Habituation, sensitization, and perceptual learning are forms of learning that do not necessarily require large expenditures of effort. Think, for example, of how much a couch potato can learn without ever needing to get up from his couch.
He can quickly detect which commercials he’s seen a thousand times and distin-guish the television characters he likes from those he despises. Similarly, many
of the laboratory experiments described above require little effort on the part of the learners involved. Neither rats nor babies need to do much of anything to habituate their responses to a tone.
In many situations, however—particularly in discrimination training—
individuals may be far more active, exerting control over the kinds of stimuli they repeatedly experience. Animals rarely just sit around waiting for something to hap-pen. Instead, they spend much of their time traveling, searching, and exploring the world around them and thus play a decisive role in determining the kinds of stimuli they are repeatedly exposed to, as well as the frequency of exposure. And even the most extreme couch potatoes usually have a remote control device nearby so that they can scan for what they want to watch next. In short, humans’ and other ani-mals’ actions are a major factor in determining the events they experience repeat-edly. This in turn affects what the individuals learn about, what they remember, and how long the memories last.
Somewhat ironically, relatively few researchers are actively exploring the role that active exploring plays in learning about repeated events, but one area where this issue has been considered in some detail is in studies of how individuals find their way around.
Spatial Learning
Spatial learning—the acquisition of information about one’s surroundings—
can be accomplished in different ways. In one of the earliest laboratory studies of exploratory spatial learning, Edward Tolman, working with C. H. Honzik, placed rats in a complex maze (Figure 3.6a) and trained them to make their way to a particular location in it—the food box—to be rewarded with a bit of food (Tolman & Honzik, 1930). These trained rats learned to run to the food box with fewer and fewer errors (wrong turns) as the days went by (Figure 3.6b).
Rats in a second group were simply placed in the maze for the first 10 days of the study and allowed to explore. If they happened into the food box, they received no food but were removed from the maze. On the eleventh day, these rats started getting food every time they entered the food box. As Figure 3.6b shows, these exploration-first rats also learned to run to the food box to get
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Figure 3.6 Learning by exploration in rats (a) Tolman placed rats in the start box of a complex maze. (b) Rats rewarded with food every time they reached the food box learned gradually to run to the food box. Other rats (the exposure-first rats) were simply placed in the maze and allowed to explore, with no food reward.
On the 11th day, these rats began receiving rewards and immediately learned to run to the box for food.
(Adapted from Tolman and Honzik, 1930.)
Will & Deni McIntyre/Getty Images
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93their food—and they learned this task so well that their performance quickly surpassed that of the rats who’d been training on the task all along! Tolman and Honzik concluded that both groups of rats had learned about the location of the food box. One group had learned how to get to the food box through explicit training, and the other group learned what the maze was like by exploring it.
This is yet another example of latent learning, because until food was placed in the food box, there was little evidence that the explorer rats knew how to get there quickly.
What were the rats learning? Perhaps they were learning a sequence of turns that they could perform to get to certain spots: turn right from the start box, then left, and so on. Such learning does occur, but it isn’t enough to account for everything the rats did in the maze, because a rat could be placed in a new start position and still find its way to the goal. Rats also appear to use visual cues to determine their location in such mazes. For example, a rat in a labora-tory maze may use the sight of a window or a wall decoration visible over the edges of the maze to orient itself. As long as these cues are in sight, the rat may learn to navigate from any starting point in the maze, although if the cues are then moved around, the rat may get temporarily confused (we describe such an experiment later in the chapter). In fact, rats can learn many things while explor-ing a maze; as a result, spatial tasks have played a major role in studies of many different kinds of learning and memory, including studies of operant condition-ing (Chapter 5), memories for events (Chapter 7), skill memories (Chapter 8), and working memory (Chapter 9). Exploration is important in all of these tasks, because a rat that refuses to explore a maze will learn very little about its spatial organization.
Animals in the wild also sometimes navigate based on visual cues they have learned through exploration. In a classic study, Niko Tinbergen studied wasps’
ability to locate their home nest. Certain species of wasps and bees engage in orientation flights before leaving their hives or burrows to look for food; during these orientation flights, they circle their home base. In one study, Tinbergen and William Kruyt laid a circle of pinecones around a wasp burrow while the wasps were inside (Tinbergen & Kruyt, 1972). The experimenters left the pine-cone circle intact for several orientation flights—long enough for the wasps to get used to these landmarks (Figure 3.7a). Then, while a wasp was away on a foraging trip, the experimenters moved the circle of pinecones away from the burrow (Figure 3.7b). When the wasp returned, it repeatedly searched for its burrow within the ring of pinecones.
Tinbergen and Kruyt concluded that when wasps leave home to forage, they use the orientation flight to collect visual information about landmarks that will later help them locate the burrow. If these landmarks are repositioned while the wasp is away, the wasp will search for the burrow based on the landmarks, revealing that it has learned about the spatial relationship between the burrow and surrounding landmarks. Just like Tolman’s rats, the wasps learn about the spatial properties of their environments through exploration. Much of this learning is latent and does not become evident until a subsequent test challenges the animal to reveal what it has learned. As illustrated in Figure 3.7, wasps often make several passes over the nest before departing. After multiple trips, a wasp will have repeatedly experienced the visual cues surrounding its nest. Such repeated events could lead to habituation, sensitization, perceptual learning, or other forms of learning. In this sort of naturalistic experiment, there is no way to know exactly what a wasp is learning from these repeated events. The follow-ing section describes more controlled studies that are helpfollow-ing researchers get a better handle on what is learned about repeated events during exploration.
Novel Object Recognition
Earlier we noted that when a novel stimulus appears after repeated presenta-tions of a familiar stimulus, babies show a strong orienting response to the new stimulus (because habituation is stimulus-specific). A similar phenomenon can be seen in exploratory behavior. In the novel object recognition task, people, monkeys, or rodents are first acclimated to the context of the experiment (the room or box where the tests will be given) by being allowed to freely explore it.
Next, two identical objects or pictures are briefly presented within the experi-mental setting. After a variable delay, one of these stimuli is presented again, but this time paired with a new object or picture. Generally, individuals will spend about twice as much time examining the novel object as they will inspecting the familiar one. From this difference, researchers can infer that the individual rec-ognizes the previously experienced object as one it has investigated before—that is, the repeated stimulus is perceived as familiar. Not all animals are so eager to investigate novel objects, however. Some actively avoid them, a phenomenon known as neophobia. For example, when dolphin trainers want to teach a dolphin to use an object, they often spend several sessions rewarding the dolphin for simply not bolting when the new object is brought near them (many dolphins are neophobic). In this case, the dolphin’s fear response provides evidence that it does not recognize an object.
Psychologists have used variants of the novel object recognition task to determine what kinds of information individuals remember about objects and places they have inspected in the past, such as an object’s position, observable properties, and the circumstances under which it was observed. This task is also useful for investigating the resilience of memories formed through observations or exploration. The perception of familiarity is a fundamental component of recognition memory. William James (1890) described memory in general as
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(b) Nest Figure 3.7 Use of
land-marks by wasps (a) Tinbergen and Kruyt placed pinecones around a wasps’ burrow (an underground nest) to provide visual information about the burrow’s location. When leaving home, wasps take orienta-tion flights, during which they seem to note local landmarks (such as the pinecones) that will help them return. (b) When the circle of pinecones was moved to flat ground near the nest, the returning wasps searched for the burrow inside the circle of pinecones.
(Adapted from Tinbergen and Kruyt, 1972.)
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95“the knowledge of an event, or fact, of which meantime we have not been think-ing, with the additional consciousness that we have thought or experienced it before”
[italicized as in James, 1890]. Familiarity can be defined as the perception of similarity that occurs when an event is repeated—it is, in James’s words, a “sense of sameness.” Although it is difficult to know what this feeling of sameness is like for a rat or monkey, we can conclude from tasks such as the novel object recognition task that rats and monkeys discriminate different levels of familiar-ity, just as they distinguish different intensities of sound or shades of gray. In the past decade, memory researchers have intensively investigated how individuals judge familiarity, how this capacity relates to other memory abilities, and what brain mechanisms contribute to familiarity judgments (Eichenbaum, Yonelinas,
& Ranganath, 2007). Consequently, a learning phenomenon that scientists once used mainly to distinguish habituation from fatigue has transformed into a cor-nerstone of modern memory research.
Priming
Prior exposure to a stimulus can lead to a sense of familiarity the next time that stimulus is observed. Even when it does not lead to a sense of familiarity, it can affect the individual’s response to the stimulus (or related stimuli) the next time the stimulus is observed; this latter effect is called priming. For example, prim-ing in humans is often studied usprim-ing a word-stem completion task, in which a person is given a list of word stems (MOT__, SUP__, and such) and asked to fill in the blank with the first word that comes to mind. People generally fill in the blanks to form common English words (MOTEL or MOTOR, SUPPOSE or SUPPER). But if the people were previously exposed to a list of words con-taining those stems (MOTH, SUPREME, and so on), then they are much more likely to fill in the blanks to form words that were present in that list, even if they don’t consciously remember having previously seen the words on the list (Graf, Squire, & Mandler, 1984). When they complete the word stem with a previously experienced word, they do not recognize the word as one they recently saw, and yet the prior experience clearly affects their word choice. Such effects are con-sistent with the findings from sexual habituation studies described previously in
“Learning and Memory in Everyday Life” on page 80 that prior exposure can affect a person’s behavior and perception even if the person is not conscious of the previous exposure or its effects or both.
Nonhuman animals show priming, too. For example, blue jays like to eat moths, and moths have evolved coloration patterns that help them blend into the background where they alight. Therefore, blue jays
have to be very good at detecting subtle differences in visual patterns that distinguish a tasty meal from a patch of tree bark. Researchers studied this detection ability by training blue jays to look at pictures on a screen (Figure 3.8a) and
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Figure 3.8 Priming in blue jays (a) Virtual moths on a gray background are more detectable than the same moths on speckled backgrounds. Higher numbers indi-cate more cryptic backgrounds. (b) Blue jays learn to peck on screens when they detect a virtual moth and to peck on a green key when they detect no moths. (c) When a moth is similar to a recently detected moth, blue jays are better able to detect the moth, suggest-ing that prior exposure facilitates recognition. In other words, prim-ing has occurred.
(Adapted from Bond and Kamil, 1999.)
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to peck at the screen to signal “there’s a moth here” or at a key to signal “no moth” (Figure 3.8b). The birds did very well, but they were quicker and more accurate at detecting a particular species of moth if they had recently detected other members of that species, as shown in Figure 3.8c (Bond & Kamil, 1999).
In other words, recent observations of one kind of moth primed the jays’ abilities to recognize similar moths later.
Interim Summary
■ Habituation is learning that leads to a decrease in the strength or frequency of a behavior after repeated exposure to the stimulus that produces the behavior. A response that has habituated can be renewed (dishabituated) by a novel stimulus.
■ In sensitization, exposure to an arousing stimulus causes a heightened response to any stimuli that follow.
■ Dual process theory proposes that changes in behavioral responses after repeated exposures to a stimulus reflect the combined effects of habituation and sensitization processes.
■ Perceptual learning occurs when repeated experiences with a set of stimuli improve the organism’s ability to distinguish those stimuli.
■ In mere exposure learning (a kind of latent learning), simply being exposed to stimuli results in perceptual learning.
■ Perceptual learning can also occur when an organism learns to distinguish stimuli by repeatedly practicing at making fine distinctions.
■ Comparator models and differentiation theory suggest that habituation depends on perceptual learning. Differentiation theory explains percep-tual learning as resulting from new details being added to existing stimulus representations.
■ Spatial learning often involves latent learning about features of the environment (including encountered objects) through exploration.
■ Priming is a phenomenon in which prior exposure to a stimulus, even without awareness of the exposure, affects the organism’s response to that stimulus later.
3.2 Brain Substrates
The discussion above considered several ways in which experiences with repeated events can lead to learning. In some cases, gradual changes in behavior revealed this learning, but in others the learning was latent until the right test was given.
Even in the “simple” case of habituation, learning seems to involve multiple parallel processes that can sometimes operate without any associated changes in behavior. Using only behavioral evidence, it is extremely difficult to understand how and what organisms learn from repeated events. Because researchers recog-nized this dilemma early on, there is a long history of neurophysiological stud-ies of habituation (Thompson, 2009), starting in the early 1900s with Charles Sherrington’s studies of the spinal reflex (discussed in Chapter 2). More recently, neuroimaging and electrophysiological studies have begun to shed new light on the processes underlying perceptual learning and object recognition. The abil-ity to observe how brain function and structure changes as an individual learns about repeated events has provided many new clues about the nature of these phenomena, as the following discussions will illustrate.
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97Dogs and cats are natural antagonists, as any dog or cat owner knows. Some of the earliest brain studies on habituation, using dogs and cats as subjects, seemed to bear out the view that these animals are fundamentally antitheti-cal. Ivan Pavlov, for example, found that when a dog’s cortex was removed, the dog no longer showed habituation to auditory stimuli: the dog would instead continue to show orienting responses to the sounds, even after many exposures (Pavlov, 1927). Such findings led researchers to suggest that the cortex was criti-cal for habituation and that it actively suppressed reflexive orienting responses to stimuli perceived as familiar (Sokolov, 1963). The data from cats, however, seemed completely contradictory. Cats that had their brain disconnected from their spinal cord, called spinal cats, still showed habituation to tactile stimulation (Thompson & Spencer, 1966). This seemed to prove that the spinal cord by itself contained all the neural machinery necessary for habituation; the cortex—
and indeed the rest of the brain—wasn’t needed. The cat data were consistent with the finding that many other organisms known to habituate, including roaches, protozoa, and numerous other invertebrates, don’t have any cortex.
How to reconcile the dog data and the cat data? For one thing, the animals in these early studies were learning about different kinds of stimuli. Whether cortical processing is involved in habituation likely depends on the kinds of stimuli that are being repeated, where they are normally processed, and where memories of the stimuli are formed. One way to avoid these complications is to study habituation not with mammals, such as cats and dogs, but with smaller-brained animals such as everyone’s favorite—the sea slug.