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Conditioning affects a wide range of behaviors, far beyond just salivation. One is how we react to painful stimuli. Our bodies work to maintain internal states within safe limits (homeostasis), and conditioning allows us to anticipate painful stimuli, and to take action to counteract them. Conditioning also affects a wide range of emotions, including fear, hunger, sexual arousal, and cravings for alcohol and drugs. And conditioning can also be used to treat problems involving these emotions. In aversion therapy, exposure to alcohol is followed by inducd illness; by creating an aversion to alcohol, this therapy has had considerable success in treating alcoholism. Conditioning has also been used to treat phobias. Phobias often develop through conditioning, and conditioning principles can be used to overcome them. In exposure therapies such as systematic desensitization, the feared stimulus is presented and not followed by harmful consequences (in one variant, virtual reality therapy, the stimuli are presented through virtual reality headsets). The aim is to extinguish the fear, and this treatment too has had considerable success.
One assumption underlying research on learning and memory is that behavior is lawful, determined by our environment and heredity. Examples of powerful influence include child abuse, aggression, advertising, and sexual attraction. These examples reveal how powerfully our behavior can be determined, sometimes without our knowledge, but they do not rule out the possiblity that we also possess some free will. A second assumption is that the best way to discover laws is through experiments. Experiments allow us to separate possible causes of behavior, but finding appropriate control groups can be tricky, slowing progress. Two contrasting approaches have dominated psychology, influencing what topics researchers choose to study: behaviorism and cognitive psychology. A third assumption is that studying animals can be helpful in analyzing behavior, because animal research allows greater control of environmental and genetic variables, and animal and human behavior is far more similar than once believed—as shown, for example, in the ability of chimpanzees and even birds to acquire English vocabulary. However, animal research can also raise difficult ethical issues. The chapter concludes with an introduction to some of the key forms of learning and memory that will be discussed.
To study memory, Ebbinghaus memorized lists of nonsense syllables. He found that success depended on the amount and spacing of trials, and that forgetting occured rapidly at first but then more slowly. He believed that practice strengthens associations, but research on levels of processing showed that practice is not sufficient; deeper and more elaborate processing enhances memory. Similarly, research on textual material demonstrated that we don’t just associate successive words; we abstract and store their underlying meaning. Purely associative accounts also proved unable to explain the acquisition of motor skills; we create motor programs to guide our movements. To understand all these processes, psychologists adopted an information-processing framework, studying how information is coded, stored, and retrieved. Important clues came from two discoveries: that participants can remember only about seven new items at one time, and that these items are forgotten within seconds if rehearsal is prevented. To explain this, Atkinson and Shiffrin proposed that information is initially held in a temporary or short-term store that has only a limited capacity. Their model also accounts for the fact that we remember words from the beginning and end of a list better than from the middle (the serial position effect).
Our brains consist of billions of neurons in densely-interconnected networks, and they control every aspect of our behavior, our movements, thoughts, and feelings. To explore their functioning, theorists have proposed neural network models in which every unit is connected to every other unit. Activity in one will spread to the others, depending on the strength of their connections. A key assumption is that when units are active simultaneously, their connection is strengthened; one formula used to calculate such changes is the delta rule, which is almost identical to the fomula of the Rescorla-Wagner model. These simple networks prove to be surprisingly powerful; they can account for many features of conditioning, concept learning, and memory. One recent development has been deep learning models that incorporate hidden units, between input and output units. This seemingly small innovation has dramatically increased the ability of these models to carry out sophisticated tasks; examples include beating world champions at chess and diagnosing skin cancer. One problem is that learning is slow, and new learning can result in the loss of older information (catastrophic interference). Whatever their ultimate fate, these models have demonstrated the power of even simple networks to perform tasks of astonishing sophistication.
The method of loci is one of the most effective techniques for memorizing lists. Its effectiveness reflects several memory principles, including elaboration, imagery, and the generation effect. The effectiveness of studying depends on the amount and spacing of practice; not just reading passively but actively thinking about material; and practicing retrieving what you’ve read: Practice, Think, and Review. The accuracy of eyewitness testimony can vary widely; important factors include the weapon-focus effect (distraction if a weapon is present), source confusion, and emotional intensity. Accuracy can be substantially improved by using the cognitive interview, in which witnesses are questioned in a manner designed to re-create the original scene as fully as possible, thereby maximizing possible retrieval cues. The accuracy of lineups can also be improved, by warning witnesses that the criminal may not be present. Recovered memories of childhood abuse can be false, as source confusion can make it difficult for people to tell whether their memories are based on real events or only ones that they imagined or heard described; therapeutic techniques such as hypnosis and guided imagery can exacerbate the problem. However, there is also compelling evidence that some recovered memories are true.
A wide variety of events can function as reinforcers. The Premack principle provides a useful guide; activities that individuals engage in when given a free choice will probably be effective reinforcers. One factor is the delay between the response and reinforcer; we discount, or give less value, to rewards that are delayed. Effectiveness also depends on the schedule of reinforcement; partial reinforcement (reinforcing only some responses) produces greater persistence in extinction. Effectiveness also depends on how the reinforcer contrasts with past reinforcers—we value a reinforcer less if we are accustomed to more attractive reinforcers—and how long we have been deprived of it. The stimuli present during reinforcement are also important; we are more likely to repeat a response if we are in the same environment where we obtained it previously. Which elements of that environment will be important, though, can be difficult to predict, depending in part on attention and perceptual learning (with practice we can become better at distinguishing elements of a situation). The chapter ends with an application involving shaping—when a behavior is difficult to train, start by reinforcing the response closest to it, and then gradually reinforce closer approximations.
Thorndike believed that reinforcement was an essentially simple process in which the reinforer stamped in an association between the preceding stimulus and response (S-R theory). Tolman disagreed, arguing that reinforcement was a more sophisticated process in which animals formed expectations that the response would produce the reinforcer. Behaviorists at first rejected the postulation of mental states, but both sides eventually agreed that it was acceptable to talk about invisible events (intervening variables), provided that they were couched in clear theories that led to testable predictions. This requirement proved difficult to satisfy, but it now looks as if Thorndike and Tolman were both right; evolution first produced a relatively simple associative system in which learning can occur without our awareness, but also to a more sophisticated system based on expectations. When several reinforced responses are available, the matching law says that we will distribute our responses to match the relative rates of reinforcement they have produced in the past. Kahneman and Tversky proposed an alternative analysis, that we use mental short-cuts or heuristics to make choices, partly based on emotions. Kahneman later proposed two systems, an unconscious system which generates intuitions, and a conscious system that may then modify them.