationships include those between height and weight, between education and income, and between age and mathematical abilities in children. In each case people who score higher on one of the variables also tend to score higher on the other variable. Negative linear relationships, in contrast, as shown in part (b), occur when above-average values for one variable tend to be associated with below-average values for the other variable. Examples of negative linear relationships include those between the age of a child and the number of diapers the child uses, and between practice on and errors made on a learning task. In these cases, people who score higher on one of the variables tend to score lower on the other variable.

Relationships between variables that cannot be described with a straight line are known as nonlinear relationships. Part (c) shows a common pattern in which the distribution of the points is essentially random. In this case there is no relationship at all between the two variables, and they are said to be independent.

Examples of Scatter Plots

Some examples of relationships between two variables as shown in scatter plots. Adapted from Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

The most common statistical measure of the strength of linear relationships among variables is the Pearson correlation coefficient, which is symbolized by the letter r. The value of the correlation coefficient ranges from r = –1.00 to r = +1.00. The direction of the linear relationship is indicated by the sign of the correlation coefficient. Positive values of r (such as r= .54 or r = .67) indicate that the relationship is positive linear (i.e., the pattern of the dots on the scatter plot runs from the lower left to the upper right), whereas negative values of r (such as r = –.30 or r = –.72) indicate negative linear relationships (i.e., the dots run from the upper left to the lower right). The strength of the linear relationship is indexed by the distance of the correlation coefficient from zero (its absolute value). For instance, r = –.54 is a stronger relationship than r = .30, and r = .72 is a stronger relationship than r = –.57.

An important limitation of correlational research designs is that they cannot be used to draw conclusions about the causal relationships among the measured variables. Consider, for instance, a researcher who has hypothesized that viewing violent behavior will cause increased aggressive play in children. He has collected, from a sample of fourth-grade children, the data on how many violent television shows each child views during the week. He has also collected the data on how aggressively each child plays on the school playground. From his collected data, the researcher discovers a positive correlation between the two measured variables.

Although this positive correlation appears to support the researcher’s hypothesis, it cannot be taken to indicate that viewing violent television causes aggressive behavior. Although the researcher is tempted to assume that viewing violent television causes aggressive play, there are other possibilities.

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

It may be possible that the causal direction is exactly opposite from what has been hypothesized. Perhaps children who buhave aggressively at school develop residual excitement that leads them to want to watch violent television shows at home:

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Although this possibility may seem less likely, there is no way to rule out the possibility of such reverse causation on the basis of this observed correlation. It is also possible that both causal directions are operating and that the two variables cause each other:

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Another possible explanation for the observed correlation is that it has been produced by the presence of a common-causal variable (also known as a third variable). A common-causal variable is a variable that is not part of the research hypothesis but that causes both the predictor and the outcome variable and thus produces the observed correlation between them. In our example, a potential common-causal variable is the discipline style of the children’s parents. Parents who use a harsh and punitive discipline style may produce children who like to watch violent television and who behave aggressively in comparison to children whose parents use less harsh discipline:

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

In this case, television viewing and aggressive play would be positively correlated (as indicated by the curved arrow between them), even though neither one caused the other but they were both caused by the discipline style of the parents (the straight arrows). When the predictor and outcome variables are both caused by a common-causal variable, the observed relationship between them is said to be spurious. A spurious relationship is a relationship between two variables in which a common-causal variable produces and “explains away” the relationship. If effects of the common-causal variable were taken away, or controlled for, the relationship between the predictor and outcome variables would disappear. In the example, the relationship between aggression and television viewing might be spurious because by controlling for the effect of the parents’ disciplining style, the relationship between television viewing and aggressive behavior might go away.

Common-causal variables in correlational research designs can sometimes be thought of as “mystery” variables. For instance, some variables have not been measured or their presence and identity are unknown to the researcher. Since it is not possible to measure every variable that could cause both the predictor and outcome variables, the existence of an unknown common-causal variable is always a possibility. For this reason, we are left with the basic limitation of correlational research: Correlation does not demonstrate causation. It is important that when you read about correlational research projects, you keep in mind the possibility of spurious relationships and be sure to interpret the findings appropriately. Although correlational research is sometimes reported as demonstrating causality without any mention being made of the possibility of reverse causation or common-causal variables, informed consumers of research, like you, are aware of these interpretational problems.

In summary, correlational research designs have both strengths and limitations. One strength is that they can be used when experimental research is not possible because the predictor variables cannot be manipulated. Correlational designs also have the advantage of allowing the researcher to study behavior as it occurs in everyday life. And we can also use correlational designs to make predictions—for instance, to predict from the scores on their battery of tests the success of job trainees during a training session. But we cannot use such correlational information to determine whether the training caused better job performance. For that, researchers rely on experiments.

True experiments are the only reliable method scientists have for inferring causal relationships between two variables of interest: Does one thing cause another? So, the goal of an experimental research design is to provide more definitive conclusions about the causal relationships among the variables in the research hypothesis than is available from correlational designs.

In an experimental research design, the variables of interest are called the independent variable (or variables) and the dependent variable. The independent variable in an experiment is the causing variable that is created (manipulated) by the experimenter. The dependent variable in an experiment is a measured variable that is expected to be influenced by the experimental manipulation. The research hypothesis suggests that the manipulated independent variable or variables will cause changes in the measured dependent variables. We can diagram the research hypothesis by using an arrow that points in one direction. This demonstrates the expected direction of causality:

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

An example of the use of these independent and dependent variables in an experiment is the effect of witnessing aggression on children’s aggressive behaviors—certainly an important developmental question given the television and video game influence currently in place. In a classic study conducted by Albert Bandura in 1961, it was revealed that children who first watched an adult demonstrating violent behavior on a Bobo doll (inflatable clown with sand at the base) in a play room were more likely to show the same aggressive behaviors, compared to children who watched a passive adult in the play room or no adult at all in the play room before each child entered the play room. The independent variable manipulated by the experimenter was viewing violent behavior with the Bobo doll. The dependent variable, or the measure of behavior, was whether the child in a play room by his or herself expressed aggression by hitting a Bobo doll. The operational definition of this dependent variable was the number of hits, kicks, and other displays of aggression the child inflicted on the Bobo doll. The design of the experiment is shown in the following figure .

Consider an experiment conducted by Anderson and Dill. ^[1] The study was designed to test the hypothesis that viewing violent video games would increase aggressive behavior. In this research, male and female undergraduates from Iowa State University were given a chance to play with either a violent video game (Wolfenstein 3D) or a nonviolent video game (Myst). During the experimental session, the participants played their assigned video games for 15 minutes. Then, after the play, each participant played a competitive game with an opponent in which the participant could deliver blasts of white noise through the earphones of the opponent. The operational definition of the dependent variable (aggressive behavior) was the level and duration of noise delivered to the opponent. The design of the experiment is shown in the figure below.

An Experimental Research Design

Two advantages of the experimental research design are (1) the assurance that the independent variable (also known as the experimental manipulation) occurs prior to the measured dependent variable, and (2) the creation of initial equivalence between the conditions of the experiment (in this case by using random assignment to conditions). From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Anderson and Dill first randomly assigned about 100 participants to each of their two groups (Group A and Group B). Because they used random assignment to conditions, they could be confident that, before the experimental manipulation occurred, the students in Group A were, on average, equivalent to the students in Group B on every possible variable, including variables that are likely to be related to aggression, such as parental discipline style, peer relationships, hormone levels, diet—and in fact everything else.

Then, after they had created initial equivalence, Anderson and Dill created the experimental manipulation—they had the participants in Group A play the violent game and the participants in Group B play the nonviolent game. Then they compared the dependent variable (the white noise blasts) between the two groups, finding that the students who had viewed the violent video game gave significantly longer noise blasts than did the students who had played the nonviolent game.

Anderson and Dill had from the outset created initial equivalence between the groups. This initial equivalence allowed them to observe differences in the white noise levels between the two groups after the experimental manipulation, leading to the conclusion that it was the independent variable (and not some other variable) that caused these differences. The idea is that the only thing that was different between the students in the two groups was the video game they had played.

Experimental designs have two very nice features. For one, they guarantee that the independent variable occurs prior to the measurement of the dependent variable. This eliminates the possibility of reverse causation. Second, the influence of common-causal variables is controlled, and thus eliminated, by creating initial equivalence among the participants in each of the experimental conditions before the manipulation occurs.

The most common method of creating equivalence among the experimental conditions is through random assignment to conditions, a procedure in which the condition that each participant is assigned to is determined through a random process, such as drawing numbers out of an envelope or using a random number table.

Despite the advantage of determining causation, experiments do have limitations. One is that they are often conducted in laboratory situations rather than in the everyday lives of people. Therefore, we do not know whether results that we find in a laboratory setting will necessarily hold up in everyday life. Second, and more important, is that some of the most interesting and key social variables cannot be experimentally manipulated. If we want to study the influence of the size of a mob on the destructiveness of its behavior, or to compare the personality characteristics of people who join suicide cults with those of people who do not join such cults, these relationships must be assessed using a quasi-experiemental design because it may simply not possible to randomly assign subjects to groups or manipulate variables of interest.

Considering the phenomenon of aggression, certainly some would argue that spanking is a demonstration of aggression to which some children are exposed. Does spanking increase aggression in children? To study this question with an experimental design, one would need to recruit families into the study, randomly divide them into “spanking” and “non-spanking” groups, and compare the aggression in the children from the two groups. However, it would not be ethical or even possible to compel parents to spank their children in order to manipulate the independent variable. Thus, the strategy for this type of research would be a quasi-experimental design, which compares two groups that already exist in the population—in this case families who spank their children and those who do not. However, this nonrandom design eliminates the possibility of finding a causal relationship because we could never be sure there wasn’t a third variable contributing to differences in aggression. For instance, perhaps the families who do not spank their children also watch a significant amount of violence on television while the spanking families watch much less television in general. There’s no pattern or order to these habits, but they can nonetheless influence the analysis, particularly if there’s no difference in aggression found. Why? If spanking increases aggression and so does violent television, the groups might be about equal in aggression but for completely different reasons. Without random assignment and controlling for extraneous variables, it’s not possible to discover causality. Thus, quasi-experiments are used to describe relationships between existing groups. We call these pre-existing variables quasi-independent variables, and studies that use quasi-independent variables instead of randomly assigned true independent variables quasi-experiments.

learn by doing

In this activity, you will view a series of short videos about experimental designs. For each video, you will answer several questions:

1. What is the dependent variable? If there is more than one, identify all of the dependent variables.
2. What is the independent variable? If there is more than one, identify all of the independent variables.
3. Is this a true experiment or a quasi-experiment?
4. What conclusions can we draw from this study about the relationship between the independent and dependent variables?

Study 1: Reducing Stress

Background: Social Psychologist Mark Baldwin has studied the relationship between stressful environments and feelings of anxiety. He wondered if stressful work might lead people to expect and even search for negative messages, such as angry facial expressions, from other people. This can be a problem, because these negative messages then add to the stress which in turn increases anxiety. In this video, Dr. Baldwin shows a creative way to help people break away from this stress-induced tendency to search for negative messages.

Adobe Flash Player is required.

Get Adobe^® Flash^® Player.

Test My System

Summary of the experiment:

Telemarketers were randomly assigned to one of two tasks. Some of them looked for happy faces among sets of non-smiling faces. This version of the independent variable was the “treatment condition” because the experimenter believed that this task would be the one that would reduce stress levels. The other task was to search for flowers with five petals. This was the control condition, because the experimenter believed that this task would have little if any beneficial effect on stress.

Because telemarketers were randomly assigned to one of the two tasks, we can call this a TRUE experiment. If they had been assigned based on personal characteristics or preferences or some other nonrandom basis, we would call this a quasi-experiment.

Photo captured from “Anti-Stress Video Game” by ScienCentral, Inc. Partial Funding by National Science Foundation.

The primary dependent variable in this study was stress hormone level. Stress hormones are a biological indicator of the stress that the person is feeling, so level of the hormone is a valuable measure of actual stress experienced, and it does not depend on people’s personal statements about their feelings of stress, which might be distorted by various other factors. The researchers also looked at telemarketing sales, though the idea is that lower stress leads to better performance, so telemarketing sales are only indirectly affected by the task.

The research question was this: Does the specific task—looking for smiling faces versus flowers—affect stress hormone levels and telemarketing sales performance?

Photo captured from “Anti-Stress Video Game” by ScienCentral, Inc. Partial Funding by National Science Foundation.

The results were clear. Stress hormones were 17% lower in the group that looked for smiling faces when compared to the control group. The only known difference between these groups was the task itself, so—tentatively—we can conclude that the task of looking for smiling faces caused the people in that group to have lower stress levels than similar telemarketers in the other group.

The results also showed that telemarketing sales in the treatment group (smiling faces) were 68% higher than sales for those in the control group (flowers). Here, too, we can tentatively conclude that the task of looking for smiling faces caused the people in that group to have higher telemarketing sales than similar telemarketers in the other group.

Photo captured from “Anti-Stress Video Game” by ScienCentral, Inc. Partial Funding by National Science Foundation.

Study 2: Red for Romance?

Background: Psychologist Daniella Niesta is a researcher who is interested in factors that influence our motivation. Some factors that influence our behavior and thoughts can be unconscious and subtle. Dr. Niesta believes that colors often have meaning, and that red, particularly in a context of romantic attraction, carries a strong subconscious meaning for men. If she is correct, then colors associated with a romantic context should influence men’s feelings of attraction and interest.

Adobe Flash Player is required.

Get Adobe^® Flash^® Player.

Test My System

Summary of the experiment:

Undergraduate males were randomly assigned to one of two conditions. The men in one group saw a picture of a woman wearing a red blouse and the men in the other condition saw the same picture, except that the blouse had been digitally altered to be blue. The color of the shirt was the independent variable.

Photo captured from “Red: The Color to a Man’s Heart?” by ScienCentral, Inc. Partial Funding by National Science Foundation.

The men then rated the woman on the question:”How attractive do you think this person is?” They answered on a 9-point scale, where 1 was labeled “not at all” and 9 was labeled “extremely.” They were also asked other related questions and answered these on a similar scale.

Photo captured from “Red: The Color to a Man’s Heart?” by ScienCentral, Inc. Partial Funding by National Science Foundation.

The results showed that the woman was rated as more attractive on the average when she was depicted in a red blouse than when she was in a blue blouse. Other related questions showed a similar higher level of attraction for the woman when the shirt was red.

Dr. Niesta also looked at other colors: green, gray, and white. The same pattern of results showed when red was up against these other colors. Men found the woman more attractive when she was wearing red.

Study 3

Background: Dr. Ahmed El-Sohemy is a professor of nutritional science at the University of Toronto. In this study, he was interested in differences in people’s ability to regulate their own food intake, particularly their consumption of sugar. He divided people according to which version of a particular gene they had and studied their eating behavior. Watch the video for more details.

Adobe Flash Player is required.

Get Adobe^® Flash^® Player.

Test My System

Summary of the experiment:

Previous research had indicated to Dr. El-Sohemy that the GLUT2 gene might be involved in regulation of sugar consumption. He recruited volunteers and, using blood samples, divided his volunteers into two groups according to the variation on the GLUT2 gene each person had. The gene with its two variations (alleles) was the quasi-independent variable.

Photo courtesy of National Human Genome Research Institute, Public Domain.

He then had each person fill out an extensive questionnaire on their eating behaviors. For the study reported here, sugar consumption based on these reports was the dependent variable.

Photo captured from "Sweet Tooth Gene" by ScienCentral, Inc. Partial Funding by National Science Foundation.

The researcher found that people with different versions of the gene consumed substantially different amounts of sugar. The researcher speculated that this gene might be associated with sensitivity to sugar so it could influence how much we eat before we feel we have had enough.

Good research is valid research. When research is valid, the conclusions drawn by the researcher are legitimate. For instance, if a researcher concludes that participating in psychotherapy reduces anxiety, or that taller people are smarter than shorter people, the research is valid only if the therapy really works or if taller people really are smarter. Unfortunately, there are many threats to the validity of research, and these threats may sometimes lead to unwarranted conclusions. Often, and despite researchers’ best intentions, some of the research reported on websites as well as in newspapers, magazines, and even scientific journals is invalid. Validity is not an all-or-nothing proposition, which means that some research is more valid than other research. Only by understanding the potential threats to validity will you be able to make knowledgeable decisions about the conclusions that can or cannot be drawn from a research project. Here we discuss two of these major types of threats to the validity of research: internal and external validity.

Two Threats to the Validity of Research

1. Threats to internal validity. Although it is claimed that the independent variable caused the dependent variable, the dependent variable actually may have been caused by a confounding variable.
2. Threats to external validity. Although it is claimed that the results are more general, the observed effects may actually only be found under limited conditions or for specific groups of people. ^[1]

Internal validity refers to the extent to which we can trust the conclusions that have been drawn about the causal relationship between the independent and dependent variables. Internal validity applies primarily to experimental research designs, in which the researcher hopes to conclude that the independent variable has caused the dependent variable. Internal validity is maximized when the research is free from the presence of confounding variables—variables other than the independent variable on which the participants in one experimental condition differ systematically from those in other conditions.

Consider an experiment in which a researcher tested the hypothesis that drinking alcohol makes members of the opposite sex look more attractive. Participants older than 21 years of age were randomly assigned either to drink orange juice mixed with vodka or to drink orange juice alone. To eliminate the need for deception, the participants were told whether or not their drinks contained vodka. After enough time had passed for the alcohol to take effect, the participants were asked to rate the attractiveness of pictures of members of the opposite sex. The results of the experiment showed that, as predicted, the participants who drank the vodka rated the photos as significantly more attractive.

If you think about this experiment for a minute, it may occur to you that although the researcher wanted to draw the conclusion that the alcohol caused the differences in perceived attractiveness, the expectation of having consumed alcohol is confounded with the presence of alcohol. That is, the people who drank alcohol also knew they drank alcohol, and those who did not drink alcohol knew they did not. It is possible that simply knowing that they were drinking alcohol, rather than the effect of the alcohol itself, may have caused the differences as shown in the following figure. One solution to the problem of potential expectancy effects is to tell both groups that they are drinking orange juice and vodka but really give alcohol to only half of the participants (it is possible to do this because vodka has very little smell or taste). If differences in perceived attractiveness are found, the experimenter could then confidently attribute them to the alcohol rather than to the expectancies about having consumed alcohol.

An Example of Confounding

Confounding occurs when a variable that is not part of the research hypothesis is “mixed up,” or confounded with, the variable in the research hypothesis. In the bottom panel alcohol consumed and alcohol expectancy are confounded, but in the top panel they are separate (independent). Confounding makes it impossible to be sure that the independent variable (rather than the confounding variable) caused the dependent variable. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Another threat to internal validity can occur when the experimenter knows the research hypothesis and also knows which experimental condition the participants are in. The outcome is the potential for experimenter bias, a situation in which the experimenter subtly treats the research participants in the various experimental conditions differently, resulting in an invalid confirmation of the research hypothesis. In one study demonstrating experimenter bias, Rosenthal and Fode ^[2] sent twelve students to test a research hypothesis concerning maze learning in rats. Although it was not initially revealed to the students, they were actually the participants in an experiment. Six of the students were randomly told that the rats they would be testing had been bred to be highly intelligent, whereas the other six students were led to believe that the rats had been bred to be unintelligent. In reality there were no differences among the rats given to the two groups of students. When the students returned with their data, a startling result emerged. The rats run by students who expected them to be intelligent showed significantly better maze learning than the rats run by students who expected them to be unintelligent. Somehow the students’ expectations influenced their data. They evidently did something different when they tested the rats, perhaps subtly changing how they timed the maze running or how they treated the rats. And this experimenter bias probably occurred entirely out of their awareness.

To avoid experimenter bias, researchers frequently run experiments in which the researchers are blind to condition. This means that although the experimenters know the research hypotheses, they do not know which conditions the participants are assigned to. Experimenter bias cannot occur if the researcher is blind to condition. In a double-blind experiment, both the researcher and the research participants are blind to condition. For instance, in a double-blind trial of a drug, the researcher does not know whether the drug being given is the real drug or the ineffective placebo, and the patients also do not know which they are getting. Double-blind experiments eliminate the potential for experimenter effects and at the same time eliminate participant expectancy effects.

While internal validity refers to conclusions drawn about events that occurred within the experiment, external validity refers to the extent to which the results of a research design can be generalized beyond the specific way the original experiment was conducted. Generalization is the extent to which relationships among conceptual variables can be demonstrated in a wide variety of people and a wide variety of manipulated or measured variables.

Psychologists who use college students as participants in their research may be concerned about generalization, wondering if their research will generalize to people who are not college students. And researchers who study the behaviors of employees in one company may wonder whether the same findings would translate to other companies. Whenever there is reason to suspect that a result found for one sample of participants would not hold up for another sample, then research may be conducted with these other populations to test for generalization.

Recently, many psychologists have been interested in testing hypotheses about the extent to which a result will replicate across people from different cultures. For instance, a researcher might test whether the effects on aggression of viewing violent video games are the same for Japanese children as they are for American children by showing violent and nonviolent films to a sample of both Japanese and American schoolchildren. If the results are the same in both cultures, then we say that the results have generalized, but if they are different, then we have learned a limiting condition of the effect.

A Cross-Cultural Replicationg

In a cross-cultural replication, external validity is observed if the same effects that have been found in one culture are replicated in another culture. If they are not replicated in the new culture, then a limiting condition of the original results is found. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Unless the researcher has a specific reason to believe that generalization will not hold, it is appropriate to assume that a result found in one population (even if that population is college students) will generalize to other populations. Because the investigator can never demonstrate that the research results generalize to all populations, it is not expected that the researcher will attempt to do so. Rather, the burden of proof rests on those who claim that a result will not generalize.

Because any single test of a research hypothesis will always be limited in terms of what it can show, important advances in science are never the result of a single research project. Advances occur through the accumulation of knowledge that comes from many different tests of the same theory or research hypothesis. These tests are conducted by different researchers using different research designs, participants, and operationalizations of the independent and dependent variables. The process of repeating previous research, which forms the basis of all scientific inquiry, is known as replication.

Did a Neurological Disorder Cause a Musician to Compose Boléro and an Artist to Paint It 66 Years Later?

In 1986 Anne Adams was working as a cell biologist at the University of Toronto in Ontario, Canada. She took a leave of absence from her work to care for a sick child, and while she was away, she completely changed her interests, dropping biology entirely and turning her attention to art. In 1994 she completed her painting Unravelling Boléro, a translation of Maurice Ravel’s famous orchestral piece, Boléro, onto canvas. As you can see in the following image, this artwork is filled with themes of repetition. Each bar of music is represented by a lacy vertical figure, with the height representing volume, the shape representing note quality, and the color representing the music’s pitch. Like Ravel’s music (see the following video), which is a hypnotic melody consisting of two melodial themes repeated eight times over 340 musical bars, the theme in the painting repeats and builds, leading to a dramatic change in color from blue to orange and pink, a representation of Boléro’s sudden and dramatic climax.

Adams’s depiction of Ravel’s orchestral piece Boléro was painted during the very early phase of her illness in 1994. From Flat World Knowledge, Introduction to Psychology, v1.0: Photo courtesy of New Scientist, http://www.newscientist.com/data/images/ns/cms/dn13599/dn13599-1_567.jpg.

This is a video clip of Maurice Ravel's Boléro composed in 1928 during the early phases of his illness.

Shortly after finishing the painting, Adams began to experience behavioral problems, including increased difficulty speaking. Neuroimages of Adams’s brain taken during this time show that regions in the front part of her brain, which are normally associated with language processing, had begun to deteriorate, while at the same time, regions of the brain responsible for the integration of information from the five senses were unusually well developed. ^[1] The deterioration of the frontal cortex is a symptom of frontotemporal dementia, a disease associated with changes in artistic and musical tastes and skills ^[2] as well as with an increase in repetitive behaviors. ^[3]

What Adams did not know as she worked on her painting was that her brain may have been undergoing the same changes that Ravel’s had undergone 66 years earlier. In fact, it appears that Ravel may have suffered from the same neurological disorder. Ravel composed Boléro at age 53, when he himself was beginning to show behavioral symptoms that interfered with his ability to move and speak. Scientists have concluded, on the basis of an analysis of his written notes and letters, that Ravel was also experiencing the effects of frontotemporal dementia. ^[4] If Adams and Ravel were both affected by the same disease, it could explain why they both became fascinated with the repetitive aspects of their arts, and it would present a remarkable example of the influence of our brains on behavior.

Every behavior begins with biology. Our behaviors, as well as our thoughts and feelings, are produced by the actions of our brains, nerves, muscles, and glands. In this unit, we begin our journey into the world of psychology by considering the biological makeup of the human being, including the most remarkable of human organs—the brain. We consider the structure of the brain and the methods psychologists use to study the brain and to understand how it works. Let’s begin by looking at neurons, which are nerve cells involved with all information processing in your brain.

A neuron is a cell in the nervous system whose function it is to receive and transmit information. Amazingly, your nervous system is composed of more than 100 billion neurons!

As you can see in the following figure, neurons consist of three major parts: a cell body, or soma, which contains the nucleus of the cell and keeps the cell alive; a branching, treelike fiber known as the dendrite, which collects information from other cells and sends the information to the soma; and a long, segmented fiber known as the axon, which transmits information away from the cell body toward other neurons or to the muscles and glands.

Components of the Neuron

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

The nervous system, including the brain, is made up of billions of interlinked neurons. This vast interconnected web is responsible for all human thinking, feeling, and behavior. From Flat World Knowledge, Introduction to Psychology, v1.0: Photo courtesy of GE Healthcare, http://www.flickr.com/photos/gehealthcare.

Some neurons have hundreds or even thousands of dendrites, and these dendrites may be branched to allow the cell to receive information from thousands of other cells. The axons are also specialized, and some, such as those that send messages from the spinal cord to the muscles in the hands or feet, may be very long—even up to several feet in length. To improve the speed of their communication, and to keep their electrical charges from shorting out with other neurons, axons are often surrounded by a myelin sheath. The myelin sheath is a layer of fatty tissue surrounding the axon of a neuron that both acts as an insulator and allows faster transmission of the electrical signal. Axons branch out toward their ends, and at the tip of each branch is a terminal button.

The nervous system operates using an electrochemical process (see the following video). An electrical charge moves through the neuron, and chemicals are used to transmit information between neurons. Within the neuron, when a signal is received by the dendrites, it is transmitted to the soma in the form of an electrical signal, and if the signal is strong enough, it may then be passed to the axon and then to the terminal buttons. If the signal reaches the terminal buttons, they are signaled to emit chemicals known as neurotransmitters, which communicate with other neurons across the spaces between the cells, known as synapses. You will be learning more about synapses and why they are important later on in this module.

The electrical signal moves through the neuron as a result of changes in the electrical charge of the axon. Normally, the axon remains in the resting potential, a state in which the interior of the neuron contains a greater number of negatively charged ions than does the area outside the cell. When the segment of the axon that is closest to the cell body is stimulated by an electrical signal from the dendrites, and if this electrical signal is strong enough that it passes a certain level or threshold, the cell membrane in this first segment opens its gates, allowing positively charged sodium ions that were previously kept out to enter. This change in electrical charge that occurs in a neuron when a nerve impulse is transmitted is known as the action potential. Once the action potential occurs, the number of positive ions exceeds the number of negative ions in this segment, and the segment temporarily becomes positively charged.

As you can see in the following figure, the axon is segmented by a series of breaks between the sausage-like segments of the myelin sheath. Each of these gaps is a node of Ranvier. The electrical charge moves down the axon from segment to segment, in a set of small jumps, moving from node to node. When the action potential occurs in the first segment of the axon, it quickly creates a similar change in the next segment, which then stimulates the next segment, and so forth, as the positive electrical impulse continues all the way down to the end of the axon. As each new segment becomes positive, the membrane in the prior segment closes up again, and the segment returns to its negative resting potential. In this way, the action potential is transmitted along the axon toward the terminal buttons. The entire response along the length of the axon is very fast—it can happen up to 1,000 times each second.

The myelin sheath wraps around the axon but also leaves small gaps called the nodes of Ranvier. The action potential jumps from node to node as it travels down the axon. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

An important aspect of the action potential is that it operates in an all-or-nothing manner. What this means is that the neuron either fires completely, such that the action potential moves all the way down the axon, or it does not fire at all. Thus, neurons can provide more energy to the neurons down the line by firing faster but not by firing more strongly. Furthermore, the neuron is prevented from repeated firing by the presence of a refractory period—a brief time after the firing of the axon in which the axon cannot fire again because the neuron has not yet returned to its resting potential.

Not only do neural signals travel via electrical charges within the neuron, but they also travel via chemical transmission between the neurons. As we just learned, neurons are separated by junction areas known as synapses, areas where the terminal buttons at the end of the axon of one neuron nearly, but don’t quite, touch the dendrites of another. The synapses provide a remarkable function because they allow each axon to communicate with many dendrites in neighboring cells. Because a neuron may have synaptic connections with thousands of other neurons, the communication links among the neurons in the nervous system allow for a highly sophisticated communication system.

When the electrical impulse from the action potential reaches the end of the axon, it signals the terminal buttons to release neurotransmitters into the synapse. A neurotransmitter is a chemical that relays signals across the synapses between neurons. Neurotransmitters travel across the synaptic space between the terminal button of one neuron and the dendrites of other neurons, where they bind to the dendrites in the neighboring neurons. Furthermore, different terminal buttons release different neurotransmitters, and different dendrites are particularly sensitive to different neurotransmitters. The dendrites admit the neurotransmitters only if they are the right shape to fit in the receptor sites on the receiving neuron. For this reason, the receptor sites and neurotransmitters are often compared to a lock and key, as shown in the following figure.

To explore the process of neurotransmission, watch this animation.

When the nerve impulse reaches the terminal button, it triggers the release of neurotransmitters into the synapse. The neurotransmitters fit into receptors on the receiving dendrites in the manner of a lock and key. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

When neurotransmitters are accepted by the receptors on the receiving neurons, their effect may be either excitatory (i.e., they make the cell more likely to fire) or inhibitory (i.e., they make the cell less likely to fire). Furthermore, if the receiving neuron is able to accept more than one neurotransmitter, it is influenced by the excitatory and inhibitory processes of each. If the excitatory effects of the neurotransmitters are greater than the inhibitory influences of the neurotransmitters, the neuron moves closer to its firing threshold, and if it reaches the threshold, the action potential and the process of transferring information through the neuron begins.

Neurotransmitters that are not accepted by the receptor sites must be removed from the synapse in order for the next potential stimulation of the neuron to happen. This process occurs in part through the breaking down of the neurotransmitters by enzymes, and in part through reuptake, a process in which neurotransmitters that are in the synapse are reabsorbed into the transmitting terminal buttons, ready to again be released after the neuron fires.

More than 100 chemical substances produced in the body have been identified as neurotransmitters, and these substances have a wide and profound effect on emotion, cognition, and behavior. Neurotransmitters regulate our appetite, our memory, our emotions, as well as our muscle action and movement. And as you can see in the following table, some neurotransmitters are also associated with psychological and physical diseases.

Drugs that we might ingest—either for medical reasons or recreationally—can act like neurotransmitters to influence our thoughts, feelings, and behavior. An agonist is a drug that has chemical properties similar to a particular neurotransmitter and thus mimics the effects of the neurotransmitter. When an agonist is ingested, it binds to the receptor sites in the dendrites to excite the neuron, acting as if more of the neurotransmitter had been present. As an example, cocaine is an agonist for the neurotransmitter dopamine. Because dopamine produces feelings of pleasure when it is released by neurons, cocaine creates similar feelings when it is ingested. An antagonist is a drug that reduces or stops the normal effects of a neurotransmitter. When an antagonist is ingested, it binds to the receptor sites in the dendrite, thereby blocking the neurotransmitter. As an example, the poison curare is an antagonist for the neurotransmitter acetylcholine. When the poison enters the brain, it binds to the dendrites, stops communication among the neurons, and usually causes death. Still other drugs work by blocking the reuptake of the neurotransmitter itself—when reuptake is reduced by the drug, more neurotransmitter remains in the synapse, increasing its action.

If you were someone who understood brain anatomy and were to look at the brain of an animal that you had never seen before, you would nevertheless be able to deduce the likely capacities of the animal because the brains of all animals are much alike in overall form. In each animal the brain is layered, and the basic structures of the brain are similar. The innermost structures of the brain—the parts nearest the spinal cord—are the oldest part of the brain, and these areas carry out the same functions they did for our distant ancestors. The “old brain” regulates basic survival functions, such as breathing, moving, resting, and feeding, and creates our experiences of emotion. Mammals, including humans, have developed further brain layers that provide more advanced functions—for instance, better memory, more sophisticated social interactions, and the ability to experience emotions. Humans have a large and highly developed outer layer known as the cerebral cortex, which makes us particularly adept at these processes.

The Major Structures in the Human Brain

From Flat World Knowledge, Introduction to Psychology, v1.0: Adapted from Camazine, S. (n.d.). Images of the brain: Medical, science, and nature things. Photography and digital imagery by Scott Camazine.

The Cerebral Cortex

Humans have a large and highly developed outer brain layer known as the cerebral cortex. The cortex provides humans with excellent memory, outstanding cognitive skills, and the ability to experience complex emotions. From Flat World Knowledge, Introduction to Psychology, v1.0: Adapted from Wikia Education. (n.d.). Cerebral cortex.

The brain stem is the oldest and innermost region of the brain. It controls the most basic functions of life, including breathing, attention, and motor responses. The brain stem begins where the spinal cord enters the skull and forms the medulla, the area of the brain stem that controls heart rate and breathing. In many cases, the medulla alone is sufficient to maintain life—animals that have their brains severed above the medulla are still able to eat, breathe, and even move. The spherical shape above the medulla is the pons, a structure in the brain stem that helps control the movements of the body, playing a particularly important role in balance and walking. The pons is also important in sleeping, waking, dreaming, and arousal.

Running through the medulla and the pons is a long, narrow network of neurons known as the reticular formation. The job of the reticular formation is to filter out some of the stimuli that are coming into the brain from the spinal cord and to relay the remainder of the signals to other areas of the brain. The reticular formation also plays important roles in walking, eating, sexual activity, and sleeping. When electrical stimulation is applied to the reticular formation of an animal, it immediately becomes fully awake, and when the reticular formation is severed from the higher brain regions, the animal falls into a deep coma.

The Brain Stem

The brain stem is an extension of the spinal cord, including the medulla, the pons, the thalamus, and the reticular formation. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Two structures near the brain stem are also vital for basic survival functions. The thalamus is the egg-shaped structure sitting just above the brain stem that applies still more filtering to the sensory information coming from the spinal cord and through the reticular formation, and it relays some of these remaining signals to the higher brain levels. ^[1] The thalamus also receives some of the higher brain’s replies, forwarding them to the medulla and the cerebellum. The thalamus is also important in sleep because it shuts off incoming signals from the senses, allowing us to rest.

The cerebellum (literally, “little brain”) consists of two wrinkled ovals behind the brain stem. It functions to coordinate voluntary movement. People who have damage to the cerebellum have difficulty walking, keeping their balance, and holding their hands steady. Consuming alcohol influences the cerebellum, which is why people who are drunk have difficulty walking in a straight line. Also, the cerebellum contributes to emotional responses, helps us discriminate between different sounds and textures, and is important in learning. ^[2]

Whereas the primary function of the brain stem is to regulate the most basic aspects of life, including motor functions, the limbic system is largely responsible for memory and emotions, including our responses to reward and punishment. The limbic system is a set of distinct and important brain structures located beneath and around the thalamus. Limbic system structures interact with the rest of the brain in complex ways, and they are extremely important for memory and control of emotional responses. They include the amygdala, the hypothalamus, and the hippocampus, among other structures.

The Limbic System

This diagram shows the major parts of the limbic system, as well as the pituitary gland, which is controlled by it. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

The amygdala consists of two almond-shaped clusters (amygdala comes from the Latin word for almond) and is primarily responsible for regulating our perceptions of and reactions to aggression and fear. The amygdala has connections to other bodily systems related to fear, including the sympathetic nervous system (which we will see later is important in fear responses), facial responses (which perceive and express emotions), the processing of smells, and the release of neurotransmitters related to stress and aggression. ^[1] In a 1939 study, Klüver and Bucy ^[2] damaged the amygdala of an aggressive rhesus monkey. They found that the once angry animal immediately became passive and no longer responded to fearful situations with aggressive behavior. Electrical stimulation of the amygdala in other animals also influences aggression. In addition to helping us experience fear, the amygdala helps us learn from situations that create fear. When we experience events that are dangerous, the amygdala stimulates the brain to remember the details of the situation so that we learn to avoid it in the future. ^[3]

Located just under the thalamus (hence its name), the hypothalamus is a brain structure that contains a number of small areas that perform a variety of functions. Through its many interactions with other parts of the brain, the hypothalamus helps regulate body temperature, hunger, thirst, and sex drive and responds to the satisfaction of these needs by creating feelings of pleasure.

The hippocampus consists of two “horns” that curve back from the amygdala. The hippocampus is important in storing information in long-term memory. If the hippocampus is seriously damaged on both sides of the brain, a person may be unable to store new long-term memories, living instead in a strange world where everything he or she experiences just fades away, even while older memories from the time before the damage are untouched.

All animals have adapted to their environments by developing abilities that help them survive. Some animals have hard shells, others run extremely fast, and some have acute hearing. Human beings do not have any of these particular characteristics, but we do have one big advantage over other animals—we are very, very smart.

You might think we should be able to determine the intelligence of an animal by looking at the ratio of the animal’s brain weight to the weight of its entire body. But brain size is not a measure of intelligence. The elephant’s brain is one-thousandth of its body weight, but the whale’s brain is only one-ten-thousandth of its body weight. On the other hand, although the human brain is one-sixtieth of its body weight, the mouse’s brain represents one fortieth of its body weight. Despite these comparisons, elephants do not seem 10 times smarter than whales, and humans definitely seem smarter than mice.

The key to the advanced intelligence of humans is not found in the size of our brains. What sets humans apart from other animals is our larger cerebral cortex—the outer barklike layer of our brain that allows us to so successfully use language, acquire complex skills, create tools, and live in social groups. ^[1] In humans, the cerebral cortex is wrinkled and folded rather than smooth, as it is in most other animals. This creates a much greater surface area and size. and allows increased capacities for learning, remembering, and thinking. The folding of the cerebral cortex is called corticalization.

Although the cortex is only about one tenth of an inch thick, it makes up more than 80% of the brain’s weight. The cortex contains about 20 billion nerve cells and 300 trillion synaptic connections. ^[2] Supporting all these neurons are billions more glial cells (glia), cells that surround and link to the neurons, protecting them, providing them with nutrients, and absorbing unused neurotransmitters. The glia come in different forms and have different functions. For instance, the myelin sheath surrounding the axon of many neurons is a type of glial cell. The glia are essential partners of neurons, without which the neurons could not survive or function. ^[3]

The cerebral cortex is divided into two hemispheres, and each hemisphere is divided into four lobes, each separated by folds known as fissures. If we look at the cortex starting at the front of the brain and moving over the top, we see first the frontal lobe (behind the forehead), which is responsible primarily for thinking, planning, memory, and judgment. Following the frontal lobe is the parietal lobe, which extends from the middle to the back of the skull and is responsible primarily for processing information about touch. Then comes the occipital lobe, at the very back of the skull, which processes visual information. Finally, in front of the occipital lobe (pretty much between the ears) is the temporal lobe, responsible primarily for hearing and language.

Hemispheres and Lobes of the Cerebral Cortex

The brain's cerebral cortex is divided into two hemispheres (left and right), each of which has four lobes (temporal, frontal, occipital, and parietal). Complex processes such as planning, interpreting sensory input, and learning are controlled by specific cortical areas. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Functions of the Cortex

When the German physicists Gustav Fritsch and Eduard Hitzig (1870/2009) applied mild electric stimulation to different parts of a dog’s cortex, they discovered that they could make different parts of the dog’s body move. ^[4] They also discovered an important and unexpected principle of brain activity. They found that stimulating the right side of the brain produced movement in the left side of the dog’s body, and conversely, stimulating the left brain affected the right side of the body. This finding follows from a general principle about how the brain is structured, called contralateral control. The brain is wired such that in most cases the left hemisphere receives sensations from and controls the right side of the body, and vice versa.

Fritsch and Hitzig also found that the movement that followed the brain stimulation occurred only when they stimulated a specific arch-shaped region that runs across the top of the brain from ear to ear, just at the front of the parietal lobe. Fritsch and Hitzig had discovered the motor cortex, the part of the cortex that controls and executes movements of the body by sending signals to the cerebellum and the spinal cord. More recently, researchers have mapped the motor cortex even more fully by providing mild electronic stimulation to different areas of the motor cortex in fully conscious participants while observing their bodily responses (because the brain has no sensory receptors, these participants feel no pain). As you can see in the following figure, this research has revealed that the motor cortex is specialized for providing control over the body: The parts of the body that require more precise and finer movements, such as the face and hands, also are allotted the greatest amount of cortical space.

The Sensory and Motor Cortex

The portion of the sensory and motor cortex devoted to receiving messages that control specific regions of the body is determined by the amount of fine movement that area is capable of performing. Thus, the hand and fingers have as much area in the cerebral cortex as does the entire trunk of the body. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Just as the motor cortex sends out messages to the specific parts of the body, the somatosensory cortex, an area just behind and parallel to the motor cortex at the back of the frontal lobe, receives information from the skin’s sensory receptors and the movements of different body parts. Again, the more sensitive the body region, the more area is dedicated to it in the sensory cortex. Our sensitive lips, for example, occupy a large area in the sensory cortex, as do our fingers and genitals.

Other areas of the cortex process other types of sensory information. The visual cortex is the area located in the occipital lobe (at the very back of the brain) that processes visual information. If you were stimulated in the visual cortex, you would see flashes of light or color, and perhaps you have had the experience of “seeing stars” when you were hit in or fell on the back of your head. The temporal lobe, located on the lower side of each hemisphere, contains the auditory cortex, which is responsible for hearing and language. The temporal lobe also processes some visual information, providing us with the ability to name the objects around us. ^[5]

As you can see in the preceding figure, the motor and sensory areas of the cortex account for a relatively small part of the total cortex. The remainder of the cortex is made up of association areas in which sensory and motor information are combined and associated with our stored knowledge. These association areas are responsible for most of the things that make human beings seem human—the higher mental functions, such as learning, thinking, planning, judging, moral reflecting, figuring, and spatial reasoning.

The control of some bodily functions, such as movement, vision, and hearing, is performed in specific areas of the cortex, and if an area is damaged, the individual will likely lose the ability to perform the corresponding function. For instance, if an infant suffers damage to facial recognition areas in the temporal lobe, it is likely that he or she will never be able to recognize faces. ^[1] However, the brain is not divided in an entirely rigid way. The brain’s neurons have a remarkable capacity to reorganize and extend themselves to carry out particular functions in response to the needs of the organism and to repair damage. As a result, the brain constantly creates new neural communication routes and rewires existing ones. Neuroplasticity is the brain’s ability to change its structure and function in response to experience or damage. Neuroplasticity enables us to learn and remember new things and adjust to new experiences.

Our brains are the most “plastic” when we are young children, as it is during this time that we learn the most about our environment. And neuroplasticity continues to be observed even in adults. ^[2] The principles of neuroplasticity help us understand how our brains develop to reflect our experiences. For instance, accomplished musicians have a larger auditory cortex compared with the general population ^[3] and also require less neural activity to play their instruments than do novices. ^[4] These observations reflect the changes in the brain that follow our experiences.

Plasticity is also observed when damage occurs to the brain or to parts of the body that are represented in the motor and sensory cortexes. When a tumor in the left hemisphere of the brain impairs language, the right hemisphere begins to compensate to help the person recover the ability to speak. ^[5] And if a person loses a finger, the area of the sensory cortex that previously received information from the missing finger begins to receive input from adjacent fingers, causing the remaining digits to become more sensitive to touch. ^[6]

Although neurons cannot repair or regenerate themselves as skin and blood vessels can, new evidence suggests that the brain can engage in neurogenesis, the forming of new neurons. ^[7] These new neurons originate deep in the brain and may then migrate to other brain areas where they form new connections with other neurons. ^[8] This leaves open the possibility that someday scientists might be able to “rebuild” damaged brains by creating drugs that help grow neurons.

Visual and Verbal Processing in the Split-Brain Patient

The information presented on the left side of our field of vision is transmitted to the right brain hemisphere, and vice versa. In split-brain patients, the severed corpus callosum does not permit information to be transferred between hemispheres, which allows researchers to learn about the functions of each hemisphere.

In the sample on the left, the split-brain patient could not choose which image had been presented because the left hemisphere cannot process visual information. In the sample on the right, the patient could not read the passage because the right brain hemisphere cannot process language. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

This research, and many other studies following it, demonstrated that the two brain hemispheres specialize in different abilities. In most people, the ability to speak, write, and understand language is located in the left hemisphere. This is why W. J. could read passages that were presented on the right side and thus transmitted to the left hemisphere, but could not read passages that were only experienced in the right brain hemisphere. The left hemisphere is also better at math and at judging time and rhythm. It is also superior in coordinating the order of complex movements—for example, lip movements needed for speech. The right hemisphere has only limited verbal abilities, and yet it excels in perceptual skills. The right hemisphere is able to recognize objects, including faces, patterns, and melodies, and it can put a puzzle together or draw a picture. This is why W. J. could pick out the image when he saw it on the left, but not the right, visual field.

Although Gazzaniga’s research demonstrated that the brain is in fact lateralized, such that the two hemispheres specialize in different activities, this does not mean that when people behave in a certain way or perform a certain activity they are using only one hemisphere of their brains at a time. That would be drastically oversimplifying the concept of brain differences. We normally use both hemispheres at the same time, and the difference between the abilities of the two hemispheres is not absolute. ^[11]

Lesion studies are done using various neuroimaging methods that can record electrical activity in the brain, visualize blood flow and areas of brain activity in real time, provide cross-sectional images, and even provide computer-generated three-dimensional composites of the brain.

The single-unit recording method, in which a thin microelectrode is surgically inserted in or near an individual neuron, is used primarily with animals. The microelectrode records electrical responses or activity of the specific neuron. Research using this method has found, for instance, that specific neurons, known as feature detectors, in the visual cortex detect movement, lines, edges, and even faces. ^[1]

A less invasive electrical method that is used on humans is called the electroencephalograph (EEG). The EEG is an instrument that records the electrical activity produced by the brain’s neurons through the use of electrodes placed on the surface of the research participant’s head. An EEG can show if a person is asleep, awake, or anesthetized because the brain wave patterns are known to differ during each state. EEGs can also track the waves that are produced when a person is reading, writing, and speaking and are useful for understanding brain abnormalities, such as epilepsy. A particular advantage of EEG is that the participant can move around while the recordings are being taken, which is useful when measuring brain activity in children who often have difficulty keeping still. Furthermore, by following electrical impulses across the surface of the brain, researchers can observe changes over very short time periods (microseconds).

Electroencephalograph, an Instrument That Records Electrical Currents from a Brain

Photo by Yury Petrovich Masloboev, Electroencephalograph Neurovisor-BMM 40, CC-BY-2.5.

A Participant in an EEG Study

A participant in an EEG study has a number of electrodes placed around the head, which allows the researcher to study the activity of the person’s brain. The patterns of electrical activity vary depending on the participant’s current state (e.g., whether he or she is sleeping or awake) and on the tasks the person is engaging in. From Flat World Knowledge Introduction to Psychology, v1.0: Photo courtesy of the University of Oregon Child and Family Center, http://www.uoregon.edu/~cfc/projects-bbl.htm.

Although the EEG can provide information about the general patterns of electrical activity within the brain, and although the EEG allows the researcher to see these changes quickly as they occur in real time, the electrodes must be placed on the surface of the skull, and each electrode measures brain waves from large areas of the brain. As a result, EEGs do not provide a very clear picture of the structure of the brain.

Positron Emission Tomography (PET Scan) Machine

Photo by Jens Langner, ECAT Exact HR+ PET scanner. Public Domain

PET Scan of a Healthy Brain

Photo by Jens Langner, PET image. Public Domain.

But other methods exist to provide more specific brain images. The positron emission tomography (PET) scan is an invasive imaging technique that provides color-coded images of brain activity by tracking the brain’s use of a radioactively tagged compound, such as glucose, oxygen, or a drug that has been injected into a person’s bloodstream. The person lies in a PET scanner and performs a mental task, such as recalling a list of words or solving an arithmetic problem, while the PET scanner tracks the amounts of radioactive substance that causes metabolic changes in different brain regions as they are stimulated by a person’s activity. A computer analyzes the data, producing color-coded images of the brain’s activity. A PET scan can determine levels of activity when a person is given a task that requires hearing, seeing, speaking, or thinking.

fMRI Machine

Photo by Semiconscious, Varian 4T fMRI. Public Domain.

fMRI of a Healthy Brain (Left) and a Schizophrenic Brain

Photo courtesy of J. Kim, N. L. Matthews, and S. Park, http://www.plosone.org/article/info:doi/10.1371/journal.pone.002276, CC-BY-2.5.

Functional magnetic resonance imaging (fMRI) is a type of brain scan that uses a magnetic field to create images of brain activity in each brain area. The patient lies on a bed in a large cylindrical structure containing a very strong magnet. Neurons that are firing use more oxygen than neurons that are not firing, and the need for oxygen increases blood flow to the area. The fMRI detects the amount of blood flow in each brain region and thus is an indicator of neural activity.

Very clear and detailed pictures of brain structures can be produced via fMRI. Often, the images take the form of cross-sectional “slices” that are obtained as the magnetic field is passed across the brain. The images of these slices are taken repeatedly and are superimposed on images of the brain structure itself to show how activity changes in different brain structures over time. When the research participant is asked to engage in tasks (e.g., playing a game with another person), the images can show which parts of the brain are associated with which types of tasks. Another advantage of the fMRI is that is it noninvasive. The research participant simply enters the machine and the scans begin.

Although the scanners are expensive, the advantages of fMRI are substantial, and the machines are now available in many university and hospital settings. fMRI is now the most commonly used method of learning about brain structure.

fMRI Brain Image with Color Activity Scale

The fMRI creates images of brain structure and activity. In this image, the red and yellow areas represent increased blood flow and thus increased activity. From your knowledge of brain structure, can you guess what this person is doing? From Flat World Knowledge, Introduction to Psychology, v1.0: Photo courtesy of the National Institutes of Health, Face recognition.

A new approach that is being more frequently implemented to understand brain function, transcranial magnetic stimulation (TMS), may turn out to be the most useful of all. TMS is a procedure in which magnetic pulses are applied to the brain of living persons with the goal of temporarily and safely deactivating a small brain region. In TMS studies, the research participant is first scanned in an fMRI machine to determine the exact location of the brain area to be tested. Then the electrical stimulation is provided to the brain before or while the participant works on a cognitive task, and the effects of the stimulation on performance are assessed. If the participant’s ability to perform the task is influenced by the presence of the stimulation, then the researchers can conclude that this particular area of the brain is important to carrying out the task.

Transcranial Magnetic Stimulation (TMS) Equipment

Photos by MistyHora at English-Language Wikipedia, TMS focal field, TMS Butterfly Coil HEAD, CC-BY-SA.

The primary advantage of TMS is that it allows the researcher to draw causal conclusions about the influence of brain structures on thoughts, feelings, and behaviors. When the TMS pulses are applied, the brain region becomes less active, and this deactivation is expected to influence the research participant’s responses. Current research has used TMS to study the brain areas responsible for emotion and cognition and their roles in how people perceive intention and approach moral reasoning. ^{[1] [2] [3]} TMS is also used as a treatment for a variety of conditions, including migraine, Parkinson disease, and major depressive disorder.

learn by doing

Recall what you learned about the amygdala in the previous module. The amygdala is a small, almond-shaped group of nuclei found at the base of the temporal lobe. Research has shown that the amygdala performs a primary role in the processing and memory of emotional reactions.

Using an fMRI machine, researchers assessed differences in the amygdala activity of participants when they viewed either expressions on a human face (figure on the left) or geometric shapes (figure on the right). While each participant was in the fMRI machine, he or she was told to identify either the two identical faces or the two identical shapes within a trio. This simple cognitive task was used to keep the participants’ gaze and attention on either the faces or the shapes so that the fMRI machine could record the activity of the amygdala in both conditions (faces or shapes). Then the activity level of the amygdala (its activation or lack of activation) was compared between the two conditions.

Woman with glasses photo by Tine Steiss, I'll bite off your nose!; frightened woman photo by Alexowolff, Angizia; CC-BY-SA.Adapted from image by Amber Rieder, Jenna Traynor, and Geoff B Hall, MRI coronal view of the amygdala, Public Domain.

Study the fMRI image above. Using what you have learned about the amygdala and how the fMRI records activation in the brain, answer the following two questions.

Now that we have considered how individual neurons operate and the roles of the different brain areas, it is time to ask how the body manages to “put it all together.” How do the complex activities in the various parts of the brain, the simple all-or-nothing firings of billions of interconnected neurons, and the various chemical systems within the body, work together to allow the body to respond to the social environment and engage in everyday behaviors? In this section, we will see that the complexities of human behavior are accomplished through the joint actions of electrical and chemical processes in the nervous system and the endocrine system.

The nervous system, the electrical information highway of the body, is made up of nerves—bundles of interconnected neurons that fire in synchrony to carry messages. The central nervous system (CNS) , made up of the brain and spinal cord, is the major controller of the body’s functions, charged with interpreting sensory information and responding to it with its own directives. The CNS interprets information coming in from the senses, formulates an appropriate reaction, and sends responses to the appropriate system to respond accordingly. Everything we see, hear, smell, touch, and taste is conveyed to us from our sensory organs as neural impulses, and each of the commands that the brain sends to the body, both consciously and unconsciously, travels through this system as well.

The Central Nervous System

The central nervous system consists of the brain and the spinal cord. The CNS controls all processing and interpretation of sensory information and our responses to the information.

Nerves are differentiated according to their function. A sensory neuron carries information from the sensory receptors, whereas a motor neuron transmits information to the muscles and glands. An interneuron, which is by far the most common type of neuron, is located primarily within the CNS and is responsible for communicating among the neurons. Interneurons allow the brain to combine the multiple sources of available information to create a coherent picture of the sensory information being conveyed.

The spinal cord is the long, thin, tubular bundle of nerves and supporting cells that extends down from the brain. It is the central pathway of information for the body. Within the spinal cord, ascending tracts of sensory neurons relay sensory information from the sense organs to the brain while descending tracts of motor neurons relay motor commands back to the body. When a quicker-than-usual response is required, the spinal cord can do its own processing, bypassing the brain altogether. A reflex is an involuntary and nearly instantaneous movement in response to a stimulus. Reflexes are triggered when sensory information is powerful enough to reach a given threshold and the interneurons in the spinal cord act to send a message back through the motor neurons without relaying the information to the brain, as shown in the following figure. When you touch a hot stove and immediately pull your hand back, or when you fumble your cell phone and instinctively reach to catch it before it falls, reflexes in your spinal cord order the appropriate responses before your brain even knows what is happening.

Reflex Response

The central nervous system can interpret signals from sensory neurons and respond to them extremely quickly via the motor neurons without any need for the brain to be involved. These quick responses, known as reflexes, can reduce the damage that we might experience as a result of, for instance, touching a hot stove. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

If the central nervous system is the command center of the body, the peripheral nervous system (PNS) represents the front line. The PNS links the CNS to the body’s sense receptors, muscles, and glands. As you can see in the following figure, the PNS is divided into two subsystems, one controlling internal responses and one controlling external responses.

The Functional Divisions of the Nervous System

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

The autonomic nervous system (ANS) is the division of the PNS that governs the internal activities of the human body, including heart rate, breathing, digestion, salivation, perspiration, urination, and sexual arousal. Many of the actions of the ANS, such as heart rate and digestion, are automatic and out of our conscious control, but others, such as breathing and sexual activity, can be controlled and influenced by conscious processes.

The somatic nervous system (SNS) is the division of the PNS that controls the external aspects of the body, including the skeletal muscles, skin, and sense organs. The somatic nervous system consists primarily of motor nerves responsible for sending brain signals for muscle contraction.

The autonomic nervous system itself can be further subdivided into the sympathetic and parasympathetic systems (see figure below). The sympathetic division of the ANS is involved in preparing the body for rapid action in response to stress from threats or emergencies by activating the organs and glands in the endocrine system. When the sympathetic nervous system recognizes danger or a threat, the heart beats faster, breathing accelerates, and lungs and bronchial tubes expand. These physiological responses increase the amount of oxygen to the brain and muscles to prepare your body for defense. In other sympathetic nervous system responses, your pupils dilate to increase your field of vision, salivation stops and your mouth becomes dry, digestion stops in your stomach and intestines, and you begin to sweat due to your body’s use of more energy and heat. These bodily changes collectively represent the fight-or-flight response, which prepares you to either fight or flee from a perceived danger.

The parasympathetic division of the ANS tends to calm the body by slowing the heart and breathing and by allowing the body to recover from the activities that the sympathetic system causes. The parasympathetic nervous system acts more slowly than the sympathetic nervous system as it calms the activated organs and glands of the endocrine system, eventually returning your body to a normal state, called homeostasis.

The Two Divisions of the Autonomic Nervous System

The autonomic nervous system has two divisions: The sympathetic division acts the energize the body, preparing it for action. The parasympathetic division acts to calm the body, allowing it to rest. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Our everyday activities are also controlled by the interaction between the sympathetic and parasympathetic nervous systems. For example, when we get out of bed in the morning, we would experience a sharp drop in blood pressure if it were not for the action of the sympathetic system, which automatically increases blood flow through the body. Similarly, after we eat a big meal, the parasympathetic system automatically sends more blood to the stomach and intestines, allowing us to efficiently digest the food. And perhaps you’ve had the experience of not being at all hungry before a stressful event, such as a sports game or an exam (when the sympathetic division was primarily in action), but suddenly finding yourself starved afterward, as the parasympathetic system takes over. The two systems work together to maintain vital bodily functions, resulting in homeostasis, the natural balance in the body’s systems.

As you have seen, the nervous system is divided structurally into the central nervous system and the peripheral nervous system. The PNS is further divided into subdivisions, each having a particular function in the nervous system to help regulate the body. In the following activity, you will learn the function of each of the nervous system divisions by matching a specific descriptive function with each structure.

There are three major types of transduction:

1. Photoreaction: Photo means “light,” so one type of transduction is the reaction of a chemical in a nerve cell. This is the basis of vision.
2. Mechanical Reactions: Physical movement of attachments to some nerve cells or physical pressure against others starts transduction in three systems:
   1. Our sense of hearing works by fluids in the inner ear brushing against hair cells attached to neurons. The movement of the fluid is produced by sound waves.
   2. Our sense of balance also works in a very similar way to our sense of hearing: a gelatin-like mass in the semicircular canals of your inner ear brush against hair cells attached to neurons.
   3. Our skin senses have four different kinds of detectors, and three of them respond to physical pressure. We have a soft touch detectors and strong pressure detectors. Pain detectors respond to strong and potentially damaging physical contact. Finally, we have hot/cold detectors that respond to the temperature.
3. Molecular Reactions: Two of our senses are sensitive to molecules in the world around us.
   1. Our sense of taste is based on taste buds on our tongue that respond to molecules in the substances that touch the tongue. The taste buds also sort the molecules into different types, giving us the variety—like sweetness and bitterness—that we are able to taste.
   2. Our sense of smell is based on specialized detectors in our nasal cavity that detect different kinds of molecules floating in the air. Like taste, smell categorizes the molecules into different types to give of the wonderful range of odors we can detect.

To explore the various senses further, go to this website of the BBC (British Broadcasting System) and click on each of the senses listed.

Web page from BBC Science.

The Eye

Light enters the eye through the transparent cornea, passing through the pupil at the center of the iris. The lens adjusts to focus the light on the retina, where it appears upside down and backward. Receptor cells on the retina send information via the optic nerve to the visual cortex. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

As you can see in the above figure, light enters the eye through the cornea, a clear covering that protects the eye and begins to focus the incoming light. The light then passes through the pupil, a small opening in the center of the eye. The pupil is surrounded by the iris, the colored part of the eye that controls the size of the pupil by constricting or dilating in response to light intensity. When we enter a dark movie theater on a sunny day, for instance, muscles in the iris open the pupil and allow more light to enter. Complete adaptation to the dark may take up to 20 minutes.

Behind the pupil is the lens, a structure that focuses the incoming light on the retina, the layer of tissue at the back of the eye that contains photoreceptor cells. As our eyes move from near objects to distant objects, a process known as accommodation occurs. Accommodation is the process of changing the curvature of the lens to keep the light entering the eye focused on the retina. Rays from the top of the image strike the bottom of the retina, and vice versa, and rays from the left side of the image strike the right part of the retina, and vice versa, causing the image on the retina to be upside down and backward. Furthermore, the image projected on the retina is flat, and yet our final perception of the image will be three dimensional.

Accommodation is not always perfect, and in some cases the light hitting the retina is a bit out of focus. As you can see in the figure below, when the focus is in front of the retina, we say that the person is nearsighted, and when the focus is behind the retina we say that the person is farsighted. Eyeglasses and contact lenses correct this problem by adding another lens in front of the eye. Laser eye surgery corrects the problem by reshaping the eye's cornea, while another type of surgery involves replacing the eye's own lens.

Nearsightedness and Farsightedness

For people with normal vision (left), the lens properly focuses incoming light on the retina. For people who are nearsighted (center), images from far objects focus too far in front of the retina, whereas for people who are farsighted (right), images from near objects focus too far behind the retina. Eyeglasses solve the problem by adding a secondary, corrective, lens. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

The retina contains layers of neurons specialized to respond to light (see the figure below). As light falls on the retina, it first activates receptor cells known as rods and cones. The activation of these cells then spreads to the bipolar cells and then to the ganglion cells, which gather together and converge, like the strands of a rope, forming the optic nerve. The optic nerve is a collection of millions of ganglion neurons that sends vast amounts of visual information, via the thalamus, to the brain. Because the retina and the optic nerve are active processors and analyzers of visual information, it is not inappropriate to think of these structures as an extension of the brain itself.

The Retina

When light falls on the retina, it creates a photochemical reaction in the rods and cones at the back of the retina. The reactions then continue to the bipolar cells, the ganglion cells, and eventually to the optic nerve. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Rods are visual neurons that specialize in detecting black, white, and gray colors. There are about 120 million rods in each eye. The rods do not provide a lot of detail about the images we see, but because they are highly sensitive to shorter-waved (darker) and weak light, they help us see in dim light, for instance, at night. Because the rods are located primarily around the edges of the retina, they are particularly active in peripheral vision (when you need to see something at night, try looking away from what you want to see). Cones are visual neurons that are specialized in detecting fine detail and colors. The 5 million or so cones in each eye enable us to see in color, but they operate best in bright light. The cones are located primarily in and around the fovea, which is the central point of the retina.

To demonstrate the difference between rods and cones in attention to detail, choose a word in this text and focus on it. Do you notice that the words a few inches to the side seem more blurred? This is because the word you are focusing on strikes the detail-oriented cones, while the words surrounding it strike the less-detail-oriented rods, which are located on the periphery.

Mona Lisa's Smile

Margaret Livingstone found an interesting effect that demonstrates the different processing capacities of the eye’s rods and cones—namely, that the Mona Lisa’s smile, which is widely referred to as “elusive,” is perceived differently depending on how one looks at the painting. Because Leonardo da Vinci painted the smile in low-detail brush strokes, these details are better perceived by our peripheral vision (the rods) than by the cones. Livingstone found that people rated the Mona Lisa as more cheerful when they were instructed to focus on her eyes than they did when they were asked to look directly at her mouth. As Livingstone put it, “She smiles until you look at her mouth, and then it fades, like a dim star that disappears when you look directly at it.” From Flat World Knowledge, Introduction to Psychology, v1.0: Photo courtesy of the Louvre Museum, Mona_Lisa_detail_face.

As you can see in the figure below, the sensory information received by the retina is relayed through the thalamus to corresponding areas in the visual cortex, which is located in the occipital lobe at the back of the brain. (Hint: You can remember that the occipital lobe processes vision because it starts with the letter O, which is round like an eye.) Although the principle of contralateral control might lead you to expect that the left eye would send information to the right brain hemisphere and vice versa, nature is smarter than that. In fact, the left and right eyes each send information to both the left and the right hemispheres, and the visual cortex processes each of the cues separately and in parallel. This is an adaptational advantage to an organism that loses sight in one eye, because even if only one eye is functional, both hemispheres will still receive input from it.

The Visual Pathways

The left and right eyes each send information to both the left and the right brain hemispheres. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

The visual cortex is made up of specialized neurons that turn the sensations they receive from the optic nerve into meaningful images. Because there are no photoreceptor cells at the place where the optic nerve leaves the retina, a hole or blind spot in our vision is created (see the figure below). When both of our eyes are open, we don’t experience a problem because our eyes are constantly moving, and one eye makes up for what the other eye misses. But the visual system is also designed to deal with this problem if only one eye is open—the visual cortex simply fills in the small hole in our vision with similar patterns from the surrounding areas, and we never notice the difference. The ability of the visual system to cope with the blind spot is another example of how sensation and perception work together to create meaningful experience.

learn by doing

You can get an idea of the extent of your blind spot (the place where the optic nerve leaves the retina) by trying this demonstration. Close your left eye and stare with your right eye at the cross in the diagram. You should be able to see the elephant image to the right (don’t look at it, just notice that it is there). If you can’t see the elephant, move closer or farther away until you can. Now slowly move so that you are closer to the image while you keep looking at the cross. At one distance (probably a foot or so), the elephant will completely disappear from view because its image has fallen on the blind spot.

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Perception is created in part through the simultaneous action of thousands of feature detector neurons—specialized neurons, located in the visual cortex, that respond to the strength, angles, shapes, edges, and movements of a visual stimulus. ^{[1] [2]} The feature detectors work in parallel, each performing a specialized function. When faced with a red square, for instance, the parallel line feature detectors, the horizontal line feature detectors, and the red color feature detectors all become activated. This activation is then passed on to other parts of the visual cortex where other neurons compare the information supplied by the feature detectors with images stored in memory. Suddenly, in a flash of recognition, the many neurons fire together, creating the single image of the red square that we experience. ^[3]

The Necker Cube

The Necker cube is an example of how the visual system creates perceptions out of sensations. We do not see a series of lines, but rather a cube. Which cube we see varies depending on the momentary outcome of perceptual processes in the visual cortex. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Some feature detectors are tuned to selectively respond to particularly important objects, for instance, faces, smiles, and other parts of the body. ^{[4] [5]} When researchers disrupted face recognition areas of the cortex using the magnetic pulses of transcranial magnetic stimulation (TMS), people were temporarily unable to recognize faces, and yet they were still able to recognize houses. ^{[6] [7]}

It has been estimated that the human visual system can detect and discriminate among 7 million color variations, ^[1] but these variations are all created by the combinations of the three primary colors: red, green, and blue. The shade of a color, known as hue, is conveyed by the wavelength of the light that enters the eye (we see shorter wavelengths as more blue and longer wavelengths as more red), and we detect brightness from the intensity or height of the wave (bigger or more intense waves are perceived as brighter).

Light waves with shorter frequencies are perceived as more blue than red; light waves with higher intensity are seen as brighter. Adapted from Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Like vision and all the other senses, hearing begins with transduction. Sound waves collected by our ears are converted to neural impulses, which are sent to the brain where they are integrated with past experience and interpreted as the sounds we experience. The human ear is sensitive to a wide range of sounds, ranging from the faint tick of a clock in a nearby room to the roar of a rock band at a nightclub, and we have the ability to detect very small variations in sound. But the ear is particularly sensitive to sounds in the same frequency as the human voice. A mother can pick out her child’s voice from a host of others, and when we pick up the phone we quickly recognize a familiar voice. In a fraction of a second, our auditory system receives the sound waves, transmits them to the auditory cortex, compares them to stored knowledge of other voices, and identifies the identity of the caller.

Sound Waves

Just as the eye detects light waves, the ear detects sound waves. Vibrating objects (such as the human vocal cords or guitar strings) cause air molecules to bump into each other and produce sound waves, which travel from their source as peaks and valleys much like the ripples that expand outward when a stone is tossed into a pond. Unlike light waves, which can travel in a vacuum, sound waves are carried within mediums such as air, water, or metal, and it is the changes in pressure associated with these mediums that the ear detects.

As with light waves, we detect both the wavelength and the amplitude of sound waves. The wavelength of the sound wave (known as frequency) is measured in terms of the number of waves that arrive per second and determines our perception of pitch, the perceived frequency of a sound. Longer sound waves have lower frequency and produce a lower pitch, whereas shorter waves have higher frequency and a higher pitch.

The amplitude, or height of the sound wave, determines how much energy it contains and is perceived as loudness (the degree of sound volume). Larger waves are perceived as louder. Loudness is measured using the unit of relative loudness known as the decibel. Zero decibels represents the absolute threshold for human hearing, below which we cannot hear a sound. Each increase in 10 decibels represents a tenfold increase in the loudness of the sound. This means that 20 decibels is 10 times louder than 10 decibels, and 30 decibels is 100 times louder (10 X 10) than 10 decibels. The sound of a typical conversation (about 60 decibels) is 1,000 times louder than the sound of a faint whisper (30 decibels), whereas the sound of a jackhammer (130 decibels) is 10 billion times louder than the whisper.

Sounds in Everyday Life—Levels of Noise in Decibels (dB)

The human ear can comfortably hear sounds up to 80 decibels. Prolonged exposure to sounds above 80 decibels can cause hearing loss. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

did I get this

More than 31 million Americans suffer from some kind of hearing impairment. ^[1] Conductive hearing loss is caused by physical damage to the ear (such as to the eardrums or ossicles) that reduce the ability of the ear to transfer vibrations from the outer ear to the inner ear. Sensorineural hearing loss, which is caused by damage to the cilia or to the auditory nerve, is less common overall but frequently occurs with age. ^[2] The cilia are extremely fragile, and by the time we are 65 years old, we will have lost 40% of them, particularly those that respond to high-pitched sounds. ^[3]

Prolonged exposure to loud sounds will eventually create sensorineural hearing loss as the cilia are damaged by the noise. People who constantly operate noisy machinery without using appropriate ear protection are at high risk of hearing loss, as are people who listen to loud music on their headphones or who engage in noisy hobbies, such as hunting or motorcycling. Sounds that are 85 decibels or more can cause damage to your hearing, particularly if you are exposed to them repeatedly. Sounds of more than 130 decibels are dangerous even if you are exposed to them infrequently. People who experience tinnitus (a ringing or a buzzing sensation) after being exposed to loud sounds have very likely experienced some damage to their cilia. Taking precautions when being exposed to loud sound is important, as cilia do not grow back.

While conductive hearing loss can often be improved through hearing aids that amplify the sound, they are of little help to sensorineural hearing loss. But if the auditory nerve is still intact, a cochlear implant may be used. A cochlear implant is a device made up of a series of electrodes that are placed inside the cochlea. The device serves to bypass the hair cells by stimulating the auditory nerve cells directly. The latest implants utilize place theory, enabling different spots on the implant to respond to different levels of pitch. The cochlear implant can help children hear who would normally be deaf, and if the device is implanted early enough, these children can frequently learn to speak, often as well as normal children do. ^{[4] [5]}

Although vision and hearing are by far the most important, human sensation is rounded out by four other senses, each of which provides an essential avenue to a better understanding of and response to the world around us. These other senses are touch, taste, smell, and our sense of body position and movement (proprioception).

Smelling

As we breathe in air through our nostrils, we inhale airborne chemical molecules, which are detected by the 10 million to 20 million receptor cells embedded in the olfactory membrane of the upper nasal passage. The olfactory receptor cells are topped with tentacle-like protrusions that contain receptor proteins. When an odor receptor is stimulated, the membrane sends neural messages up the olfactory nerve to the brain.

The Olfactory Membrane

There are more than 1,000 types of odor receptor cells in the olfactory membrane. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

We have approximately 1,000 types of odor receptor cells, ^[5] and it is estimated that we can detect 10,000 different odors. ^[6] The receptors come in many different shapes and respond selectively to different smells. Like a lock and key, different chemical molecules “fit” into different receptor cells, and odors are detected according to their influence on a combination of receptor cells. Just as the 10 digits from 0 to 9 can combine in many different ways to produce an endless array of phone numbers, odor molecules bind to different combinations of receptors, and these combinations are decoded in the olfactory cortex. Women tend to have a more acute sense of smell than men. The sense of smell peaks in early adulthood and then begins a slow decline. By ages 60 to 70, the sense of smell has become sharply diminished.

Age Differences in Smell

The ability to identify common odorants declines markedly between 20 and 70 years of age. From Flat World Knowledge, Introduction to Psychology, v1.0. Adapted from Murphy, C. (1986). Taste and smell in the elderly. In H. L. Meiselman and R. S. Rivlin (Eds.), Clinical Measurement of Taste and Smell (Vol. 1, pp. 343–371). New York: Macmillan.

did I get this

The eyes, ears, nose, tongue, and skin sense the world around us, and in some cases perform preliminary information processing on the incoming data. But by and large, we do not experience sensation—we experience the outcome of perception—the total package that the brain puts together from the pieces it receives through our senses and that the brain creates for us to experience. When we look out the window at a view of the countryside, or when we look at the face of a good friend, we don’t just see a jumble of colors and shapes—we see, instead, an image of a countryside or an image of a friend. ^[1]

Our perception is also influenced by psychological factors such as our belief system and our expectations. For example, every so often, we may hear of people spotting UFO’s in the sky, only to discover later that they were hot air balloons or military air craft. Similarly, some people believe that they have seen images of divinity in unexpected places, such as the 10 year old who saw the Virgin Mary on his grilled cheese sandwich. Our beliefs, expectations, and culture therefore influence how we perceive sensory information.

This meaning-making involves the automatic operation of a variety of essential perceptual processes. One of these is sensory interaction-the working together of different senses to create experience. Sensory interaction is involved when taste, smell, and texture combine to create the flavor we experience in food. It is also involved when we enjoy a movie because of the way the images and the music work together.

Although you might think that we understand speech only through our sense of hearing, it turns out that the visual aspect of speech is also important. One example of sensory interaction is shown in the McGurk effect—an error in perception that occurs when we misperceive sounds because the audio and visual parts of the speech are mismatched.

Other examples of sensory interaction include the experience of nausea that can occur when the sensory information being received from the eyes and the body does not match information from the vestibular system ^[1] and synesthesia—an experience in which one sensation (e.g., hearing a sound) creates experiences in another (e.g., vision). Most people do not experience synesthesia, but those who do link their perceptions in unusual ways, for instance, by experiencing color when they taste a particular food or by hearing sounds when they see certain objects. ^[2]

Another important perceptual process is selective attention—the ability to focus on some sensory inputs while tuning out others. View the videos in the exercise below. You will see how surprisingly little we notice about things happening right in front of our faces. Perhaps the process of selective attention can help you see why the security guards completely missed the fact that the Chaser group’s motorcade was a fake—they focused on some aspects of the situation, such as the color of the cars and the fact that they were there at all, and completely ignored others (the details of the security information).

Selective attention also allows us to focus on a single talker at a party while ignoring other conversations that are occurring around us. ^[1] Without this automatic selective attention, we’d be unable to focus on the single conversation we want to hear. However, selective attention is not complete; we also at the same time monitor what is happening in the channels we are not focusing on. Perhaps you have had the experience of being at a party and talking to someone in one part of the room, when suddenly you hear your name being mentioned by someone in another part of the room. This cocktail party phenomenon shows us that, although selective attention is limiting what we process, we are nevertheless at the same time doing a lot of unconscious monitoring of the world around us—you did not know you were attending to the background sounds of the party, but evidently you were.

One of the major problems in perception is to ensure that we always perceive the same object in the same way, despite the fact that the sensations that it creates on our receptors changes dramatically. The ability to perceive a stimulus as constant despite changes in sensation is known as perceptual constancy. Consider our image of a door as it swings. When it is closed, we see it as rectangular, but when it is open, we see only its edge and it appears as a line. But we never perceive the door as changing shape as it swings—perceptual mechanisms take care of the problem for us by allowing us to see a constant shape.

The figure below illustrates this point. In natural circumstances, it never occurs to us that a door is changing shapes as it opens in front of our eyes. As the figure shows, the shape that hits the retina undergoes a significant transformation, but our perceptual system simply interprets it as a rectangular door that is changing in its orientation to us.

Example of Perceptual Constancy

The visual system also corrects for color constancy. Imagine that you are wearing blue jeans and a bright white t-shirt. When you are outdoors, both colors will be at their brightest, but you will still perceive the white t-shirt as bright and the blue jeans as darker. When you go indoors, the light shining on the clothes will be significantly dimmer, but you will still perceive the t-shirt as bright. This is because we put colors in context and see that, compared to its surroundings, the white t-shirt reflects the most light. ^[1] In the same way, a green leaf on a cloudy day may reflect the same wavelength of light as a brown tree branch does on a sunny day. Nevertheless, we still perceive the leaf as green and the branch as brown.

To see an example of color constancy, look at the picture of the hot air balloon below. If you were looking at it in a natural setting, not thinking about your psychology class, you would simply think of the main colors: green, red, white, and blue. However, our camera allows us to take a picture frozen in time to analyze. What we can easily see is that the four colors are extremely variable. Look at the color patches to the right. They are all taken from the three bands of color-green, white, and blue-in the lower half of the picture. Notice how the actual hues vary considerably, although we would simply perceive them as the same color if we were not concentrating on their variability. Color constancy is produced by your perceptual system, taking sensory input and compensating for changes in lighting.

Example of Color Constancy

Courtesy of Shanta, Hot Air Balloon—Color Constancy, CC-BY-2.0.

A third kind of constancy is size constancy. Our eyes see objects that differ radically in size, but our perceptual system compensates for this. In the classroom scene below, notice the huge difference in actual size of people in the picture as you go from front to back. This is what the retina detects. But your perceptual system compensates for these differences, using the knowledge that all of the people are approximately the same size.

Example of Size Constancy

Courtesy of USDAgov’s photostream, CC-BY-2.0.

Our perceptual system compensates for distance, using depth cues from the space around objects to help it make adjustments. The figure below shows how physical context influences our perceptual system. On the left, the monster in front seems smaller than the one in the back because our perceptual system adjusts the perceived size to take the distance into the tunnel into account. On the right, we remove the tunnel, and the two monsters are easily seen as being identical in size.

Example of Depth Cues

Courtesy of Wikimedia Commons, Optical_illusion3, CC-BY-SA.

Although our perception is very accurate, it is not perfect. Illusions occur when the perceptual processes that normally help us correctly perceive the world around us are fooled by a particular situation so that we see something that does not exist or that is incorrect. We will look at some perceptual illusions in the exercises below to see what we can learn from them.

The moon illusion refers to the fact that the moon is perceived to be about 50% larger when it is near the horizon than when it is seen overhead, despite the fact that both moons are the same size and cast the same size retinal image. The monocular depth cues of position and aerial perspective create the illusion that things that are lower and more hazy are farther away. The skyline of the horizon (trees, clouds, outlines of buildings) also gives a cue that the moon is far away, compared to a moon at its zenith. If we look at a horizon moon through a tube of rolled up paper, taking away the surrounding horizon cues, the moon will immediately appear smaller.

Illusions demonstrate that our perception of the world around us may be influenced by our prior knowledge. But the fact that some illusions exist in some cases does not mean the perceptual system is generally inaccurate—in fact, humans normally become so closely in touch with their environment that the physical body and the particular environment we sense and perceive become embodied—that is, built into and linked with—our cognition, such that the worlds around us become part of our brain. ^[1] The close relationship between people and their environments means that, although illusions can be created in the lab and under some unique situations, they may be less common with active observers in the real world. ^[2]

Here is a great spot to see many more illusions and to learn more about why they occur.

A Google image search will also turn up interesting illusions.

In the early part of the 20th century, Russian physiologist Ivan Pavlov (1849–1936) was studying the digestive system of dogs when he noticed an interesting behavioral phenomenon: The dogs began to salivate when the lab technicians who normally fed them entered the room, even though the dogs had not yet received any food. Pavlov realized that the dogs were salivating because they knew that they were about to be fed; the dogs had begun to associate the arrival of the technicians with the food that soon followed their appearance in the room.

With his team of researchers, Pavlov began studying this process in more detail. He conducted a series of experiments in which, over a number of trials, dogs were exposed to a sound immediately before receiving food. He systematically controlled the onset of the sound and the timing of the delivery of the food, and recorded the amount of the dogs’ salivation. Initially the dogs salivated only when they saw or smelled the food, but after several pairings of the sound and the food, the dogs began to salivate as soon as they heard the sound. The animals had learned to associate the sound with the food that followed.

Pavlov identified a fundamental associative learning process called classical conditioning. Classical conditioning refers to learning that occurs when a neutral stimulus (e.g., a tone) becomes associated with a stimulus (e.g., food) that naturally produces a specific behavior. After the association is learned, the previously neutral stimulus is sufficient to produce the behavior. As you can see in the following figure, psychologists use specific terms to identify the stimuli and the responses in classical conditioning. The unconditioned stimulus (US) is something (such as food) that triggers a natural occurring response, and the unconditioned response (UR) is the naturally occurring response (such as salivation) that follows the unconditioned stimulus. The conditioned stimulus (CS) is a neutral stimulus that, after being repeatedly presented prior to the unconditioned stimulus, evokes a response similar to the response to the unconditioned stimulus. In Pavlov’s experiment, the sound of the tone served as the conditioned stimulus that, after learning, produced the conditioned response (CR), which is the acquired response to the formerly neutral stimulus. Note that the UR and the CR are the same behavior—in this case salivation—but they are given different names because they are produced by different stimuli (the US and the CS, respectively).

Classical Conditioning

Before conditioning, the unconditioned stimulus (US) naturally produces the unconditioned response (UR). Top right: Before conditioning, the neutral stimulus (the whistle) does not produce the salivation response. Bottom left: The unconditioned stimulus (US), in this case the food, is repeatedly presented immediately after the neutral stimulus. Bottom right: After learning, the neutral stimulus (now known as the conditioned stimulus or CS), is sufficient to produce the conditioned responses (CR). From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Conditioning is evolutionarily beneficial because it allows organisms to develop expectations that help them prepare for both good and bad events. Imagine, for instance, that an animal first smells a new food, eats it, and then gets sick. If the animal can learn to associate the smell (CS) with the food (US), then it will quickly learn that the food creates the negative outcome and will not eat it next time.

did I get this

A researcher is testing young children to see if they can learn to associate a red circle with an event that the child enjoys. She sets up an experiment where a toy bear dances. The infants predictably love the toy bear and stare at it when it makes noise and dances. She then trains the child by showing a big red circle on a screen in front of the child and, immediately after that, the bear appears and dances off to the side. The bear is only visible right after the red circle appears and the child must turn his or her head to see the bear.

Teddy bear photo by falcon1961; baby photo by Tammra McCauley, CC-BY-2.0.

After he had demonstrated that learning could occur through association, Pavlov moved on to study the variables that influenced the strength and the persistence of conditioning. In some studies, after the conditioning had taken place, Pavlov presented the sound repeatedly but without presenting the food afterward. As you can see, after the initial acquisition (learning) phase in which the conditioning occurred, when the CS was then presented alone, the behavior rapidly decreased—the dogs salivated less and less to the sound, and eventually the sound did not elicit salivation at all. Extinction is the reduction in responding that occurs when the conditioned stimulus is presented repeatedly without the unconditioned stimulus.

Although at the end of the first extinction period the CS was no longer producing salivation, the effects of conditioning had not entirely disappeared. Pavlov found that, after a pause, sounding the tone again elicited salivation, although to a lesser extent than before extinction took place. The increase in responding to the CS following a pause after extinction is known as spontaneous recovery. When Pavlov again presented the CS alone, the behavior again showed extinction.

Although the behavior has disappeared, extinction is never complete. If conditioning is again attempted, the animal will learn the new associations much faster than it did the first time. Pavlov also experimented with presenting new stimuli that were similar, but not identical to, the original conditioned stimulus. For instance, if the dog had been conditioned to being scratched before the food arrived, the stimulus would be changed to being rubbed rather than scratched. He found that the dogs also salivated upon experiencing the similar stimulus, a process known as generalization. Generalization refers to the tendency to respond to stimuli that resemble the original conditioned stimulus. The ability to generalize has important evolutionary significance. If we eat some red berries and they make us sick, it would be a good idea to think twice before we eat some purple berries. Although the berries are not exactly the same, they nevertheless are similar and may have the same negative properties.

Lewicki ^[1] conducted research that demonstrated the influence of stimulus generalization and how quickly and easily it can happen. In his experiment, high school students first had a brief interaction with a female experimenter who had short hair and glasses. The study was set up so that the students had to ask the experimenter a question, and (according to random assignment) the experimenter responded either in a negative way or a neutral way toward the students. Then the students were told to go into a second room in which two experimenters were present, and to approach either one of them. However, the researchers arranged it so that one of the two experimenters looked a lot like the original experimenter, while the other one did not (she had longer hair and no glasses). The students were significantly more likely to avoid the experimenter who looked like the earlier experimenter when that experimenter had been negative to them than when she had treated them more neutrally. The participants showed stimulus generalization such that the new, similar-looking experimenter created the same negative response in the participants as had the experimenter in the prior session.

The flip side of generalization is discrimination—the tendency to respond differently to stimuli that are similar but not identical. Pavlov’s dogs quickly learned, for example, to salivate when they heard the specific tone that had preceded food, but not upon hearing similar tones that had never been associated with food. Discrimination is also useful—if we do try the purple berries, and if they do not make us sick, we will be able to make the distinction in the future. And we can learn that although the two people in our class, Courtney and Sarah, may look a lot alike, they are nevertheless different people with different personalities.

In some cases, an existing conditioned stimulus can serve as an unconditioned stimulus for a pairing with a new conditioned stimulus—a process known as second-order conditioning. In one of Pavlov’s studies, for instance, he first conditioned the dogs to salivate to a sound, and then repeatedly paired a new CS, a black square, with the sound. Eventually he found that the dogs would salivate at the sight of the black square alone, even though it had never been directly associated with the food. Secondary conditioners in everyday life include our attractions to things that stand for or remind us of something else, such as when we feel good on a Friday because it has become associated with the paycheck that we receive on that day, which itself is a conditioned stimulus for the pleasures that the paycheck buys us.

Scientists associated with the behaviorist school argued that all learning is driven by experience, and that nature plays no role. Classical conditioning, which is based on learning through experience, represents an example of the importance of the environment. But classical conditioning cannot be understood entirely in terms of experience. Nature also plays a part, as our evolutionary history has made us better able to learn some associations than others.

Clinical psychologists make use of classical conditioning to explain the learning of a phobia—a strong and irrational fear of a specific object, activity, or situation. For example, driving a car is a neutral event that would not normally elicit a fear response in most people. But if a person were to experience a panic attack in which he suddenly experienced strong negative emotions while driving, he may learn to associate driving with the panic response. The driving has become the CS that now creates the fear response.

Psychologists have also discovered that people do not develop phobias to just anything. Although people may in some cases develop a driving phobia, they are more likely to develop phobias toward objects (such as snakes, spiders, heights, and open spaces) that have been dangerous to people in the past. In modern life, it is rare for humans to be bitten by spiders or snakes, to fall from trees or buildings, or to be attacked by a predator in an open area. Being injured while riding in a car or being cut by a knife are much more likely. But in our evolutionary past, the potential of being bitten by snakes or spiders, falling out of a tree, or being trapped in an open space were important evolutionary concerns, and therefore humans are still evolutionarily prepared to learn these associations over others. ^{[1] [2]}

Another evolutionarily important type of conditioning is conditioning related to food. In his important research on food conditioning, John Garcia and his colleagues ^{[3] [4]} attempted to condition rats by presenting either a taste, a sight, or a sound as a neutral stimulus before the rats were given drugs (the US) that made them nauseous. Garcia discovered that taste conditioning was extremely powerful—the rat learned to avoid the taste associated with illness, even if the illness occurred several hours later. But conditioning the behavioral response of nausea to a sight or a sound was much more difficult. These results contradicted the idea that conditioning occurs entirely as a result of environmental events, such that it would occur equally for any kind of unconditioned stimulus that followed any kind of conditioned stimulus. Rather, Garcia’s research showed that genetics matters—organisms are evolutionarily prepared to learn some associations more easily than others. You can see that the ability to associate smells with illness is an important survival mechanism, allowing the organism to quickly learn to avoid foods that are poisonous.

Classical conditioning has also been used to help explain the experience of posttraumatic stress disorder (PTSD), as in the case of P. K. Philips described at the beginning of this module. PTSD is a severe anxiety disorder that can develop after exposure to a fearful event, such as the threat of death. ^[5] PTSD occurs when the individual develops a strong association between the situational factors that surrounded the traumatic event (e.g., military uniforms or the sounds or smells of war) and the US (the fearful trauma itself). As a result of the conditioning, being exposed to, or even thinking about the situation in which the trauma occurred (the CS), becomes sufficient to produce the CR of severe anxiety. ^[6]

Posttraumatic Stress Disorder (PTSD): A Case of Classical Conditioning

Posttraumatic stress disorder (PTSD) represents a case of classical conditioning to a severe trauma that does not easily become extinct. In this case the original fear response, experienced during combat, has become conditioned to a loud noise. When the person with PTSD hears a loud noise, he or she experiences a fear response despite being far from the site of the original trauma. From Flat World Knowledge, Introduction to Psychology, v1.0. © Thinkstock.

PTSD develops because the emotions experienced during the event have produced neural activity in the amygdala and created strong conditioned learning. In addition to the strong conditioning that people with PTSD experience, they also show slower extinction in classical conditioning tasks. ^[7] In short, people with PTSD have developed very strong associations with the events surrounding the trauma and are also slow to show extinction to the conditioned stimulus.

learn by doing

Instructions: John Garcia’s experiment, described in the text above, was based on the idea that it is easy to condition some associations, but others are difficult to condition. He injected a rat with a chemical that made the rat nauseous.

Let’s reconstruct Garcia’s experiment, so we’re sure that its implications are clear. Here is our subject, a rat.

Rat photo by asplosh, CC-BY-2.0

Task #1: Conditioning the rat to a light. Does it work?

Answer each question to fill in the boxes. The emoticon faces represent whether the rat is happy or sick. You will have one emoticon face left over.

Now show what happened when Garcia tested to see if conditioning had been successful after only a few of the training trials above. As before, you will have an emoticon face left over. You will only use one of the stimuli, so pick the right one to see if classical conditioning has occurred.

Task #2: Conditioning the rat to a distinctive taste (e.g., salt). Does it work?

Answer the questions to fill in the learning phase of the experiment. What are the conditioned and unconditioned stimuli, and what is the unconditioned response? You will have one of the emoticon faces left over.

Now show what happened when Garcia tested to see if conditioning had been successful after only a few of the training trials above. As before, you will have an emoticon face left over. You will only use one of the stimuli, so pick the right one to see if classical conditioning has occurred.

Task #3: Conditioning the rat to a tone. Does it work?

Answer the questions to put the pictures in the appropriate locations to show the learning phase of the experiment. What are the conditioned and unconditioned stimuli, and what is the unconditioned response? You will have one of the emoticon faces left over.

Now show what happened when Garcia tested to see if conditioning had been successful after only a few of the training trials above. As before, you will have an emoticon face left over. You will only use one of the stimuli, so pick the right one to see if classical conditioning has occurred.

Images in this activity courtesy of qtipd, inky2010, azieser, rgesthuizen (Public Domain), and L. Marie (CC-BY-2.0).

In this module, you learn about a different kind of conditioning called operant conditioning. First, remember how classical conditioning works. In classical conditioning, the individual learns to associate new stimuli with natural, biological responses, such as salivation or fear. The organism does not learn a new behavior but rather learns to perform an existing behavior in the presence of a new signal. For example, remember how Pavlov’s dogs learned to salivate when a bell was rung. This learning occurred because the dog learned to associate a new stimulus (e.g., the bell) with an existing stimulus (e.g., the meat), so now the bell produced the same response (the CR: salivation) originally produced only by the meat.

Operant conditioning, on the other hand, is learning that occurs on the bases of the consequences of behavior and can involve the learning of new behaviors. For operant conditioning, the process starts with doing something—behavior—and then noticing the consequences of that behavior. For example, operant conditioning occurs when a dog rolls over on command because it has been praised for doing so in the past. We go into the details of how this learning happens later in this module, but the important point is that an animal that never rolled over on command can learn this new behavior because it notices that its actions lead to rewards—treats or praise.

In summary, classical conditioning is a process in which an individual learns a new cue for an existing behavior by associating the new cue (the CS) with the existing cue (US). Operant conditioning is the process of learning a new behavior by noticing the consequences of that behavior.

Psychologist Edward L. Thorndike (1874–1949) was the first scientist to systematically study operant conditioning. In his research Thorndike ^[1] observed cats who had been placed in a “puzzle box” from which they tried to escape. At first the cats scratched, bit, and swatted haphazardly, without any idea how to get out. But eventually, and accidentally, they pressed the lever that opened the door and exited to their prize, a scrap of fish. The next time the cat was constrained within the box, it attempted fewer of the ineffective responses before carrying out the successful escape, and after several trials the cat learned to almost immediately make the correct response.

Observing these changes in the cats’ behavior led Thorndike to develop his law of effect, the principle that responses that create a typically pleasant outcome in a particular situation are more likely to occur again in a similar situation, whereas responses that produce a typically unpleasant outcome are less likely to occur again in the situation. ^[2] The essence of the law of effect is that successful responses, because they are pleasurable, are “stamped in” by experience and thus occur more frequently. Unsuccessful responses, which produce unpleasant experiences, are “stamped out” and subsequently occur less frequently.

The influential behavioral psychologist B. F. Skinner (1904–1990) expanded on Thorndike’s ideas to develop a more complete set of principles to explain operant conditioning. Skinner created specially designed environments known as operant chambers (usually called Skinner boxes) to systemically study learning. A Skinner box (operant chamber) is a structure that is big enough to fit a rodent or bird and that contains a bar or key that the organism can press or peck to release food or water. It also contains a device to record the animal’s responses.

The most basic of Skinner’s experiments was quite similar to Thorndike’s research with cats. A rat placed in the chamber reacted as one might expect, scurrying about the box and sniffing and clawing at the floor and walls. Eventually the rat chanced upon a lever, which it pressed to release pellets of food. The next time around, the rat took a little less time to press the lever, and on successive trials, the time it took to press the lever became shorter and shorter. Soon the rat was pressing the lever as fast as it could eat the food that appeared. As predicted by the law of effect, the rat had learned to repeat the action that brought about the food and cease the actions that did not.

Skinner studied, in detail, how animals changed their behavior through reinforcement and punishment, and he developed terms that explained the processes of operant learning as shown in the table below.. Skinner used the term reinforcer to refer to any event that strengthens or increases the likelihood of a behavior and the term punisher to refer to any event that weakens or decreases the likelihood of a behavior. And he used the terms positive and negative to refer to whether a reinforcement was presented or removed, respectively.

Reinforcement, either positive or negative, works by increasing the likelihood of a behavior. Punishment, on the other hand, refers to any event that weakens or reduces the likelihood of a behavior. Positive punishment weakens a response by presenting something unpleasant after the response, whereas negative punishment weakens a response by reducing or removing something pleasant. A child who is yelled at after fighting with a sibling (positive punishment) or who loses out on the opportunity to go to recess after getting a poor grade (negative punishment) is less likely to repeat these behaviors.

Although the distinction between reinforcement (which increases behavior) and punishment (which decreases it) is usually clear, in some cases it is difficult to determine whether a reinforcer is positive or negative. On a hot day a cool breeze could be seen as a positive reinforcer (because it brings in cool air) or a negative reinforcer (because it removes hot air). In other cases, reinforcement can be both positive and negative. One may smoke a cigarette both because it brings pleasure (positive reinforcement) and because it eliminates the craving for nicotine (negative reinforcement).

It is important to note that reinforcement and punishment are not simply opposites. The use of positive reinforcement in changing behavior is almost always more effective than using punishment. This is because positive reinforcement makes the person or animal feel better, helping create a positive relationship with the person providing the reinforcement. Types of positive reinforcement that are effective in everyday life include verbal praise or approval, the awarding of status or prestige, and direct financial payment. Punishment, on the other hand, is more likely to create only temporary changes in behavior because it is based on coercion and typically creates a negative and adversarial relationship with the person providing the reinforcement. When the person who provides the punishment leaves the situation, the unwanted behavior is likely to return.

Perhaps you remember watching a movie or being at a show in which an animal—maybe a dog, a horse, or a dolphin—did some pretty amazing things. The trainer gave a command and the dolphin swam to the bottom of the pool, picked up a ring on its nose, jumped out of the water through a hoop in the air, dived again to the bottom of the pool, picked up another ring, and then took both of the rings to the trainer at the edge of the pool. The animal was trained to do the trick, and the principles of operant conditioning were used to train it. But these complex behaviors are a far cry from the simple stimulus-response relationships that we have considered thus far. How can reinforcement be used to create complex behaviors such as these?

One way to expand the use of operant learning is to modify the schedule on which the reinforcement is applied. To this point we have only discussed a continuous reinforcement schedule, in which the desired response is reinforced every time it occurs; whenever the dog sits, for instance, it gets a biscuit. This type of reinforcement schedule can be depicted as follows.

Continuous Reinforcement Schedule

Continuous reinforcement results in relatively fast learning but also rapid extinction of the desired behavior once the reinforcer disappears. The problem is that because the organism is used to receiving the reinforcement after every behavior, the responder may give up quickly when it doesn’t appear.

Most real-world reinforcers are not continuous; they occur on a partial (or intermittent) reinforcement schedule—a schedule in which the responses are sometimes reinforced, and sometimes not. In comparison to continuous reinforcement, partial reinforcement schedules lead to slower initial learning, but they also lead to greater resistance to extinction. Because the reinforcement does not appear after every behavior, it takes longer for the learner to determine that the reward is no longer coming, and thus extinction is slower.

The four types of partial reinforcement schedules are summarized in the following table.

Partial reinforcement schedules are determined by whether the reinforcement is presented on the basis of the time that elapses between reinforcement (interval) or on the basis of the number of responses that the organism engages in (ratio), and by whether the reinforcement occurs on a regular (fixed) or unpredictable (variable) schedule.

In a fixed-interval schedule, reinforcement occurs for the first response made after a specific amount of time has passed. For instance, on a one-minute fixed-interval schedule the animal receives a reinforcement every minute, assuming it engages in the behavior at least once during the minute.

In a variable-interval schedule, the reinforcers appear on an interval schedule, but the timing is varied around the average interval, making the actual appearance of the reinforcer unpredictable. An example might be checking your e-mail: You are reinforced by receiving messages that come, on average, say every 30 minutes, but the reinforcement occurs only at random times. Interval reinforcement schedules tend to produce slow and steady rates of responding.

In a fixed-ratio schedule, a behavior is reinforced after a specific number of responses. For instance, a rat’s behavior may be reinforced after it has pressed a key 20 times, or a salesperson may receive a bonus after she has sold 10 products. A variable-ratio schedule provides reinforcers after a specific but average number of responses. Winning money from slot machines or on a lottery ticket are examples of reinforcement that occur on a variable-ratio schedule. For instance, a slot machine may be programmed to provide a win every 20 times the user pulls the handle, on average.

Complex behaviors are also created through shaping, the process of guiding an organism’s behavior to the desired outcome through the use of successive approximation to a final desired behavior. Skinner made extensive use of this procedure in his boxes as shown in the video below. For instance, he could train a rat to press a bar two times to receive food, by first providing food when the animal moved near the bar. Then when that behavior had been learned he would begin to provide food only when the rat touched the bar. Further shaping limited the reinforcement to only when the rat pressed the bar, to when it pressed the bar and touched it a second time, and finally, to only when it pressed the bar twice. Although it can take a long time, in this way operant conditioning can create chains of behaviors that are reinforced only when they are completed.

Reinforcing animals if they correctly discriminate between similar stimuli allows scientists to test the animals’ ability to learn, and the discriminations that they can make are sometimes quite remarkable. Pigeons have been trained to distinguish between images of Charlie Brown and the other Peanuts characters, ^[1] and between different styles of music and art. ^{[2] [3]}

Behaviors can also be trained through the use of secondary reinforcers. Whereas a primary reinforcer includes stimuli that are naturally preferred or enjoyed by the organism, such as food, water, and relief from pain, a secondary reinforcer (sometimes called conditioned reinforcer) is a neutral event that has become associated with a primary reinforcer through classical conditioning. An example of a secondary reinforcer would be the whistle given by an animal trainer, which has been associated over time with the primary reinforcer, food. An example of an everyday secondary reinforcer is money. We enjoy having money, not so much for the stimulus itself, but rather for the primary reinforcers (the things that money can buy) with which it is associated.

Ivan Pavlov, John Watson, and B. F. Skinner were scientists who believed that all learning could be explained by the processes of conditioning. To critical features of their ideas about conditioning are useful to keep in mind as you study this section. First, they thought of learning as being the same thing as behavior change. Don’t confuse this with the idea that you figure out some idea first and then change your behavior. Second, they believed that learning (i.e., behavior change) occurs only when the individual directly and personally experiences the impact of some reward or punishment.

In this section, you will encounter some kinds of learning are difficult to explain using the ideas that learning occurs only with behavior change and that personal experience is required for learning. Although classical and operant conditioning play key roles in learning, they constitute only a part of the total picture.

In the preceding module, where you learned about operant conditioning, you read about Edward Thorndike’s work with trial-and-error learning. This kind of learning was described in the video that showed how a cat was able to learn to escape from a puzzle box. Trial-and-error leads to learning, according to Thorndike, because of the law of effect: individuals notice the consequences of their actions. They repeat actions that lead to desirable outcomes and avoid those that lead to undesirable results. Trial-and-error learning is the basis of operant conditioning.

One type of learning that is not determined by classical conditioning (learned associations) or operant conditioning (based on trial-and-error) occurs when we suddenly find the solution to a problem, as if the idea just popped into our head. This type of learning is known as insight, the sudden understanding of a solution to a problem. The German psychologist Wolfgang Köhler ^[1] carefully observed what happened when he presented chimpanzees with a problem that was not easy for them to solve, such as placing food in an area that was too high in the cage to be reached. He found that the chimps first engaged in trial-and-error attempts at solving the problem, but when these failed they seemed to stop and contemplate for a while. Then, after this period of contemplation, they would suddenly seem to know how to solve the problem, for instance by using a stick to knock the food down or by standing on a chair to reach it. Köhler argued that it was this flash of insight, not the prior trial-and-error approaches, which were so important for conditioning theories, that allowed the animals to solve the problem.

Edward Tolman ^[1] was studying traditional trial-and-error learning when he realized that some of his research subjects (rats) actually knew more than their behavior initially indicated. In one of Tolman’s classic experiments, he observed the behavior of three groups of hungry rats that were learning to navigate mazes.

The first group always received a food reward at the end of the maze, so the payoff for learning the maze was real and immediate. The second group never received any food reward, so there was no incentive to learn to navigate the maze effectively. The third group was like the second group for the first 10 days, but on the 11th day, food was now placed at the end of the maze.

As you might expect when considering the principles of conditioning, the rats in the first group quickly learned to negotiate the maze, while the rats of the second group seemed to wander aimlessly through it. The rats in the third group, however, although they wandered aimlessly for the first 10 days, quickly learned to navigate to the end of the maze as soon as they received food on day 11. By the next day, the rats in the third group had caught up in their learning to the rats that had been rewarded from the beginning. It was clear to Tolman that the rats that had been allowed to experience the maze, even without any reinforcement, had nevertheless learned something, and Tolman called this latent learning. Latent learning is to learning that is not reinforced and not demonstrated until there is motivation to do so. Tolman argued that the rats had formed a “cognitive map” of the maze but did not demonstrate this knowledge until they received reinforcement.

In the Learn by Doing exercise below, go through Tolman’s experiment with his three groups of rats. Keep in mind that Tolman, as a good scientist, was testing an idea that was controversial at the time: the idea that we can learn something without our behavior immediately revealing that we have learned it. It is the delay between the learning and the revealing behavior that is the basis for the name: latent (or “hidden”) learning.

learn by doing

Adobe Flash Player is required.

Get Adobe^® Flash^® Player.

Test My System

Your task here is to predict what is going to happen on Trial 12 for the “no food until Trial 11” group.

Option A: Notice that this result is the same as the “no food on any trial” group. So, if you choose option A, you think that they will not act differently now than they acted on the first 11 trials and they will continue to make a lot of wrong turns.

Option B: This option suggests that they are now motivated to learn the path to the food, but that they will do so in small steps, just as we have seen for all three groups up to this point. Option B says that they are moving in the direction of the “food on every trial” group, but that it will take some extra learning to get there.

Option C: This option says that they already know the path to the food and, now that they are motivated to get there, they will show that they already know just as much as the “food on every trial” group. Their performance on Trial 12 will be the same as the low-error performance of the “food on every trial” group.

Tolman’s studies of latent learning show that animals, and people, can learn during unrewarded experience, but this learning only shows itself when rewards or punishment provide motivation to use some knowledge. However, Tolman’s rats at least had the opportunity to wander through the maze, and the rats in the critical condition did this for 10 days before food provided them with motivation to find an efficient path through the maze. So we could still hold onto the theory that learning only takes place if you actually do something, even it it is unrewarded. The direct connection between learning and behavior—even if the behavior seems aimless—has not been disproved. But in the 1960s, Albert Bandura conducted a series of experiments showing that learning can and does occur even when the learner is merely a passive spectator. Learning can occur when someone else is doing all the behaving and receiving all the rewards and punishments.

One of the best known and most influential experiments in the history of psychology involved some adults, some children, and a big inflatable doll called a Bobo doll. Bandura and his colleagues ^[1] allowed children to watch an adult—a man or a woman in different conditions of the study—“playing” with a Bobo doll, an inflatable balloon with a weight in the bottom that makes it pop back up when you knock it down. Bandura wanted to know if watching the adults would influence the way the children behaved.

The motivation for Bandura’s study was not that of solving some abstract scientific question, but a real debate that continues to this day. Many people felt that children who were “raised properly” would not be influenced very strongly by seeing someone—an unfamiliar adult, for instance—behave in a mean or hostile way. The children might be upset by what they saw, but surely they would not imitate poor behavior. As you learned when you studied about Tolman’s rats, many learning specialists believed that learning (i.e., behavior based on experience) only occurs for the individual who is actually doing the behavior. This theory held by the learning specialists supported the belief that the children would not learn by watching, because they would not be doing anything and they would not receive rewards or punishment. Bandura—along with many parents and some other psychologists—suspected that learning might occur merely by watching the actions of others and the consequences of those actions.

Watch the following video as Dr. Bandura explains his study to you.

In the following activity, you will go through one of Bandura’s classic studies.

learn by doing

Phase 1 of the Experiment: The Observation Phase

The observation phase of the experiment is when the children see the behavior of the adults. Each child was shown into a room where an adult was already sitting near the Bobo doll. The child was positioned so he or she could easily see the adult.

Instructions: There are three people involved in the first phase of the experiment: an adult model, a child subject or participant, and an experimenter. Demonstrate your understanding of the first step of the experiment by moving each of the three characters (adult, experimenter, and child) to the correct location in the Experimentation Room depicted below.

Phase 2 of the Experiment: Frustration

Dr. Bandura thought that the children might be a bit more likely to show aggressive behavior if they were frustrated. The second phase of the experiment was designed to produce this frustration. After a child had watched the adult in phase 1, he or she was taken to another room, one that also contained a lot of attractive, fun toys and was told that is was fine to play with the toys. As soon as the child started to enjoy playing with the toys, the experimenter said something.

Phase 3 of the Experiment: The Testing Phase

After the child was told to stop playing with “the very best toys,” the experimenter said that he or she could play with any of the toys in the next room. Then the child was taken to a third room. This room contained a variety of toys. Many of the toys were engaging and interactive, but not the type that encouraged aggressive play. Critically, the Bobo doll and the hammer that the model had used in the first phase were now in this new play room. The goal of this phase in the experiment was to see how the child would react without a model around.

Instructions: The figure below represents the third room. Three individuals from the study are indicated by the boxes below the diagram. Drag each of them to the proper locations to indicate your understanding of the experimental procedure. One of three individuals does not appear in phase 3 of the study, so put this individual in the black box that says, “Not in this phase.”

The child was allowed to play freely for 20 minutes. Note that an adult did stay in the room so the child would not feel abandoned or frightened. However, this adult worked inconspicuously in a corner and interacted with the child as little as possible.

During the 20 minutes that the child played alone in the third room, the experimenters observed his or her behavior from behind a see-through mirror. Using a complex system that we won’t go into here, the experimenters counted the number of various types of behaviors that the child showed during this period. These behaviors included ones directed at the Bobo doll, as well as those involving any of the other toys. They were particularly interested in the number of behaviors the child showed that clearly imitated the actions of the adults that the child had observed earlier, in phase 1.

Below are the results for the number of imitative physically aggressive acts the children showed on average toward the Bobo doll. These acts included hitting and punching the Bobo doll. On the left, you see the two modeling conditions: aggression by the model in phase 1 or no aggression by the model in phase 1. Note: Children in the no-model conditions showed very few physically aggressive acts and their results do not change the interpretation, so we will keep the results simple by leaving them out of the table.

The story is a slightly, though not completely, different when we look at imitative verbal aggression, rather than physical aggression. The table below shows the number of verbally aggressive statements by the boys and girls under different conditions in the experiment. Verbally aggressive statements were ones like the models had made: for example, “Sock him” and “Kick him down!”

Note: Just as was true for the physically aggressive acts, children in the no model conditions showed very few verbally aggressive acts either and their results do not change the interpretation, so we will keep the results simple by leaving them out of the table.

Images in this activity courtesy of Gioppino, klaasvangend, Machovka, Gerald_G, Dug, Machovka (Public Domain); steve greer, Sacheverelle, and Horia Varlan (CC-BY-2.0).

Bandura and his colleagues did other studies in which they had children observe adults on television performing the acts rather than watching them in person. The effects of aggressive modeling were weaker when the adult was not physically present, but the same general pattern of results were found with television models. In yet another variation, Bandura had the children watch cartoon models rather than real adults. These results were even weaker than the television adult model results, but the pattern was still there and the aggressive modeling effect was still statically significant. Children even imitated the aggressive behavior of cartoon characters.

Observational learning is useful for animals and for people because it allows us to learn without having to actually engage in what might be a risky behavior. Monkeys that see other monkeys respond with fear to the sight of a snake learn to fear the snake themselves, even if they have been raised in a laboratory and have never actually seen a snake. ^[2] As Bandura put it, “the prospects for [human] survival would be slim indeed if one could learn only by suffering the consequences of trial and error. For this reason, one does not teach children to swim, adolescents to drive automobiles, and novice medical students to perform surgery by having them discover the appropriate behavior through the consequences of their successes and failures. The more costly and hazardous the possible mistakes, the heavier is the reliance on observational learning from competent learners. ^[3]

Although modeling is normally adaptive, it can be problematic for children who grow up in violent families. These children are not only the victims of aggression, but they also see it happening to their parents and siblings. Because children learn how to be parents in large part by modeling the actions of their own parents, it is no surprise that there is a strong correlation between family violence in childhood and violence as an adult. Children who witness their parents being violent or who are themselves abused are more likely as adults to inflict abuse on intimate partners or their children, and to be victims of intimate violence. ^[4] In turn, their children are more likely to interact violently with each other and to aggress against their parents. ^[5]

The average American child watches more than 4 hours of television every day, and two out of three programs they watch contain aggression. It has been estimated that by the age of 12, the average American child has seen more than 8,000 murders and 100,000 acts of violence. At the same time, children are also exposed to violence in movies, video games, and virtual reality games, as well as in music videos that include violent lyrics and imagery. ^{[1] [2] [3]}

It is clear that watching television violence can increase aggression, but what about violent video games? These games are more popular than ever and also more graphically violent. Youths spend countless hours playing these games, many of which involve engaging in extremely violent behaviors. The games often require the player to take the role of a violent person, to identify with the character, to select victims, and of course to kill the victims. These behaviors are reinforced by winning points and moving on to higher levels, and are repeated over and over.

In one experiment, Bushman and Anderson ^[4] assessed the effects of viewing violent video games on aggressive thoughts and behavior. Participants were randomly assigned to play either a violent or a nonviolent video game for 20 minutes. Each participant played one of four violent video games or one of four nonviolent video games.

Participants then read a story, such as this one about Todd, and were asked to list 20 thoughts, feelings, and actions about how they would respond if they were Todd:

Todd was on his way home from work one evening when he had to brake quickly for a yellow light. The person in the car behind him must have thought Todd was going to run the light because he crashed into the back of Todd’s car, causing a lot of damage to both vehicles. Fortunately, there were no injuries. Todd got out of his car and surveyed the damage. He then walked over to the other car.

It might not surprise you to hear that these exposures to violence have an effect on aggressive behavior. The evidence is impressive and clear: The more media violence people, including children, view, the more aggressive they are likely to be. ^{[5] [6]} The relationship between viewing television violence and aggressive behavior is about as strong as the relation between smoking and cancer or between studying and academic grades. People who watch more violence become more aggressive than those who watch less violence.

As you have just read, playing violent video games also leads to aggressive responses. A recent meta-analysis by Anderson and Bushman ^[7] reviewed 35 research studies that had tested the effects of playing violent video games on aggression. The studies included both experimental and correlational studies, with both male and female participants in both laboratory and field settings. They found that exposure to violent video games is significantly linked to increases in aggressive thoughts, aggressive feelings, psychological arousal (including blood pressure and heart rate), as well as aggressive behavior. Furthermore, playing more video games was found to relate to less altruistic behavior.

For some people, memory is truly amazing. Consider, for instance, the case of Kim Peek, who was the inspiration for the Academy Award–winning film Rain Man.

Kim Peek

Kim Peek, the subject of the movie Rain Man, was believed to have memorized the contents of more than 10,000 books. He could read a book in about an hour. From Flat World Knowledge, Introduction to Psychology, v1.0. Photo courtesy of Darold A. Treffert, MD, and the Wisconsin Medical Society, http://commons.wikimedia.org/wiki/File:Peek1.jpg.

There are others who are capable of amazing feats of memory. The Russian psychologist A. R. Luria ^[1] has described the abilities of a man known as “S,” who seems to have unlimited memory. S remembers strings of hundreds of random letters for years at a time, and seems in fact to never forget anything. As you watch the following video, you’ll notice that at the beginning, Kim is referred to as an idiot savant. Idiot is an old term that was used to describe profound mental retardation. Now we just say “profound mental retardation.” Kim and people like him are called savants.

The subject of this unit is memory. The term memory refers to our capacity to acquire, store, and retrieve the information and habits that guide our behavior. This capacity is largely modulated by associative learning mechanisms like those discussed in the unit on learning. Our memories allow us to do relatively simple things, such as remembering where we parked our car or the name of the current president of the United States. We can also form complex memories, such as how to ride a bicycle or write a computer program. Moreover, our memories define us as individuals—memories are the records of our experiences, our relationships, our successes, and our failures. Perhaps the coolest aspect of memory is that it provides us with the means to use mental time travel to access a lifetime of experiences and learning.

This unit is about human memory, but in our culture we commonly hear the term memory used in conjunction with descriptions of computers. Computer memory and human memory have some distinct differences and some similarities. Let's take a look at some of these.

Differences between Brains and Computers

• In computers, information can be accessed only if one knows the exact location of the memory. In the brain, information can be accessed through spreading activation from closely related concepts.
• The brain operates primarily in parallel, meaning that it is multitasking on many different actions at the same time. Although this is changing as new computers are developed, most computers are primarily serial—they finish one task before they start another.
• In the brain, there is no difference between hardware (the mechanical aspects of the computer) and software (the programs that run on the hardware).
• In the brain, synapses, which operate using an electrochemical process, are much slower but also vastly more complex and useful than the transistors used by computers.
• Computers differentiate memory (e.g., the hard drive) from processing (the central processing unit), but in brains there is no such distinction. In the brain (but not in computers) existing memory is used to interpret and store incoming information, and retrieving information from memory changes the memory itself.
• The brain is self-organizing and self-repairing, but computers are not. If a person suffers a stroke, neural plasticity will help him or her recover. If we drop our laptop and it breaks, it cannot fix itself.
• The brain has significantly more circuitry than any current computer. The brain is estimated to have 25,000,000,000,000,000 (25 million billion) interactions among axons, dendrites, neurons, and neurotransmitters, and that doesn’t include the approximately 1 trillion glial cells that may also be important for information processing and memory.

Although we depend on computers in multiple aspects of our lives, and computers eclipse human processing capacity in terms of speed and volume, at least for some things, human memory is exponentially better than a computer ^[2] . Once we learn a face, we can recognize that face many years later—a task which computers have yet to master. Impressively, our memories can be acquired rapidly and retained indefinitely. Mitchell ^[3] contacted participants 17 years after they had been briefly exposed to some line drawings in a lab and found that they still could identify the images significantly better than participants who had never seen them.

In this unit we learn how psychologists use behavioral responses (such as memory tests and reaction time) to draw inferences about what and how people remember. And we will see that although we have very good memory for some things, our memories are far from perfect. ^[4] The errors we make are due to the fact that our memories are not simply recording devices that input, store, and retrieve the world around us. Rather, we actively process and interpret information as we remember and recollect it, and these cognitive processes influence what we remember and how we remember it. Because memories are constructed, not recorded, when we remember events we don’t reproduce exact replicas of those events. ^[5]

We also learn that our prior knowledge can influence our memory. People who read the words dream, sheets, rest, snore, blanket, tired, and bed and are then asked to remember the words often think they saw the word sleep even though that word was not in the list. ^[6] In other circumstances, we are influenced by the ease with which we can retrieve information from memory or by the information that we are exposed to after we first learn something.

Basic memory research has revealed profound inaccuracies in our memories and judgments. Understanding these potential errors is the first step in learning to account for them in our everyday lives.

Your own experiences taking tests will probably lead you to agree with the scientific research finding that recall is more difficult than recognition. Recall, such as required on essay tests, involves two steps: first generating an answer and then determining whether it seems to be the correct one. Recognition, as on multiple-choice tests, only involves determining which item from a list seems most correct. ^[1] Although they involve different processes, recall and recognition memory measures tend to be correlated. Students who do better on a multiple-choice exam will also, by and large, do better on an essay exam. ^[2]

A third way of measuring memory is known as relearning. ^[3] Measures of relearning (or savings) assess how much more quickly information is processed or learned when it is studied again after it has already been learned but then forgotten. If you have taken some French courses in the past, for instance, you might have forgotten most of the vocabulary you learned. But if you were to work on your French again, you’d learn the vocabulary much faster the second time around. Relearning can be a more sensitive measure of memory than either recall or recognition because it allows assessing memory in terms of “how much” or “how fast” rather than simply “correct” versus “incorrect” responses. Relearning also allows us to measure memory for procedures like driving a car or playing a piano piece, as well as memory for facts and figures.

Types of Memory

From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Research Focus: Priming outside Awareness Influences Behavior

One of the most important characteristics of implicit memories is that they are frequently formed and used automatically, without much effort or awareness on our part. In one demonstration of the automaticity and influence of priming effects, John Bargh and his colleagues ^[4] conducted a study in which they showed college students lists of five scrambled words, each of which they were to make into a sentence. Furthermore, for half of the research participants, the words were related to stereotypes of the elderly. These participants saw words such as the following:

in Florida retired live people

bingo man the forgetful plays

The other half of the research participants also made sentences, but from words that had nothing to do with elderly stereotypes. The purpose of this task was to prime stereotypes of elderly people in memory for some of the participants but not for others.

The experimenters then assessed whether the priming of elderly stereotypes would have any effect on the students’ behavior—and indeed it did. When the research participant had gathered all of his or her belongings, thinking that the experiment was over, the experimenter thanked him or her for participating and gave directions to the closest elevator. Then, without the participants knowing it, the experimenters recorded the amount of time that the participant spent walking from the doorway of the experimental room toward the elevator. As you can see in the figure below, participants who had made sentences using words related to elderly stereotypes took on the behaviors of the elderly—they walked significantly more slowly as they left the experimental room.

Results from Bargh, Chen, and Burrows

Bargh, Chen, and Burrows found that priming words associated with the elderly made people walk more slowly. From Flat World Knowledge, Introduction to Psychology, v1.0. Adapted from Bargh, J. A., Chen, M., and Burrows, L. (1996). Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology, 71, 230–244.

To determine if these priming effects occurred out of the awareness of the participants, Bargh and his colleagues asked still another group of students to complete the priming task and then to indicate whether they thought the words they had used to make the sentences had any relationship to each other, or could possibly have influenced their behavior in any way. These students had no awareness of the possibility that the words might have been related to the elderly or could have influenced their behavior.

did I get this

Although it is useful to hold information in sensory and short-term memory, we also rely on our long-term memory (LTM). Long-term memory is relatively permanent storage. Explicit memories stored there will stay with us throughout our lifetime (barring a brain disease or injury) as long as we continue to use them. Most of us who teach psychology originally learned the material many years ago. But because we continue to use the information, it remains readily available to us. Once we stop using the material we have learned, it will gradually fade. Implicit memories are less subject to fading with disuse, but over time, they will fade too. If you learn to ski as a child, stop in your teens, and then resume it again in your 40s, you will still remember some of what you learned, but you’ll have to practice again to do it well.

We use long-term memory to remember the name of the new boy in the class, the name of the movie we saw last week, and the material for our upcoming psychology test. Psychological research has produced a great deal of knowledge about long-term memory, and this research can be useful as you try to learn and remember new material. In this module we consider this question in terms of the types of processing we do on the information we want to remember. To be successful, the information we want to remember must be encoded and stored and then retrieved. The rest of this module discusses these three concepts.

Encoding is the process by which we place our experiences into memory. Unless information is encoded, it cannot be remembered. I’m sure you’ve been to a party where you were introduced to someone, and then—maybe only seconds later—you realized you did not remember the person’s name. It's not surprising that you forgot the name, because you probably were distracted and never encoded the name to begin with.

Not everything we experience can or should be encoded. We tend to encode things that we need to remember and not bother to encode things that are irrelevant. Look at figure below, which shows different images of U.S. pennies. Can you tell which one is the real one? Nickerson and Adams ^[1] found that very few of the U.S. participants they tested could identify the right one. We see pennies a lot, but we don’t bother to encode their features.

Pennies in Different Styles

Can you identify the “real” penny? We tend to have poor memory for things that don’t matter, even if we see them frequently. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

One way to improve our memory is to use better encoding strategies. Some ways of studying are more effective than others. Research has found that we are better able to remember information if we encode it in a meaningful way. When we engage in elaborative encoding, we process new information in ways that make it more relevant or meaningful. ^{[2] [3]}

Imagine that you are trying to remember the characteristics of the different schools of psychology we discussed in the first unit. Rather than simply trying to remember the schools and their characteristics, you might try to relate the information to things you already know. For instance, you might try to remember the fundamentals of the cognitive school of psychology by linking the characteristics to the computer model. The cognitive school focuses on how information is input, processed, and retrieved, and you might think about how computers do pretty much the same thing. You might also try to organize the information into meaningful units. For instance, you might link the cognitive school to structuralism because both are concerned with mental processes. You also might try to use visual cues to help you remember the information. You might look at the image of Freud and imagine what he looked like as a child. That image might help you remember that childhood experiences were an important part of Freudian theory. Each person has his or her unique way of elaborating on information; the important thing is to try to develop unique and meaningful associations among the materials. These suggestions are very good study hints.

Research Focus: Elaboration and Memory

In an important study showing the effectiveness of elaborative encoding, Rogers, Kuiper, and Kirker ^[4] studied how people recalled information that they had learned under different processing conditions. All the participants were presented with the same list of 40 adjectives to learn, but through the use of random assignment, the participants were given one of four different sets of instructions about how to process the adjectives.

Participants assigned to the structural task condition were asked to judge whether the word was printed in uppercase or lowercase letters. Participants in the phonemic task condition were asked whether or not the word rhymed with another given word. In the semantic task condition, the participants were asked if the word was a synonym of another word. And in the self-reference task condition, participants were asked to indicate whether or not the given adjective was or was not true of themselves. After completing the specified task, each participant was asked to recall as many adjectives as he or she could remember.

Rogers and his colleagues hypothesized that different types of processing would have different effects on memory. As you can see in the following figure, participants in the self-reference task condition recalled significantly more adjectives than did participants in any other condition. This finding, known as the self-reference effect, is powerful evidence that the self-concept helps us organize and remember information. The next time you are studying for an exam, you might try relating the material to your own experiences. The self-reference effect suggests that doing so will help you better remember the information. ^[5]

Self-Reference Effect Results

Participants recalled the same words significantly better when they were processed in relation to the self than when they were processed in other ways. From Flat World Knowledge, Introduction to Psychology, v1.0. Adapted from Rogers, T. B., Kuiper, N. A., and Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology, 35(9), 677–688.

Hermann Ebbinghaus (1850–1909) was a pioneer of the study of memory. In this section we consider three of his most important findings, each of which can help you improve your memory. In his research, in which he was the only research participant, Ebbinghaus practiced memorizing lists of nonsense syllables, such as the following:

DIF, LAJ, LEQ, MUV, WYC, DAL, SEN, KEP, NUD

You can imagine that because the material he was trying to learn was not at all meaningful, it was not easy to do. Ebbinghaus plotted how many of the syllables he could remember against the time that had elapsed since he studied them. He discovered an important principle of memory: Memory decays rapidly at first, but the amount of decay levels off with time (see the Ebbinghaus Forgetting Curve in the following figure). Although Ebbinghaus looked at forgetting after days had elapsed, the same effect occurs on longer and shorter time scales. Bahrick ^[1] found that students who took a Spanish language course forgot about one half of the vocabulary they had learned within 3 years, but after that time, their memory remained pretty much constant. Forgetting also drops off quickly on a shorter time frame, which suggests that you should try to review the material you have already studied right before you take an exam; that way, you will be more likely to remember the material during the exam.

Ebbinghaus Forgetting Curve

Hermann Ebbinghaus found that memory for information drops off rapidly at first but then levels off after time. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Ebbinghaus also discovered another important principle of learning, known as the spacing effect. The spacing effect refers to the fact that learning is better when the same amount of study is spread out over periods of time than it is when it occurs closer together or at the same time. This means that even if you have only a limited amount of time to study, you’ll learn more if you study continually throughout the semester (a little bit every day is best) than if you wait to cram at the last minute before your exam. Another good strategy is to study and then wait as long as you can before you forget the material. Then review the information and again wait as long as you can before you forget it. (This probably will be a longer period of time than the first time.) Repeat and repeat again. The spacing effect is usually considered in terms of the difference between distributed practice (practice that is spread out over time) and massed practice (practice that comes in one block), with the former approach producing better memory.

Effects of Massed versus Distributed Practice on Learning

The spacing effect refers to the fact that memory is better when it is distributed rather than massed. Leslie, Lee Ann, and Nora each studied for 4 hours, but the students who spread out their learning into smaller study sessions did better on the exam. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Ebbinghaus also considered the role of overlearning—that is, continuing to practice and study even when we think that we have mastered the material. Ebbinghaus and other researchers have found that overlearning helps encoding. ^[2] Students frequently think that they have already mastered the material but then discover when they get to the exam that they have not. The point is clear: Try to keep studying and reviewing, even if you think you already know all the material.

Even when information has been adequately encoded and stored, it does not do us any good if we cannot retrieve it. Retrieval is the process of reactivating information that has been stored in memory.

We’ve all experienced retrieval failure in the form of the frustrating tip-of-the-tongue phenomenon in which we are certain that we know something that we are trying to recall but cannot quite come up with it. You can try this one on your friends as well. Read your friend the names of the 10 states listed below, and ask him or her to name the capital city of each state. Now, for the capital cities that your friend can’t name, provide just the first letter of the capital city. You’ll probably find that having the first letters of the cities helps with retrieval. The tip-of-the-tongue experience is a very good example of the inability to retrieve information that is actually stored in memory.

Try this demonstration of the tip-of-the-tongue phenomenon with a classmate. Follow the instructions from the paragraph above.

We are more likely to be able to retrieve items from memory when conditions at retrieval are similar to the conditions under which we encoded them. Context-dependent learning refers to an increase in retrieval when the external situation in which information is learned matches the situation in which it is remembered. Godden and Baddeley ^[1] conducted a study to test this idea using scuba divers. They asked the divers to learn a list of words either when they were on land or when they were underwater. Then they tested the divers on their memory, either in the same or the opposite situation. As you can see in the following figure, the divers’ memory was better when they were tested in the same context in which they had learned the words than when they were tested in the other context.

Results from Godden and Baddeley

Godden and Baddeley tested the memory of scuba divers for learning and retrieving information in different contexts and found strong evidence for context-dependent learning. From Flat World Knowledge, Introduction to Psychology, v1.0. Adapted from Godden, D. R., and Baddeley, A. D. (1975). Context-dependent memory in two natural environments: On land and underwater. British Journal of Psychology, 66(3), 325–331.

You can see that context-dependent learning might also be important in improving your memory. For instance, you might want to try to study for an exam in a situation that is similar to the one in which you are going to take the exam.

Whereas context-dependent learning refers to a match in the external situation between learning and remembering, state-dependent learning refers to superior retrieval of memories when the individual is in the same physiological or psychological state as during encoding. Research has found, for instance, that animals that learn a maze while under the influence of one drug tend to remember their learning better when they are tested under the influence of the same drug than when they are tested without the drug. ^[2] And research with humans finds that bilinguals remember better when tested in the same language in which they learned the material. ^[3] Mood states may also produce state-dependent learning. People who learn information when they are in a bad (rather than a good) mood find it easier to recall these memories when they are tested while they are in a bad mood, and vice versa. It is easier to recall unpleasant memories than pleasant ones when we’re sad, and easier to recall pleasant memories than unpleasant ones when we’re happy. ^{[4] [5]}

Variations in the ability to retrieve information are also seen in the serial position curve. When we give people a list of words one at a time (e.g., on flashcards) and then ask them to recall them, the results look something like those in the figure below. People are able to retrieve more words that were presented to them at the beginning and the end of the list than they are words that were presented in the middle of the list. This pattern, known as the serial position curve, is caused by two retrieval phenomenon: The primacy effect is a tendency to better remember stimuli that are presented early in a list. The recency effect is the tendency to better remember stimuli that are presented later in a list.

The Serial Position Curve

The serial position curve is the result of both primacy effects and recency effects. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

There are a number of explanations for primacy and recency effects; one has to do with the effects of rehearsal on short-term and long-term memory. ^[6] Because we can keep the last words we learned in the presented list in short-term memory by rehearsing them before the memory test begins, they are relatively easily remembered. The recency effect therefore can be explained in terms of maintenance rehearsal in short-term memory. And the primacy effect may also be due to rehearsal—when we hear the first word in the list, we start to rehearse it, making it more likely that it will be moved from short-term to long-term memory. The same is true for the other words that come early in the list. But for the words in the middle of the list, this rehearsal becomes much harder, making them less likely to be moved to long-term memory.

In some cases our existing memories influence our new learning. This may occur either in a backward way or a forward way. Retroactive interference occurs when learning something new impairs our ability to retrieve information that was learned earlier. For example, if you have learned to program in one computer language, and then you learn to program in another similar one, you may start to make mistakes programming the first language that you never would have made before you learned the new one. In this case the new memories work backward (retroactively) to influence retrieval from memory that is already in place.

In contrast to retroactive interference, proactive interference works in a forward direction. Proactive interference occurs when earlier learning impairs our ability to encode information that we try to learn later. For example, if you learned French as a second language, this knowledge may make it more difficult, at least in some respects, to learn a third language (say Spanish), which involves similar but not identical vocabulary.

Memories stored in long-term memory are not isolated but rather are linked into categories—networks of associated memories that have features in common with each other. Forming categories and using them to guide behavior is a fundamental part of human nature. Associated concepts within a category are connected through spreading activation, which occurs when activating one element of a category activates other associated elements. For instance, because tools are associated in a category, reminding people of the word screwdriver will help them remember the word wrench. And when people learn lists of words that come from different categories (e.g., as in retrieval exercise on the previous page), they do not recall the information haphazardly. If they remember the word wrench, they are more likely to remember the word screwdriver next than they are to remember the word dahlia because the words are organized in memory by category and because screwdriver is activated by spreading activation from wrench. ^[1]

Some categories have defining features that must be true of all members of the category. For instance, all members of the category “triangles” have three sides, and all members of the category “birds” lay eggs. But most categories are not so well defined; the members of the category share some common features, but it is impossible to define which are or are not members of the category. For instance, there is no clear definition of the category “tool.” Some examples of the category, such as a hammer and a wrench, are clearly and easily identified as category members, whereas other members are not so obvious. Is an ironing board a tool? What about a car?

Members of categories (even those with defining features) can be compared to the category prototype, which is the member of the category that is most average or typical of the category. Some category members are more prototypical of, or similar to, the category than others. For instance, some category members (robins and sparrows) are highly prototypical of the category “birds,” whereas other category members (penguins and ostriches) are less prototypical. We retrieve information that is prototypical of a category faster than we retrieve information that is less prototypical. ^[2]

Prototypicality

Category members vary in terms of their prototypicality. Some cats are “better” members of the category than are others. From Flat World Knowledge, Introduction to Psychology, v1.0. © Thinkstock.

Mental categories are sometimes referred to as schemas—patterns of knowledge in long-term memory that help us organize information. We have schemas about objects (that a triangle has three sides and may take on different angles), about people (that Sam is friendly, likes to golf, and always wears sandals), about events (the particular steps involved in ordering a meal at a restaurant), and about social groups (we call these group schemas stereotypes).

Different Schemas

Our schemas about people, couples, and events help us organize and remember information. From Flat World Knowledge, Introduction to Psychology, v1.0. © Thinkstock.

Schemas are important in part because they help us remember new information by providing an organizational structure for it. Read the following paragraph ^[3] and then try to write down everything you can remember.

It turns out that people’s memory for this information is quite poor unless they are told before they read it that the information describes doing laundry, in which case their memory for the material is much better. This demonstration of the role of schemas in memory shows how our existing knowledge can help us organize new information and how this organization can improve encoding, storage, and retrieval.

Just as information is stored on digital media such as DVDs and flash drives, the information in LTM must be stored in the brain. How do different encoding and retrieval strategies affect our brains at the neural level? We saw from previous sections on elaborative encoding, categories and schemas that we give LTM a unique internal organization. Does that mean that there must be a “memory center” of the brain where all memories are organized for quick retrieval? Additionally, how do diseases such as Alzheimer’s disease and conditions such as amnesia cause us to forget information we have already stored in the brain? To answer these questions, we must think of the brain at two different levels: at the level of neurons and at the level of brain areas.

The ability to maintain information in LTM involves a gradual strengthening of the connections among the neurons in the brain. When pathways in these neural networks are frequently and repeatedly fired, the synapses become more efficient in communicating with each other, and these changes create memory. This process, known as long-term potentiation (LTP), refers to the strengthening of the synaptic connections between neurons as result of frequent stimulation. ^[1] Drugs that block LTP reduce learning, whereas drugs that enhance LTP increase learning. ^[2] Because the new patterns of activation in the synapses take time to develop, LTP happens gradually. The period of time in which LTP occurs and in which memories are stored is known as the period of consolidation. Consolidation of memories formed during the day often happens during sleep, and some theorize that this is one important function of sleep.

Long-term potentiation occurs as a result of changes in the synapses, which suggests that chemicals, particularly neurotransmitters and hormones, must be involved in memory. There is quite a bit of evidence that this is true. Glutamate, a neurotransmitter and a form of the amino acid glutamic acid, is perhaps the most important neurotransmitter in memory. ^[3] When animals, including people, are under stress, more glutamate is secreted, and this glutamate can help them remember. ^[4] The neurotransmitter serotonin is also secreted when animals learn, and epinephrine may also increase memory, particularly for stressful events. ^{[5] [6]} Estrogen, a female sex hormone, also seems critical, because women who are experiencing menopause, along with a reduction in estrogen, frequently report memory difficulties. ^[7] These changes occur through practice. Rehearsal is important in learning. Each time we rehearse, the pathway is activated and each activation strengthens the connections along that pathway.

Our knowledge of the role of biology in memory suggests that it might be possible to use drugs to improve our memories, and Americans spend several hundred million dollars per year on memory supplements with the hope of doing just that. Yet controlled studies comparing memory enhancers, including Ritalin, methylphenidate, ginkgo biloba, and amphetamines, with placebo drugs find very little evidence for their effectiveness. ^{[8] [9]} Memory supplements are usually no more effective than drinking a sugared soft drink, which also releases glucose and thus improves memory slightly.

The following video demonstrates a metaphor for how long-term potentiation creates strong, easily accessible memories. Please answer the following questions about long-term potentiation based on the video and the reading.

Memory occurs through sophisticated interactions between new and old brain structures shown the following figure. One of the most important brain regions in explicit memory is the hippocampus, which serves as a preprocessor and elaborator of information. ^[10] The hippocampus helps us encode information about spatial relationships, the context in which events were experienced, and the associations among memories. ^[11] The hippocampus also serves in part as a switching point that holds the memory for a short time and then directs the information to other parts of the brain, such as the cortex, to actually do the rehearsing, elaboration, and long-term storage. ^[12] Without the hippocampus, which might be described as the brain’s “librarian,” our explicit memories would be inefficient and disorganized. Even so, the older we get, the more susceptible we are to proactive and retroactive interference, which shows that the “librarian” finds it harder to retrieve the right memory from a pile of similar memories as we age. In people with Alzheimer’s disease, a neurodegenerative disease which is most common in the elderly, the hippocampus is severely atrophied. Unsurprisingly, one of the most common symptoms of this disease is the inability to form new memories, followed by a loss of the most recent memories and, finally, the loss of old memories.

Schematic Image of Brain with Hippocampus, Amygdala, and Cerebellum Highlighted

Different brain structures help us remember different types of information. The hippocampus is particularly important in explicit memories, the cerebellum is particularly important in implicit memories, and the amygdala is particularly important in emotional memories. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

While the hippocampus is handling explicit memory, the cerebellum and the amygdala are concentrating on implicit and emotional memories, respectively. Research shows that the cerebellum is more active when we are learning associations and in priming tasks, and animals and humans with damage to the cerebellum have more difficulty in classical conditioning studies. ^{[13] [14]} The cerebellum is also highly involved in the learning of procedural tasks which need fine motor control, such as writing, riding a bike, and sewing. The storage of many of our most important emotional memories, and particularly those related to fear, is initiated and controlled by the amygdala. ^[15] If both amygdalae are damaged, people do not lose their memories of positive or negative emotional associations, but they lose the ability to create new positive or negative associations with objects and events.

Although some brain structures are particularly important in memory, this does not mean that all memories are stored in one place. The American psychologist Karl Lashley ^[16] attempted to determine where memories were stored in the brain by teaching rats how to run mazes, and then lesioning different brain structures to see if they were still able to complete the maze. This idea seemed straightforward, and Lashley expected to find that memory was stored in certain parts of the brain. But he discovered that no matter where he removed brain tissue, the rats retained at least some memory of the maze, leading him to conclude that memory isn’t located in a single place in the brain, but rather is distributed around it.

Our memories are not perfect. They fail in part due to our inadequate encoding and storage, and in part due to our inability to accurately retrieve stored information. But memory is also influenced by the setting in which it occurs, by the events that occur to us after we have experienced an event, and by the cognitive processes that we use to help us remember. Although our cognition allows us to attend to, rehearse, and organize information, cognition may also lead to distortions and errors in our judgments and our behaviors.

In this section we consider some of the cognitive biases that are known to influence humans. Cognitive biases are errors in memory or judgment that are caused by the inappropriate use of cognitive processes. The study of cognitive biases is important both because it relates to the important psychological theme of accuracy versus inaccuracy in perception, and because being aware of the types of errors that we may make can help us avoid them and therefore improve our decision-making skills.

Misinformation Effects

A particular problem for eyewitnesses such as Jennifer Thompson, who misidentified her rapist in court resulting in his wrongful conviction, is that our memories are often influenced by the things that occur to us after we have learned the information. ^{[1] [2] [3]} This new information can distort our original memories such that we are no longer sure what is the real information and what was provided later. The misinformation effect refers to errors in memory that occur when new information influences existing memories.

In an experiment by Loftus and Palmer, ^[4] participants viewed a film of a traffic accident and then, according to random assignment to experimental conditions, answered one of three questions:

• About how fast were the cars going when they hit each other?
• About how fast were the cars going when they smashed each other?
• About how fast were the cars going when they contacted each other?

As you can see in the figure below, although all the participants saw the same accident, their estimates of the cars’ speed varied by condition. Participants who had been asked about the cars “smashing” each other estimated the highest average speed, and those who had been asked the “contacted” question estimated the lowest average speed.

Misinformation Effect

Participants viewed a film of a traffic accident and then answered a question about the accident. According to random assignment, the verb in the question was filled by either “hit,” “smashed,” or “contacted” each other. The wording of the question influenced the participants’ memory of the accident. From Flat World Knowledge, Introduction to Psychology, v1.0. Adapted from Loftus, E. F., and Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13(5), 585–589.

In addition to distorting our memories for events that have actually occurred, misinformation may lead us to falsely remember information that never occurred. Loftus and her colleagues asked parents to provide them with descriptions of events that did (e.g., moving to a new house) and did not (e.g., being lost in a shopping mall) happen to their children. Then (without telling the children which events were real or made-up) the researchers asked the children to imagine both types of events. The children were instructed to “think real hard” about whether the events had occurred. ^[5] More than half of the children generated stories regarding at least one of the made-up events, and they remained insistent that the events did in fact occur even when told by the researcher that they could not possibly have occurred. ^[6] Even college students are susceptible to manipulations that make events that did not actually occur seem as if they did. ^[7]

The ease with which memories can be created or implanted is particularly problematic when the events to be recalled have important consequences. Therapists often argue that patients may repress memories of traumatic events they experienced as children, such as childhood sexual abuse, and then recover the events years later as the therapist leads them to recall the information—for instance, by using dream interpretation and hypnosis. ^[8]

But other researchers argue that painful memories such as sexual abuse are usually very well remembered, that few memories are actually repressed, and that even if they are, it is virtually impossible for patients to accurately retrieve them years later. ^{[9] [10]} These researchers have argued that the procedures used by the therapists to “retrieve” the memories are more likely to actually implant false memories, leading the patients to erroneously recall events that did not actually occur. Because hundreds of people have been accused, and even imprisoned, on the basis of claims about “recovered memory” of child sexual abuse, the accuracy of these memories has important societal implications. Many psychologists now believe that most of these claims of recovered memories are due to implanted, rather than real, memories. ^[11]

learn by doing

Using the representativeness heuristic may lead us to incorrectly believe that some patterns of observed events are more likely to have occurred than others. In this case, list B seems more random, and thus is judged as more likely to have occurred, but statistically both lists are equally likely.

Most people think that list B is more likely, probably because list B looks more random, and thus matches (is “representative of”) our ideas about randomness. But statisticians know that any pattern of four girls and four boys is mathematically equally likely. The problem is that we have a schema of what randomness should be like, which doesn’t always match what is mathematically the case. Similarly, people who see a flipped coin come up “heads” five times in a row will frequently predict, and perhaps even wager money, that “tails” will be next. This behavior is known as the gambler’s fallacy. But mathematically, the gambler’s fallacy is an error: The likelihood of any single coin flip being “tails” is always 50%, regardless of how many times it has come up “heads” in the past. Probability, the likelihood of something happening, is calculated solely by dividing the total number of potential favorable outcomes by the total number of possible outcomes (in our case ½ for both heads and tails). The previous history of events does not affect future events. Another illustration of the gambler’s fallacy is the deceptive phenomenon of streaky basketball shooters.

Our judgments can also be influenced by how easy it is to retrieve a memory.The tendency to make judgments of the frequency or likelihood that an event occurs on the basis of the ease with which it can be retrieved from memory is known as the availability heuristic. ^{[1] [2]} Imagine, for instance, that I asked you to indicate whether there are more words in the English language that begin with the letter “R” or that have the letter “R” as the third letter. You would probably answer this question by trying to think of words that have each of the characteristics, thinking of all the words you know that begin with “R” and all that have “R” in the third position. Because it is much easier to retrieve words by their first letter than by their third, we may incorrectly guess that there are more words that begin with “R,” even though there are in fact more words that have “R” as the third letter.

The availability heuristic may also operate on episodic memory. We may think that our friends are nice people, because we see and remember them primarily when they are around us (their friends, who they are, of course, nice to). And the traffic might seem worse in our own neighborhood than we think it is in other places, in part because nearby traffic jams are more easily retrieved than are traffic jams that occur somewhere else.

Counterfactual Thinking

In addition to influencing our judgments about ourselves and others, the ease with which we can retrieve potential experiences from memory can have an important effect on our own emotions. If we can easily imagine an outcome that is better than what actually happened, then we may experience sadness and disappointment; on the other hand, if we can easily imagine that a result might have been worse than what actually happened, we may be more likely to experience happiness and satisfaction. The tendency to think about and experience events according to “what might have been” is known as counterfactual thinking. ^{[3] [4]}

Imagine, for instance, that you were participating in an important contest, and you won the silver (second-place) medal. How would you feel? Certainly you would be happy that you won the silver medal, but wouldn’t you also be thinking about what might have happened if you had been just a little bit better—you might have won the gold medal! On the other hand, how might you feel if you won the bronze (third-place) medal? If you were thinking about the counterfactuals (the “what might have beens”) perhaps the idea of not getting any medal at all would have been highly accessible; you’d be happy that you got the medal that you did get, rather than coming in fourth.

Counterfactual Thinking

The person on the left is the bronze medalist and the one on the right is the silver. Notice the different smiles. Photo by Duncan Rawlinson, CC-BY-2.0.

Tom Gilovich and his colleagues investigated this idea by videotaping the responses of athletes who won medals in the 1992 Summer Olympic Games. ^[5] They videotaped the athletes both as they learned that they had won a silver or a bronze medal and again as they were awarded the medal. Then the researchers showed these videos, without any sound, to raters who did not know which medal which athlete had won. The raters were asked to indicate how they thought the athlete was feeling, using a range of feelings from “agony” to “ecstasy.” The results showed that the bronze medalists were, on average, rated as happier than were the silver medalists. In a follow-up study, raters watched interviews with many of these same athletes as they talked about their performance. The raters indicated what we would expect on the basis of counterfactual thinking—the silver medalists talked about their disappointments in having finished second rather than first, whereas the bronze medalists focused on how happy they were to have finished third rather than fourth.

You might have experienced counterfactual thinking in other situations. Once I was driving across country, and my car was having some engine trouble. I really wanted to make it home when I got near the end of my journey; I would have been extremely disappointed if the car broke down only a few miles from my home. Perhaps you have noticed that once you get close to finishing something, you feel like you really need to get it done. Counterfactual thinking has even been observed in juries. Jurors who were asked to award monetary damages to others who had been in an accident offered them substantially more in compensation if they barely avoided injury than they offered if the accident seemed inevitable. ^[6]

did I get this

Anyone who has tried to master a second language as an adult knows the difficulty of language learning. And yet children learn languages easily and naturally. Children who are not exposed to language early in their lives will likely never learn one. Documented case studies of such children include Victor the “Wild Child,” who was abandoned as a baby in France and not discovered until he was 12, and Genie, a child whose parents kept her locked in a closet from 18 months until 13 years of age. Both of these children made some progress in socialization after they were rescued and even learned many words and simple phrases, but neither of them ever developed language even to the level of a typical 3-year-old. ^[1]

The cases of Victor and Genie illustrate the importance of early experience of language with people, usually adults, who are fluent in the language. There is one group of children who are in danger of isolation even though they are born to completely normal and loving families: congenitally deaf children or children who lose their hearing very early in life. The parents of these children are seldom deaf themselves and often have no warning that their newborn will be deaf. These parents are seldom fluent or even novices in sign language, a language that, like any other language, takes years of practice to achieve competency. Deaf children who are not exposed to sign language during their early years are likely to have difficulty mastering it when they are older. ^[2] Deaf children have a much better chance of later acquiring other languages, even spoken languages, if they have early exposure to fluent signing.

Deaf children and children like Victor and Genie have shown us that language is a complex ability that is most likely to mature in a normal way if the child is raised in an environment rich in language experiences. There is probably a “sensitive period,” usually associated with the period of childhood, when exposure to language must occur for the brain systems associated with language to develop properly. If exposure does not occur until later, as happened to Genie and Victor and as once regularly happened to deaf children in isolated communities, then the ability to acquire true language abilities may be extremely difficult or even impossible. The brain may lose its ability to form the necessary neural networks to permit language to develop.

For most people, language processing is dominated by the left hemisphere, but many people have a reversal of this pattern, so the right hemisphere dominates language. For instance, a study that looked at the relationship between handedness and the dominant hemisphere for language found that only 4% of people who are strongly right handed have right hemisphere dominance for language, while 15% of ambidextrous individuals and 27% of strong left handers had right hemisphere dominance for language. ^[3]

These differences in hemispheric dominance can easily be seen in the results of neuroimaging studies that show that listening to and producing language creates greater activity in the left hemisphere than in the right. As shown in the following figure, the Broca area, an area in front of the left hemisphere near the motor cortex, is responsible for language production. This area was first localized in the 1860s by the French physician Paul Broca, who studied patients with lesions to various parts of the brain. The Wernicke area, an area of the brain next to the auditory cortex, is responsible for language comprehension.

Drawing of Brain Showing the Broca and Wernicke Areas

For most people, the left hemisphere is specialized for language. The Broca area, near the motor cortex, is involved in language production, whereas the Wernicke area, near the auditory cortex, is specialized for language comprehension. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

Evidence for the importance of the Broca and Wernicke areas in language is seen in patients who experience aphasia, a condition in which language functions are severely impaired. People with Broca aphasia have difficulty producing speech. They speak haltingly, using the minimum number of words to convey an idea. Frequently, they struggle to say a word even though they know the word they are looking for. Other times, they appear to search for a word but fail to find it. People with damage to Wernicke area can produce speech, but what they say is often confusing, and they have trouble understanding what other people are saying to them. Wernicke aphasia is sometimes called fluent aphasia because the person appears to speak in a relatively normal, fluent way, but the content of the sentences may be imprecise or even nonsensical. People with both types of aphasia have difficulty understanding what other people say to them, but this problem tends to be deeper and more serious in cases of Wernicke aphasia. People with Broca aphasia may have comprehension problems because they have difficulty understanding a particular word here and there, but people with Wernicke aphasia have trouble making sense of the meaning of entire sentences and also may have trouble keeping track of the point of the conversation.

Psychological theories of language learning differ in terms of the importance they place on nature versus nurture. Yet it is clear that both matter. Children are not born knowing language; they learn to speak by hearing what happens around them. On the other hand, human brains, unlike those of any other animal, are prewired in a way that leads them, almost effortlessly, to learn language.

Perhaps the most straightforward explanation of language development is that it occurs through principles of learning, including association, reinforcement, and the observation of others. ^[1] There must be at least some truth to the idea that language is learned, because children learn the language that they hear spoken around them rather than some other language. Also supporting this idea is the gradual improvement of language skills with time. It seems that children modify their language through imitation, reinforcement, and shaping, as would be predicted by learning theories.

But language cannot be entirely learned. For one, children learn words too fast for them to be learned through reinforcement. Between the ages of 18 months and 5 years, children learn up to 10 new words every day. ^[2] More important, language is more generative than it is imitative. Generativity refers to the ability of speakers to compose sentences to represent new ideas they have never before been exposed to. Language is not a predefined set of ideas and sentences that we choose when we need them, but rather a system of rules and procedures that allows us to create an infinite number of statements, thoughts, and ideas, including those that have never previously occurred. When a child says that she “swimmed” in the pool, for instance, she is showing generativity. An adult speaker of English would not say “swimmed,” yet the word is easily generated from the normal system of producing language.

Other evidence that refutes the idea that all language is learned through experience comes from the observation that children may learn languages better than they ever hear them. Deaf children whose parents do not speak American Sign Language very well nevertheless can learn it perfectly on their own and may even make up their own language if they need to. ^[3] A group of deaf children in a school in Nicaragua, whose teachers could not sign, invented a way to communicate through made-up signs and through signs different individuals had used to communicate with their own families. ^[4] Within a few years, this made-up signing system became increasingly rule governed and consistent. The development of this new Nicaraguan Sign Language has continued and changed as new generations of students have come to the school and started using the language. Although the original system was not a real language, linguists now find that the signing system invented by these children has all the typical features and complexity of a real language.

In the middle of the 20th century, American linguist Noam Chomsky explained how some aspects of language could be innate. Prior to this time, people tended to believe that children learn language soley by imitating the adults around them. Chomsky agreed that individual words must be learned by experience, but he argued that genes could code into the brain categories and organization that form the basis of grammatical structure. We come into the world ready to distinguish different grammatical classes, like nouns and verbs and adjectives, and sensitive to the order in which words are spoken. Then, using this innate sensitivity, we quickly learn from listening to our parents about how to organize our own language ^{[5] [6]} For instance, if we grow up hearing Spanish, we learn that adjectives come after nouns (el gato amarillo, where gato means “cat” and amarillo is “yellow”), but if we grow up hearing English, we learn that adjectives come first (“the yellow cat”). Chomsky termed this innate sensitivity that allows infants and young children to organize the abstract categories of language the language acquisition device (LAD).

According to Chomsky’s approach, each of the many languages spoken around the world (there are between 6,000 and 8,000) is an individual example of the same underlying set of procedures that are hardwired into human brains. Each language, while unique, is just a set of variations on a small set of possible rule systems that the brain permits language to use. Chomsky’s account proposes that children are born with a knowledge of general rules of grammar (including phoneme, morpheme, and syntactical rules) that determine how sentences are constructed.

Although there is general agreement among psychologists that babies are genetically programmed to learn language, there is still debate about Chomsky’s idea that a universal grammar can account for all language learning. Evans and Levinson ^[7] surveyed the world’s languages and found that none of the presumed underlying features of the language acquisition device were entirely universal. In their search they found languages that did not have noun or verb phrases, that did not have tenses (e.g., past, present, future), and some that did not have nouns or verbs at all, even though a basic assumption of a universal grammar is that all languages should share these features. Other psychologists believe that early experience can fully explain language acquisition, and Chomsky’s language acquisition device is unnecessary. Nevertheless, Chomsky’s work clearly laid out the many problems that had to be solved in order to adequately explain how children acquire language and why languages have the structures that they do.

Although it is less common in the United States than in other countries, bilingualism (the ability to speak two languages) is becoming increasingly frequent in the modern world. Nearly one-half of the world’s population, including 18% of U.S. citizens, grows up bilingual.

In recent years, many U.S. states have passed laws outlawing bilingual education in schools. These laws are in part based on the idea that students will have a stronger identity with the school, the culture, and the government if they speak only English and in part based on the idea that speaking two languages may interfere with cognitive development.

Some early psychological research showed that, when compared with monolingual children, bilingual children performed more slowly when processing language, and their verbal scores were lower. But these tests were frequently given in English, even when this was not the child’s first language, and the children tested were often of lower socioeconomic status than the monolingual children. ^[1]

More current research controlled for these factors and found that although bilingual children may in some cases learn language somewhat more slowly than do monolingual children ^[2] , bilingual and monolingual children do not significantly differ in the final depth of language learning, nor do they generally confuse the two languages. ^[3] In fact, participants who speak two languages have been found to have better cognitive functioning, cognitive flexibility, and analytic skills in comparison to monolinguals. ^[4] Thus, rather than slowing language development, learning a second language seems to increase cognitive abilities.

Nonhuman animals have a wide variety of systems of communication. Some species communicate using scents; others use visual displays, such as baring the teeth, puffing up the fur, or flapping the wings; and still others use vocal sounds. Male songbirds, such as canaries and finches, sing songs to attract mates and to protect territory, and chimpanzees use a combination of facial expressions, sounds, and actions, such as slapping the ground, to convey aggression. ^[1] Honeybees use a “waggle dance” to direct other bees to the location of food sources. ^[2] The language of vervet monkeys is relatively advanced in the sense that they use specific sounds to communicate specific meanings. Vervets make different calls to signify that they have seen either a leopard, a snake, or a hawk. ^[3]

As mentioned earlier, despite the variety and sophistication of animal communication systems, none comes close to human language in its ability to express a variety of ideas and subtle differences in meaning. For years, scientists have wondered if it is the communication systems that are limited or if other animals are simply unable to acquire a system as advanced as human language. Quite a few efforts have been made to learn more by attempting to teach human language to other animals, especially to chimpanzees and their cousins, bonobos.

Despite their wide abilities to communicate, efforts to teach animals to use language have had only limited success. One of the early efforts was made by Catherine and Keith Hayes, who raised a chimpanzee named Viki in their home along with their own children. But Viki learned little and could never speak. ^[4] Researchers speculated that Viki’s difficulties might have been in part because the she could not create the words in her vocal cords, and so subsequent attempts were made to teach primates to speak using sign language or using boards on which they can point to symbols.

Allen and Beatrix Gardner worked for many years to teach a chimpanzee named Washoe to sign using ASL. Washoe, who lived to be 42 years old, could label up to 250 different objects and make simple requests and comments, such as “please tickle” and “me sorry.” ^[5] Washoe’s adopted daughter Loulis, who was never exposed to human signers, learned more than 70 signs simply by watching her mother sign.

The most proficient nonhuman language speaker is Kanzi, a bonobo who lives at the Language Learning Center at Georgia State University. ^[6] As you can see in the following video clip, Kanzi has a propensity for language that is in many ways similar to humans’. He learned faster when he was younger than when he got older, he learns by observation, and he can use symbols to comment on social interactions rather than simply for food treats. Kanzi can also create elementary syntax and understand relatively complex commands. Kanzi can make tools and can even play Pac-Man.

And yet even Kanzi does not have a true language in the same way that humans do. Human babies learn words faster and faster as they get older, but Kanzi does not. Each new word he learns is almost as difficult as the one before. Kanzi usually requires many trials to learn a new sign, whereas human babies can speak words after only one exposure. Kanzi’s language is focused primarily on food and pleasure and only rarely on social relationships. Although he can combine words, he generates few new phrases and cannot master syntactic rules beyond the level of about a 2-year-old human child. ^[7]

In sum, although many animals communicate, none of them have a true language. With some exceptions, the information that can be communicated in nonhuman species is limited primarily to displays of liking or disliking and related to basic motivations of aggression and mating. Humans also use this more primitive type of communication, in the form of nonverbal behaviors such as eye contact, touch, hand signs, and interpersonal distance, to communicate their like or dislike for others, but they (unlike animals) supplant this more primitive communication with language. Although other animal brains share similarities to ours, only the human brain is complex enough to create language. What is perhaps most remarkable is that although language never appears in nonhumans, language is universal in humans. All humans, unless they have a profound brain abnormality or are completely isolated from other humans, learn language.

Psychologists have long debated how to best conceptualize and measure intelligence. These questions include how many types of intelligence there are, the role of nature versus nurture in intelligence, how intelligence is represented in the brain, and the meaning of group differences in intelligence.

Psychologists have studied human intelligence since the 1880s. As you will read, there are several theories of intelligence and a variety of tests to measure intelligence. In fact, some define intelligence as whatever an intelligence test measures. And most intelligence tests measure how much knowledge one has, or in other words, “school smarts”. Today, most psychologists define intelligence as a mental ability consisting of the ability to learn from experience, solve problems, and use knowledge to adapt to new situations.

In the early 1900s, the French psychologist Alfred Binet (1857–1914) and his colleague Henri Simon (1872–1961) began working in Paris to develop a measure that would differentiate students who were expected to be better learners from students who were expected to be slower learners. The goal was to help teachers better educate these two groups of students. Binet and Simon developed what most psychologists today regard as the first intelligence test, which consisted of a wide variety of questions that included the ability to name objects, define words, draw pictures, complete sentences, compare items, and construct sentences.

Binet and Simon believed that the questions they asked their students, even though they were on the surface dissimilar, all assessed the basic abilities to understand, reason, and make judgments. And it turned out that the correlations among these different types of measures were in fact all positive; students who got one item correct were more likely to also get other items correct, even though the questions themselves were very different.

Charles Spearman’s two-factor theory of intelligence. He believed that one general intelligence (g) influenced other specific intelligences (s).

On the basis of these results, the psychologist Charles Spearman (1863–1945) hypothesized that there must be a single underlying construct that all of these items measure. He called the construct that the different abilities and skills measured on intelligence tests have in common the general intelligence factor (g). Virtually all psychologists now believe that there is a generalized intelligence factor, g, that relates to abstract thinking and that includes the abilities to acquire knowledge, to reason abstractly, to adapt to novel situations, and to benefit from instruction and experience. People with higher general intelligence learn faster.

Soon after Binet and Simon introduced their test, the American psychologist Lewis Terman (1877–1956) developed an American version of Binet’s test that became known as the Stanford-Binet Intelligence Test. The Stanford-Binet is a measure of general intelligence made up of a wide variety of tasks including vocabulary, memory for pictures, naming of familiar objects, repeating sentences, and following commands.

Although there is general agreement among psychologists that g exists, there is also evidence for specific intelligence (s), a measure of specific skills in narrow domains. One empirical result in support of the idea of s comes from intelligence tests themselves. Although the different types of questions do correlate with each other, some items correlate more highly with each other than do other items; they form clusters or clumps of intelligences.

One distinction is between fluid intelligence, which refers to the capacity to learn new ways of solving problems and performing activities, and crystallized intelligence, which refers to the accumulated knowledge of the world we have acquired throughout our lives. These intelligences must be different because crystallized intelligence increases with age—older adults are as good as or better than young people in solving crossword puzzles—whereas fluid intelligence tends to decrease with age.

Other researchers have proposed even more types of intelligences. L. L. Thurstone ^[1] proposed that there were seven clusters of primary mental abilities: word fluency, verbal comprehension, spatial ability, perceptual speed, numerical ability, inductive reasoning, and memory. But even these dimensions tend to be at least somewhat correlated, showing again the importance of g.

The goal of most intelligence tests is to measure g, the general intelligence factor. Good intelligence tests are reliable, meaning that they are consistent over time, and also demonstrate construct validity, meaning that they actually measure intelligence rather than something else. Because intelligence is such an important individual difference dimension, psychologists have invested substantial effort in creating and improving measures of intelligence, and these tests are now the most accurate of all psychological tests. In fact, the ability to accurately assess intelligence is one of the most important contributions of psychology to everyday public life.

Intelligence changes with age. A 3-year-old who could accurately multiply 183 by 39 would certainly be intelligent, but a 25-year-old who could not do so might be seen as unintelligent. Thus, understanding intelligence requires that we know the norms or standards in a given population of people at a given age. The standardization of a test involves giving it to a large number of people at different ages and computing the average score on the test at each age level.

It is important that intelligence tests be standardized periodically to determine that the average scores on the test at each age level remain the same; in other words, that the median score of 100 remains the same for each age level on the test over time. James Flynn, a New Zealand researcher, discovered that the mean IQ score of 100 between the years 1918 and 1995 had actually risen by about 25 points. ^[1] This is called the Flynn effect, referring to the observation that scores on intelligence tests worldwide have increased substantially over the past decades. Although the increase varies somewhat from country to country, the average increase is about 3 IQ points every 10 years. It is uncertain what causes this increase in intelligence on IQ tests. But some of the explanations for the Flynn effect include better nutrition, increased access to information, and more familiarity with multiple-choice tests. Whether people are actually getting smarter is debatable.

Once the standardization has been accomplished, we have a picture of the average abilities of people at different ages and can calculate a person’s mental age, which is the age at which a person is performing intellectually. If we compare the mental age of a person to the person’s chronological age, the result is the intelligence quotient (IQ), a measure of intelligence that is adjusted for age. A simple way to calculate IQ is by using the following formula:

IQ = mental age ÷ chronological age × 100

A 10-year-old child who does as well as the average 10-year-old child has an IQ of 100 (10 ÷ 10 × 100), whereas an 8-year-old child who does as well as the average 10-year-old child would have an IQ of 125 (10 ÷ 8 × 100). Most modern intelligence tests are based on the relative position of a person’s score among people of the same age, rather than on the basis of this formula, but the idea of an intelligence “ratio” or “quotient” provides a good description of the score’s meaning.

A number of scales are based on the IQ. The Wechsler Adult lntelligence Scale (WAIS) is the most widely used intelligence test for adults. The current version of the WAIS, called the WAIS-IV, was standardized on 2,200 people ranging from 16 to 90 years of age. It consists of 15 different tasks, each designed to assess intelligence, including working memory, arithmetic ability, spatial ability, and general knowledge about the world (see the figure below). The WAIS-IV yields scores on four domains: verbal, perceptual, working memory, and processing speed. The reliability of the test is high (more than 0.95), meaning that when a person is assessed at different times on the test, the person will score approximately the same every time with more than a 95% accuracy rate.

The WAIS-IV also shows substantial validity; it is correlated highly with other IQ tests such as the Stanford-Binet, as well as with criteria of academic and life success, including college grades, measures of work performance, and occupational level. It also shows significant correlations with measures of everyday functioning among the mentally retarded.

The Wechsler scale has also been adapted for preschool children in the form of the Wechsler Primary and Preschool Scale of Intelligence (WPPSI-III) and for older children and adolescents in the form of the Wechsler Intelligence Scale for Children (WISC-IV).

Sample Items from the Wechsler Adult Intelligence Scale (WAIS)

From Flat World Knowledge, Introduction to Psychology, v1.0. Adapted from Thorndike, R. L., and Hagen, E. P. (1997). Cognitive Abilities Test (Form 5): Research Handbook. Chicago: Riverside Publishing.

learn by doing

Let's now look at the concepts of reliability and validity. These are concepts that are easily confused with one another and, in fact, they are related. A valid test must be reliable, but the fact that a test is reliable does not mean it is valid. So what is the difference?

Validity refers to the degree to which a test or other measure of some psychological construct actually measures that construct. A valid measure of your self-confidence is a questionnaire or other measure that accurately indicates or predicts your true level of self-confidence. There are a couple of things to notice about this definition.

First, it says “the degree to which…”—that means that validity is not an all-or-none idea. Some tests are more valid than other tests. You will seldom see a test in general use that is absolutely invalid, because such a test will be noticed and discarded by people who want to study the construct being measured (e.g., self-confidence).

Second, validity is a very difficult characteristic to prove, particularly when you are trying to measure something as complex as self-esteem or level of depression. For this reason, any test in widespread use in psychology has many studies that attempt to determine how valid it is in measuring what it is trying to measure and enumerating its limitations.

Reliability refers to the degree to which a test keeps producing the same or similar results over repeated testing. In other words, reliability is another term for consistency. There are a couple of things to notice here, as well.

First, reliability, like validity, is not all-or-none. Some tests are more reliable than other tests.

Second, reliability is easier to establish than validity, because we can easily conduct research that allows us to see if a test gives the same answer on repeated testing.

A nice metaphor for thinking about validity and reliability comes from target shooting. Imagine that you go to a target range and shoot at a target for a bull’s eye. Here is what you hope you will see when you are done:

But let’s imagine that the target below is the one you produce:

What’s wrong? The hits are all clustered together, so you are very consistent. The trouble is that you are missing the place you are aiming for.

For your review, here are four drawings of targets that illustrate the various levels of validity and reliability.

Now let’s apply the concepts of validity and reliability to a psychological test designed to measure self-confidence. A person’s true self-confidence is the “center of the target.” The self-confidence test requires people to answer five questions, such as the ones below. The person reads each statement and then rates himself or herself on a scale of 1 to 5, with 1 representing strong disagreement with the statement and 5 representing strong agreement with the statement.

This is not a real self-confidence test but just an example. As you can see, the test will result in a minimum score of 5 and a maximum score of 25. A person’s score can then be compared to his or her actual or true self-confidence level to determine how closely the test predicts the respondent’s actual self-confidence. The closer the result is to the true self-confidence level, the higher the validity.

To help you with this activity, each person’s true level of self-confidence is provided in the chart below in the column labeled TRUTH. Obviously, in real life, we don’t associate a person’s actual self-confidence level with a score—that’s why we are using this self-questionnaire.

Imagine that you gave the self-confidence test to 10 people, and then you retested them a week later. The chart below lists each person’s test scores for Week 1 and Week 2. The two scores are compared to determine whether they are consistent with each other. The more consistent the test scores, the higher the test reliability. Now you want to determine the validity and reliability of the self-confidence test.

Here is another example with different scores for each person for weeks 1 and 2:

Following is another example that presents more difficulty in determining the level of validity and reliability. Let’s see if you can get this one correct.

Depending on the design, intelligence tests measure achievement (what one has already learned) and aptitude (an ability to learn). Most licensed psychologists, who want to determine one’s mental abilities with regard to any mental disorders, will assess an individuals IQ that measures both achievement and aptitude. A psychologist will use tests such as the Standford Binet or one of the Wechsler scales.

More familiar intelligence tests are aptitude tests that are designed to measure one’s ability to do well in college or in postgraduate training. Most U.S. colleges and universities require students to take an aptitude test such as the Scholastic Assessment Test (SAT) or the American College Test (ACT), and postgraduate schools require the Graduate Record Examination (GRE), Medical College Admissions Test (MCAT), or the Law School Admission Test (LSAT). These tests are useful as one criteria for selecting students because they predict academic success in the programs that they are designed for, particularly in the first year of the program. These aptitude tests also measure, in part, intelligence. Frey and Detterman ^[1] found that the SAT correlated highly (between about r = .7 and r = .8) with standard measures of intelligence, particularly on the WAIS.

Aptitude tests are also used by industrial and organizational (I/O) psychologists in the process of personnel selection. Personnel selection is the use of structured tests to select people who are likely to perform well at given jobs. To develop a personnel selection test, industrial and organizational (I/O) psychologists begin by conducting a job analysis in which they determine what knowledge, skills, abilities, and personal characteristics (KSAPs) are required for a given job. This is normally accomplished by surveying and/or interviewing current workers and their supervisors. Based on the results of the job analysis, I/O psychologists choose selection methods that are most likely to be predictive of job performance. Measures include tests of cognitive and physical ability and job knowledge tests, as well as measures of intelligence and personality.

Before discussing different views of intelligence and controversies related to interpreting intelligence, let’s look at the typical results that researchers get when they measure intelligence using the Wechsler Adult Intelligence Scale (WAIS), which you studied in the previous module.

The WAIS was most recently updated in 2008. A sample of 2,200 adults varying in age (16 to 90 years old), sex, race, ethnicity, and other factors was tested. Although the test has many questions, the scores are standardized so that the average performance is scored as 100. People who did better than average have scores above 100, and people who did worse than average have scores below 100.

When we list all the scores of people taking tests like the WAIS, including other intelligence tests as well as tests of aptitudes and various skills and traits, those scores frequently fall into a pattern called the normal distribution, or the bell curve. It looks like this:

Although this section is a little technical, understanding normal distribution is useful for interpreting results not only of psychological studies but also of studies in many other fields. We focus on an IQ test—the WAIS—but what you will learn can be applied any time you see a bell curve.

In the following activities, you will learn the results of the study when the IQ scores from the 2,200 adults were analyzed.

learn by doing

The recent study tested 2,200 people, but for our purposes, let’s reduce the number to 16 people, and later we will discuss the results for all 2,200 people. Imagine that the 16 people pictured below participated in the IQ study. Each photo is labeled with the individual's IQ score.

Let’s see what happens when we organize them according to their IQ scores. Your task is to drag each person to an appropriate box below. You have only 16 people, so a lot of the boxes will be empty.

Start with the people with average IQ. Drag the pictures of the people with exactly average IQ (remember, average = 100 in IQ scores) into the purple boxes, starting with the bottom box.

Adobe Flash Player is required.

Get Adobe^® Flash^® Player.

Test My System

Notice what happens as you get further to the right. What you see here with our little sample of 16 people is very much like what would happen if you had all 2,200 scores.

Now let’s eliminate the empty boxes.

Photos in this exercise courtesy of eisenbahner, Victor1588, Clarkston SCAMP, expertinfantry, Adam Pniak, Mark Ramsey, Adam, L’Iconoclaste Banal, gareth1953, wonderlane, anantel, Wrote, andyj300, ~MVI~ (sleepless in Bangkok), darcyadelaide, Falkirk Council Image Library (CC-BY-2.0), and U.S. Fish and Wildlife Service (Public Domain). Note: For the purposes of this activity, IQ scores were randomly assigned to these images.

What we have here is called a frequency distribution. It shows how frequently each score (in this case, each IQ score) appears in our group. Let’s see if you can read it accurately.

The group of people, or distribution, below looks like a triangle.

However, if all 2,200 people and all the possible IQ scores were represented, the shape would look like this:

The black line that goes above and around our 16 people has a distinctive shape, which gives the graph its name: bell curve.

It is also called the normal distribution. It shows how many people have each score on the IQ scale or the scale for any other test or measure (e.g., height, weight, achievement test score, and many others).

Let’s look at the bell curve without our little people inside.

Now imagine 2,200 people squeezed beneath our bell curve. Notice that the numbers are now gone from the Y axis on the left, so you can only talk in terms of more or fewer people with any particular score.

When working with the bell curve, researchers often want to identify locations or regions. For instance, they might want to talk about the top 10% of IQ scores or the middle 50%. To do this, they break the curve into units, and for IQ those units are 15 points wide. This 15-point step is called a standard deviation.

For example, here is our bell curve, but notice that we have colored in a region that goes from the mean (IQ = 100) to 15 points above the mean (100 + 15 = 115). Because this segment covers exactly 15 points, it is one standard deviation wide.

To keep track of these units, we start counting from the mean (100) and count the standard deviation steps from the mean in each direction. Here is another picture of the bell curve with the standard deviation steps marked above the IQ scores.

And here is the area from the mean (100) to one standard deviation, or 15 points below the mean (100 − 15 = 85).

As you can see, the further you get away from the mean, the smaller the area under the curve in the 15-point units.

Here is the area between one and two standard deviations below the mean.

And now we go between two and three standard deviations below the mean.

We can keep going, but now you see there aren’t many people left as we get to the area between three and four standard deviations below the mean.

Let’s look more closely at this. Here is the bell curve with the region covering the first standard deviation above the mean colored in blue. Notice the numbers above this region. It shows that this is 34% of the total area under the curve (just a little more than one-third of the total). To put that in perspective, the number below it shows how many people out of that original group of 2,200 used to standardize the IQ test are in this area: 748 out of 2,200.

If we go the same distance on the other side of the mean, we now show two colored regions: one above the mean (100 to 115) and one below the mean (100 down to 85).

Just above each segment, you can see the percentage of the area under the curve and the number of people in that unit. On top, in red, you can see the sum of these colored-in areas. This figure says that 748 people out of 2,200 had IQ scores between 100 and 115 and another 748 had IQ scores between 100 and 85, so a total of 1,496 had IQ scores between 85 and 115. That is just a little more than two-thirds of the total set of 2,200. Of course, we’re not really interested in those 2,200 people. They simply represent the larger population of adults.

In the previous section, we explored the normal distribution in relation to the IQ scores of samples of particular people. However, IQ scores in the general population are also normally distributed. The figure below displays the distribution of IQ scores in the general population.

Distribution of IQ Scores in the General Population

The normal distribution of IQ scores in the general population shows that most people have about average intelligence, while very few have extremely high or extremely low intelligence. From Flat World Knowledge, Introduction to Psychology, v1.0, CC-BY-NC-SA.

One end of the distribution of intelligence scores is defined by people with very low IQ. Mental retardation is a generalized disorder ascribed to people who have an IQ below 70, who have experienced deficits since childhood, and who have trouble with basic life skills, such as self-care and communicating with others. ^[1] About 1% of the U.S. population, most of them males, fulfill the criteria for mental retardation, but some children who are diagnosed as mentally retarded lose the classification as they get older and better learn to function in society. A particular vulnerability of people with low IQ is that they may be taken advantage of by others, and this is an important aspect of the definition of mental retardation. ^[2] Mental retardation is divided into four categories: mild, moderate, severe, and profound. Severe and profound mental retardation is usually caused by genetic mutations or accidents during birth, whereas mild forms have both genetic and environmental influences.

One cause of mental retardation is Down syndrome, a chromosomal disorder leading to mental retardation caused by the presence of all or part of an extra 21st chromosome. The incidence of Down syndrome is estimated at 1 per 800 to 1,000 births, although its prevalence rises sharply in those born to older mothers. People with Down syndrome typically exhibit a distinctive pattern of physical features, including a flat nose, upwardly slanted eyes, a protruding tongue, and a short neck.

Societal attitudes toward individuals with mental retardation have changed over the past decades. We no longer use terms such as “moron,” “idiot,” or “imbecile” to describe these people, although these were the official psychological terms used to describe degrees of retardation in the past. Laws such as the Americans with Disabilities Act (ADA) have made it illegal to discriminate on the basis of mental and physical disability, and there has been a trend to bring the mentally retarded out of institutions and into our workplaces and schools. In 2002 the U.S. Supreme Court ruled that the execution of people with mental retardation is “cruel and unusual punishment,” thereby ending this practice. ^[3]

One advocate of the idea of multiple intelligences is the psychologist Robert Sternberg. Sternberg has proposed a triarchic (three-part) theory of intelligence that proposes that people may display more or less analytical intelligence, creative intelligence, and practical intelligence. Sternberg ^{[1] [2]} argued that traditional intelligence tests assess analytical intelligence, the ability to answer problems with a single right answer, but that they do not well assess creativity (the ability to adapt to new situations and create new ideas) or practicality (e.g., the ability to write good memos or to effectively delegate responsibility).

As Sternberg proposed, research has found that creativity is not highly correlated with analytical intelligence, ^[3] and exceptionally creative scientists, artists, mathematicians, and engineers do not score higher on intelligence than do their less creative peers. ^[4] Furthermore, the brain areas associated with convergent thinking, thinking that is directed toward finding the correct answer to a given problem, are different from those associated with divergent thinking, the ability to generate many different ideas for or solutions to a single problem. ^[5] On the other hand, being creative often takes some of the basic abilities measured by g, including the abilities to learn from experience, to remember information, and to think abstractly. ^[6]

Studies of creative people suggest at least five components that are likely to be important for creativity:

1. Expertise: Creative people have carefully studied and know a lot about the topic they are working in. Creativity comes with a lot of hard work. ^{[7] [8]}
2. Imaginative thinking: Creative people often view a problem in a visual way, allowing them to see it from a new and different point of view.
3. Risk taking: Creative people are willing to take on new but potentially risky approaches.
4. Intrinsic interest: Creative people tend to work on projects because they love doing them, not because they are paid for them. In fact, research has found that people who are paid to be creative are often less creative than those who are not paid. ^[9]
5. Working in a creative environment: Creativity is in part a social phenomenon. Simonton ^[10] found that the most creative people were supported, aided, and challenged by other people working on similar projects.

The last aspect of the triarchic model, practical intelligence, refers primarily to intelligence that cannot be gained from books or formal learning. Practical intelligence represents a type of “street smarts,” or common sense, that is learned from life experiences. Although a number of tests have been devised to measure practical intelligence, ^{[11] [12]} research has not found much evidence that practical intelligence is distinct from g or that it is predictive of success at any particular tasks. ^[13] Practical intelligence may include, at least in part, certain abilities that help people perform well at specific jobs, and these abilities may not always be highly correlated with general intelligence. ^[11] On the other hand, these abilities or skills are very specific to particular occupations and do not seem to represent the broader idea of intelligence.

Another champion of the idea of multiple intelligences is the psychologist Howard Gardner. ^{[14] [15]} Gardner argued that it would be evolutionarily functional for different people to have different talents and skills and proposed that there are eight intelligences that can be differentiated from each other (shown in the table below). Gardner noted that some evidence for multiple intelligences comes from the abilities of autistic savants, people who score low on intelligence tests overall but who nevertheless may have exceptional skills in a given domain, such as math, music, art, or in being able to recite statistics in a given sport. ^[16]

The idea of multiple intelligences has been influential in the field of education, and teachers have used these ideas to try to teach differently to different students. For instance, to teach math problems to students who have particularly good kinesthetic intelligence, a teacher might encourage the students to move their bodies or hands according to the numbers. On the other hand, some have argued that these “intelligences” sometimes seem more like “abilities” or “talents” rather than real intelligence. And there is no clear conclusion about how many intelligences there are. Are sense of humor, artistic skills, dramatic skills, and so forth also separate intelligences? Furthermore, and again demonstrating the underlying power of a single intelligence, the many different intelligences are in fact correlated and thus represent, in part, g. ^[17]

Although most psychologists have considered intelligence a cognitive ability, people also use their emotions to help them solve problems and relate effectively to others. Emotional intelligence is the ability to accurately identify, assess, and understand emotions, as well as to effectively control one’s own emotions. ^{[18] [19]}

The idea of emotional intelligence is seen in Howard Gardner’s interpersonal intelligence (the capacity to understand the emotions, intentions, motivations, and desires of other people) and intrapersonal intelligence (the capacity to understand oneself, including one’s emotions). Public interest in and research on emotional intellgence became widely prevalent following the publication of Daniel Goleman’s best-selling book, Emotional Intelligence: Why It Can Matter More Than IQ. ^[20]

Mayer and Salovey ^[19] developed a four-branch model of emotional intelligence that describes four fundamental capacities or skills. More specifically, this model defines emotional intelligence as the ability to

1. accurately perceive emotions in oneself and others (e.g., in the face or voice of others);
2. use emotions to facilitate thinking (i.e., to prioritize thinking or to allow creativity to emerge);
3. understand emotional meanings (i.e., understanding that specific emotions convey their own pattern of possible messages and actions associated with those messages); and
4. manage emotions (i.e., regulate and manage one’s own and others’ emotions to promote one’s own and others’ goals).

There are a variety of measures of emotional intelligence. ^{[21] [22]} One popular measure, the Mayer-Salovey-Caruso Emotional Intelligence Test, includes items about the ability to understand, experience, and manage emotions, such as these:

One problem with emotional intelligence tests is that they often do not show a great deal of reliability or construct validity. ^[23] Although it has been found that people with higher emotional intelligence are also healthier, ^[24] findings are mixed about whether emotional intelligence predicts life success—for instance, job performance. ^[25] Furthermore, other researchers have questioned the construct validity of the measures, arguing that emotional intelligence really measures knowledge about what emotions are, not necessarily how to use those emotions, ^[26] and that emotional intelligence is actually a personality trait, a part of g, or a skill that can be applied in some specific work situations—for instance, academic and work situations. ^[27]

Although measures of the ability to understand, experience, and manage emotions may not predict effective behaviors, another important aspect of emotional intelligence—emotion regulation—does. Emotion regulation is the ability to control and productively use one’s emotions. Research has found that people who are better able to override their impulses to seek immediate gratification and who are less impulsive also have higher cognitive and social intelligence. They have better SAT scores, are rated by their friends as more socially adept, and cope with frustration and stress better than those with less skill at emotion regulation. ^{[28] [29] [30]}

Because emotional intelligence seems so important, many school systems have designed programs to teach it to their students. However, the effectiveness of these programs has not been rigorously tested, and we do not yet know whether emotional intelligence can be taught or if learning it would improve the quality of people’s lives. ^[31]

What do you think intelligence is? Is it something that you are born with, largely inherited from your parents, leaving you with little room for improvement? Or is it something that can be changed through hard work and by taking advantage of opportunities to grow intellectually?

Your personal answer to this question turns out to be surprisingly important. It may even affect your intelligence! Stanford University psychologist Carol Dweck has spent her career studying how people’s beliefs about their own abilities—particularly mental abilities like intelligence—influence the kinds of challenges they give themselves. In much of her research, she has studied students, from their early prekindergarten days through college.

Dweck identified two broad “theories of intelligence” that people—from young children to mature adults—hold. Some people have an “entity” theory of intelligence. They believe that their intelligence is determined by factors present at birth, particularly related to their genetic inheritance. According to this theory, intelligence is a relatively unchangeable fact about who you are and about your potential to excel. You may work hard, but intelligence will always act as a limit for some people and as a supercharged fuel for others. Other people hold an “incremental” theory of intelligence. They believe that intelligence can be changed, particularly through efforts to learn and to excel. They believe that genetic factors are only a starting point, and people’s future competencies are not determined by their initial strengths and weaknesses.

These two theories of intelligence would only be vaguely interesting if they didn’t influence people’s behavior. But they do. It turns out that students who hold the entity theory of intelligence tend to avoid academic challenges. When given the opportunity to work on a really challenging task—with opportunity for success but also a real possibility of failure—they are less likely to take the opportunity than are their classmates who hold an incremental theory of intelligence. The students who believe that intelligence is unchangeable—the entity theory holders—are more likely to choose a task that they already know will lead to success.

Attitudes toward failure can also be predicted by knowing which theory a student has about intelligence. Students who have an entity theory of intelligence tend to interpret failure—in academics and in other aspects of life—as a message about their own inherent limitations, so failure or even the anticipation of failure reduces their motivation to work on something. For them, the way to protect their self-esteem is to avoid failure. For the students who have an incremental theory of intelligence, failure is more often seen as a challenge that can actually increase motivation. These students are more likely than their entity theorist classmates to see failure as an opportunity to discover and test their potential, thus inspiring them to try to see what they can do.

Everything you have already read in this unit should have made it clear to you that intelligence is a difficult quality to define and measure. Nevertheless, we do know that IQ—the standard measure of intelligence—can change. For example, children who are unable to attend school for a long periods due to war or extended illness show IQ levels 2 standard deviations (30 IQ points) below their peers who are attending school. ^[1] On the positive side, research has shown that children, particularly children from low socioeconomic groups, can improve in IQ if they are placed in an enriched prekindergarten program and then in an elementary school of sufficient quality to maintain these gains. ^[2] Sadly, if children are only placed in enriched preschools, but later attend academically poor elementary schools, their IQ gains diminish or even disappear.

From the earliest days of IQ testing, people have wondered about group differences in intelligence. You will probably not be surprised to learn that studies of differences between groups in intelligence can easily feed stereotypes and prejudices, and raise questions about testing biases and even the integrity of the researchers.

You might think that the question of differences between men and women could easily be resolved by analyzing IQ tests for thousands of people and simply reporting the results. But it turns out that this won’t work. The most commonly used IQ test, the WAIS, is regularly adjusted to eliminate questions that produce differences between men and women. Consequently, the fact that there are no gender differences on the WAIS is not interesting; the test is designed to eliminate the possibility of differences. The goal of this adjustment is to avoid including biased questions, but it means that we need to look elsewhere to answer the question of IQ differences between men and women.

Using advanced statistical techniques, researchers have been able to extract the necessary information from tests not specifically designed to measure IQ. For instance, Arthur Jensen, whose view we will discuss further in the section on race and intelligence, studied results from tests that are strongly related to IQ tests (“loaded heavily on g”) but have not been adjusted to eliminate gender differences. Jensen ^[1] found minor differences between men and women on tests of specific abilities, but he found no overall differences between men and women in average intelligence. Using a different strategy, James Flynn ^[2] looked at results from the Raven’s Progressive Matrices test, a well-regarded nonverbal measure of intelligence, and found that males and females were not different either in the childhood samples or adult samples. The generally accepted view today is that the average IQs for men and women are the same.

This is not the end of questions about sex differences in intelligence, however. In 2006, Lawrence Summers, president of Harvard University, was discussing reasons that far more men than women go into advanced positions in science and engineering. Citing published research, Summers suggested that there may not be a difference between the average intelligence for men and women, but men may be more variable in their intelligence.

Prof. Summers’ claim is not without some foundation. Mental retardation (i.e., IQ below 70) is about 3.6 times more common for males than females. ^[3] Note that the diagnosis of mental retardation is based on more than scores on a standard IQ test, but this fact is consistent with the low end of the blue curve in the figure—more males than females appear to occupy that lower region. Summers’ statement about the high end of the distributions is based primarily on data showing more males than females among the highest scorers on tests of mathematics and quantitative reasoning. For instance, in the 1980s, twelve times more boys than girls scored above 700 (out of a possible 800) on the SAT test. ^[4] These results are consistent with the high extreme depicted in the figure: the blue curve for males is higher (more individuals) on the right than the red curve for females.

Why are there these differences between the spread of scores for males and for females in intelligence-related measures? Most researchers think that the male and female distributions would be about the same on the lower end of the distributions if males were not more vulnerable to genetic and prenatal factors that can hurt development of brain structures related to thinking. Some X-chromosome regions have been linked to mental retardation, and only males have a Y chromosome. Furthermore, prenatal steroidal hormones influence brain structures related to intelligence, and males fetuses are exposed to massively higher levels of these steroids than are female fetuses. Estrogen, an important female hormone, may be a protective factor for girls and women, reducing the impact of biological factors that can influence intellectual functioning.

On the high extreme, genetic and other biological factors favoring males have not been found. Instead, experience appears to be the critical factor. For instance, differences between men and women on mathematics and other quantitative skills are rapidly diminishing as girls and women take more mathematics-related courses in school and are encouraged to excel in these areas. The 12:1 ratio of males over females on the quantitative SAT scores comes from data in the mid-20th century. Sex differences have dramatically declined since that time. More recent studies show about a 3:1 ratio (3 times more boys than girls) at the highest levels of SAT scores. It is impossible to know if these trends will continue or not, but such a dramatic change in a few decades strongly supports the hypothesis that most or all of the differences between men and women at the high extreme of IQ-related tests can be explained by educational and motivational differences between genders, and these differences are quickly disappearing.

Intelligence tests are adjusted to eliminate gender differences, but racial and ethnic differences have been more resistant to test changes. Prior to the civil rights era of the 1960s, little attention was paid to choices of content and wording that might bias the tests in favor of one racial or ethnic group over another. During the 1960s and 1970s, the validity and fairness of IQ tests and other achievement and aptitude tests was hotly debated. Among the positive results of that discussion was the development of now-standard procedures for detecting and eliminating some types of unfair items and the increased sensitivity of testers to potential biases in the content and scoring of tests. Nevertheless, differences in culture and experience are so complex that no procedures or statistical tests can successfully detect items or procedures that are unfair to some individuals or groups. ^[1]

In the early 20th century, it was not unusual to attribute differences in average IQ scores among various racial and ethnic groups to biological causes, an interpretation sometimes called the hereditarian theory of IQ. ^[2] The belief was that some groups had evolved further than others, leading these so-called superior groups to function better intellectually than others. For instance, at the beginning of the 20th century, immigrants from Italy to America had a median tested IQ of 87, which is nearly a standard deviation (15 points) below the average of 100. One the most respected figures in intelligence testing at the time, Henry Goddard, concluded that approximately 80% of Italian immigrants were “feeble-minded,” and he made similar claims about immigrants from Russia and the Austro-Hungarian empire. Goddard and many others attributed this supposed intellectual deficiency to hereditary factors. He recommended that all immigrants to the U.S. be tested for intelligence, and those with low scores should be barred from entry. What we now know is that the intelligence tests were given in English, not the immigrants’ native language and furthermore, contained phrases that were culturally-specific. For example, in America, you may often hear the phrase “to kill two birds with one stone.” You will likely understand this to mean that you will be able to get two jobs done with one action. However, for someone not accustomed to this phrase, it will mean very little. Today, Italian Americans as a group score slightly above 100 on the average, and other immigrant groups that, like those of Italian descent, have been able to integrate with the dominant white culture show similar gains, supporting the well-known fact that early intelligence tests had extreme cultural bias and consequently, the results were widely misconstrued.

The hereditarian theory has not completely disappeared. Most notably, in 1994, a book called The Bell Curve by two well-known social scientists, Richard Herrnstein and Charles Murray, forcefully argued that some IQ differences between races are genetic and unlikely to disappear regardless of social and educational opportunities. ^[3] Not surprisingly, the book immediately led to intense and often acrimonious debate. In response to the debate, the American Psychological Association (APA) asked a group of highly regarded scientists, headed by respected psychologist Ulric Neisser of Emory University, to review the scientific literature that related to IQ differences among racial and ethnic groups, as well as sex differences.

The APA Task Force ^[4] started by noting that “intelligence” is a very complex quality and even experts disagree about its definition. Furthermore, all IQ tests assess only a limited number and range of abilities, inevitably leaving many other aspects of intelligence untested.

The APA Task Force report summarized racial and ethnic group average IQ scores from the mid-1990s. Both Asian Americans and Caucasian Americans had averages around 100, the standardized average for IQ scores. African Americans averaged around 90, having reduced the 15 points (average IQ = 85) found in earlier decades by 5 points. Hispanic Americans were found to score in the mid-90s on average.

After reviewing evidence related to IQ, the APA Task Force concluded that there is no credible evidence for a genetic explanation for racial and ethnic differences in IQ. This does not mean that our genes have no influence on IQ; that link has been firmly established. However, this simply means that our parents’ IQ is somewhat correlated with our own IQ, but this reasoning cannot be extended to group differences. To understand how genetic factors can influence the relationship between the IQ of parents and their children while not explaining differences between racial groups, work through the following activity.

learn by doing

People often confuse causes of individual differences (e.g., why you are a better athlete than your best friend) with group differences (e.g., why people from Africa currently dominate distance running). The mistake is to believe that the cause of some difference at the individual level must follow the same rules as the cause of a difference at the group level. But let’s see if this is necessarily true.

Imagine that you have two varieties of a plant. The orange variety has developed under excellent lighting conditions. Notice that some of them are tall, some are medium sized, and some are short. This is just normal variability that we find with almost any characteristic of a living thing that you measure. A second variety of the plant, with blue flowers, can be seen on the right. As with the orange variety, some are relatively tall, some are relatively medium in height, and some are relatively short.

Now we are going to see what happens when each of these plants has offspring. What do the plants that grew from each of these look like.

Let’s also imagine that this strong relationship between relative heights of parents and offspring is heavily influenced by genes. So the reason that tall plants have tall offspring is because that tall parents pass on genes that maximize growth and the reason that short parents have short offspring is because the short parents have genes that minimize growth.

Now it is time to do some transplanting. Imagine that you wonder if the blue plants are getting enough sunlight. You plant some of the blue variety in the same sunny conditions that the orange variety already enjoys. Let’s see what happens.

How could this happen? Even though genes determine relative height (in our cartoon flowers anyway), the genes don’t determine the absolute height. Better or worse growing conditions can determine just how tall the plant can possibly grow, but, within any given set of conditions, genes will determine which are the tall, medium, and short plants.

This idea is not at all unrealistic. At the end of World War II, people from the United States were the tallest people in the world. This did not mean that everyone from the United States was taller than everyone from any other country. There were still tall, medium, and short U.S. citizens and tall, medium, and short citizens of other countries, and tall parents still tended to have tall children, short parents tended to have short children, and so on. At that time, because the United States was such a dominant center for agriculture, average nutrition in the United States was superior to average nutrition in most other places, even though there were then, as now, people going hungry even in the United States. Since that time, nutrition has improved in many other countries and now citizens of the U.S. are not, on average, among the top 10 in terms of height. The tallest people in the world today are from the Netherlands. People from the U.S. have not shrunk. People from these other countries have gotten taller.

To make the point even more strongly, imagine that you planted both the orange and blue varieties in some different soil and this is what happened:

Notice that the orange plants are unaffected by the new soil, so they are the same as before. But the blue variety loves the new soil and thrives in it. Now the variety that used to be shorter on average—the blue variety—is taller on average. But there is still the same genetic link: Tall plants have tall offspring, medium plants have medium offspring, and short plants have short offspring.

Now let’s apply this same idea to intelligence.

Imagine that there are two groups of people, represented by the orange and blue borders below. The orange group lives in an intellectually stimulating environment, while the blue group lives in a less varied and intellectually challenging environment. This graphic represents the IQ levels of members of the two groups.

Photos used in this activity courtesy of Franklin Park Library and umjanedoan (CC-BY-2.0).

Now imagine that the blue group experiences an improvement of circumstances, moving to a more stimulating and intellectually challenging environment. Here is what happens:

Under intellectually enriched conditions, the blue group has now improved its average IQ. But there is still a direct relationship between parent and offspring IQ. It is possible for genes to determine the relationship between parent and offspring IQ even if environmental factors determine the average level of each group’s IQ. Of course, in the real world, unlike our cartoon world, both genes and environmental factors influence IQ, so the relationship between parent and offspring IQ is not so easily predicted as it is in our cartoons.

Although the hereditarian hypothesis is a logically possible explanation of differences between racial and ethnic groups, research doesn’t support it. There is not empirical support for the idea that racial or ethnic groups differ genetically in ways that relate to intelligence. The APA Task Force also reviewed the research on biased tests and biased testing procedures and found that these factors cannot explain the size of the group differences. Similarly, they rejected differences in socioeconomic status as an adequate explanation. In fact, although they unequivocally rejected the hereditarian explanation, they concluded that “at this point, no one knows what causes this differential,” where the “differential” is the group difference in IQ.

Even if we cannot clearly identify the reasons for racial and ethnic differences in IQ, we do know that these differences can change, just as we suggested in the Learn by Doing exercise. For example, Dickens and Flynn ^[5] looked at IQ scores from 1972 to 2002 and found a reduction in the difference between blacks and whites during this period of more than 5 IQ points, one-third of the difference between the groups.

An adoption study by Moore ^[6] looked at black children adopted into black and white families, where the children adopted by the white families could expect to receive the benefits of greater affluence and the social and cultural support of the dominant group. On later testing, children adopted into white families had IQs that were 13 points higher than the children adopted into black families. This is almost the entire 15 point difference reported between the two races at that time. These results and others suggest that racial differences in IQ are largely or completely the result of differences in experience. It is particularly interesting that black children measured at age 4 are only about 5 IQ points below white children of the same age, while the group differences are about 17 points by age 24, a finding that strongly suggests that the life experiences of black and white children may produce these diverging outcomes.

There are many ways that experience can influence intelligence. Socioeconomic status (i.e., income and social opportunities) can affect the type of neighborhood a person can afford to live in, the quality of schooling and likelihood of preschool educational opportunities, and likelihood of taking advantage of educational activities (e.g., visiting museums and historical sites). Differences in parental education levels can have a huge impact. For instance, Hart and Risley ^[7] studied interactions between adults and children in families differing in socioeconomic status and education. This was not a race difference study. They found that children of professional-level parents heard three times as many words and far more complex and unusual words than did children of unemployed parents, and children of working-class parents heard twice as many words as the children of unemployed parents. Although a word count like this may seem unimportant, exposure to language is very important for development of communication skills and categories of knowledge.

It is impossible to know for certain at this point in time why racial groups differ in measured IQ. However, it is clear that many social and environmental factors can influence intellectual development and racial groups differ substantially in typical social experiences. Furthermore, as genetics has matured as a science, the old distinction between nature and nurture has been lost. We now understand that environmental factors influence genetic expression from the moment of conception to the end of life, so differences between groups that differ in typical experiences are to be expected. Research is slowly unraveling those influences.

Although intelligence tests may not be culturally biased, the situation in which one takes a test may be. One environmental factor that may affect how individuals perform and achieve is their expectations about their ability at a task. In some cases these beliefs may be positive, and they have the effect of making us feel more confident and thus better able to perform tasks. For instance, research has found that because Asian students are aware of the cultural stereotype that “Asians are good at math,” reminding them of this fact before they take a difficult math test can improve their performance on the test. ^[1] On the other hand, sometimes these beliefs are negative, and they create negative self-fulfilling prophecies such that we perform more poorly just because of our knowledge about the stereotypes.

In 1995 Claude Steele and Joshua Aronson tested the hypothesis that the differences in performance on IQ tests between Blacks and Whites might be due to the activation of negative stereotypes. ^[2] Because Black students are aware of the stereotype that Blacks are intellectually inferior to Whites, this stereotype might create a negative expectation, which might interfere with their performance on intellectual tests through fear of confirming that stereotype.

In support of this hypothesis, the experiments revealed that Black college students performed worse (in comparison to their prior test scores) on standardized test questions when this task was described to them as being diagnostic of their verbal ability (and thus when the stereotype was relevant), but that their performance was not influenced when the same questions were described as an exercise in problem solving. And in another study, the researchers found that when Black students were asked to indicate their race before they took a math test (again activating the stereotype), they performed more poorly than they had on prior exams, whereas White students were not affected by first indicating their race.

Steele and Aronson argued that thinking about negative stereotypes that are relevant to a task that one is performing creates stereotype threat—performance decrements that are caused by the knowledge of cultural stereotypes. That is, they argued that the negative impact of race on standardized tests may be caused, at least in part, by the performance situation itself. Because the threat is “in the air,” Black students may be negatively influenced by it.

Research has found that stereotype threat effects can help explain a wide variety of performance decrements among those who are targeted by negative stereotypes. For instance, when a math task is described as diagnostic of intelligence, Latinos and Latinas perform more poorly than do Whites. ^[3] Similarly, when stereotypes are activated, children with low socioeconomic status perform more poorly in math than do those with high socioeconomic status, and psychology students perform more poorly than do natural science students. ^{[4] [5]}

Even groups who typically enjoy advantaged social status can be made to experience stereotype threat. White men perform more poorly on a math test when they are told that their performance will be compared with that of Asian men, ^[6] and Whites perform more poorly than Blacks on a sport-related task when it is described to them as measuring their natural athletic ability. ^{[7] [8]}

Research has found that stereotype threat is caused by both cognitive and emotional factors. ^[9] On the cognitive side, individuals who are experiencing stereotype threat show an increased vigilance toward the environment as well as increased attempts to suppress stereotypic thoughts. Engaging in these behaviors takes cognitive capacity away from the task. On the affective side, stereotype threat occurs when there is a discrepancy between our positive concept of our own skills and abilities and the negative stereotypes that suggest poor performance. These discrepancies create stress and anxiety, and these emotions make it harder to perform well on the task.

Stereotype threat is not, however, absolute; we can get past it if we try. What is important is to reduce the self doubts that are activated when we consider the negative stereotypes. Manipulations that affirm positive characteristics about the self or one’s social group are successful at reducing stereotype threat. ^{[10] [11]} In fact, just knowing that stereotype threat exists and may influence our performance can help alleviate its negative impact. ^[12]

Conception occurs when an egg from the mother is fertilized by a sperm from the father. In humans, the conception process begins with ovulation, when an ovum, or egg (the largest cell in the human body), which has been stored in one of the mother’s two ovaries, matures and is released into the fallopian tube. Ovulation occurs about halfway through the woman’s menstrual cycle and is aided by the release of a complex combination of hormones. In addition to helping the egg mature, the hormones also cause the lining of the uterus to grow thicker and more suitable for implantation of a fertilized egg.

If the woman has had sexual intercourse within 1 or 2 days of the egg’s maturation, one of the up to 500 million sperm deposited by the man’s ejaculation, which are traveling up the fallopian tube, may fertilize the egg. Although few of the sperm can make the long journey, some of the strongest swimmers succeed in meeting the egg. As the sperm reach the egg in the fallopian tube, they release enzymes that attack the outer jelly-like protective coating of the egg, each trying to be the first to enter. When one of the millions of sperm enters the egg’s coating, the egg immediately responds by blocking out all other challengers and at the same time pulling in the single successful sperm.

Prenatal development is a complicated process and may not always go as planned. About 45% of pregnancies result in a miscarriage, often without the mother ever being aware it has occurred. ^[1] Although the amniotic sac and the placenta are designed to protect the embryo, substances that can harm the fetus, known as teratogens, may nevertheless cause problems. Teratogens include general environmental factors, such as air pollution and radiation, as well as cigarettes, alcohol, and drugs that the mother may use. Teratogens do not always harm the fetus, but they are more likely to do so when they occur in larger amounts, for long time periods, and during the more sensitive phases of fetal development, such as when the fetus is growing most rapidly. The most vulnerable period for many of the fetal organs is very early in the pregnancy—before the mother even knows she is pregnant.

Harmful substances that the mother ingests may harm the child. Cigarette smoking, for example, reduces the blood oxygen for both the mother and child and can cause a fetus to be born severely underweight. Another serious threat is fetal alcohol syndrome (FAS), a condition caused by maternal alcohol drinking that can lead to numerous detrimental developmental effects, including limb and facial abnormalities, genital anomalies, and mental retardation. One in about every 500 babies in the United States is born with fetal alcohol syndrome, and it is considered one of the leading causes of retardation in the world today. ^[2] Because there is no known safe level of alcohol consumption for a pregnant woman, the U.S. Centers for Disease Control and Prevention recommends that “a pregnant woman should not drink alcohol.” ^[3] Therefore, the best approach for expectant mothers is to avoid alcohol completely. Maternal drug abuse is also of major concern and is considered one of the greatest risk factors facing unborn children.

The environment in which the mother lives also has a major impact on infant development. ^{[4] [5]} Children born into homelessness or poverty are more likely to have mothers who are malnourished; who suffer from domestic violence, stress, and other psychological problems; and who smoke or abuse drugs. Children born into poverty are also more likely to be exposed to teratogens. Poverty’s impact may also amplify other issues, creating substantial problems for healthy child development. ^{[6] [7]} Mothers normally receive genetic and blood tests during the first months of pregnancy to determine the health of the embryo or fetus. They may undergo sonogram, ultrasound, amniocentesis, or other testing. The screenings detect potential birth defects, including neural tube defects, chromosomal abnormalities (such as Down syndrome), genetic diseases, and other potentially dangerous conditions. Early diagnosis of prenatal problems can allow medical treatment to improve the health of the fetus.