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1 Behavior Mind and Brain
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1 B- e Pavlov , Mind, and Brain From the beginnings of scientific inquiry, researchers have tried to understand the workings of the mind and its relationship to behavior. In modern terms, scientists seek to answer such questions as: How does an individual manage to see coherent objects in changing patches of multicolored light or to hear speech and music in bursts of sound varying in loudness and pitch? How do people remember, even imperfectly, the vast storehouse of factual and functional information that each of us carries about? How do infants and other nonverbal creatures think, and what are their thoughts like? How does an individual learn new ideas, create concepts, organize his or her knowledge, and act upon what he or she knows? Until about 100 years ago, these and similar questions led mainly to spec- ulation, to sophisticated but untestable guesses about the nature of the mind and its function in behavior. Many scientists thought that this confinement to speculation would always be the case, on the presumption that mental life, unlike the world of objects, is not directly observable and so is not amenable to systematic, scientific study. But during the second half of the nineteenth century, experimental and close observational approaches to such questions began to appear. Some of the first work involved the study of sensory processes 7
8 / The Behavioral and Social Sciences that underlie organic sensitivity to different physical stimuli, rigorous obser- vations about how behavior is shaped by experience, and the relation of ob- servable behaviors to certain brain regions and neural events. Both theory and method have since advanced at an accelerating pace, with extensive revisions of earlier questions to make them more tractable and to take advantage of the growing linkages between knowledge about behavior, the mind, and the brain. Instead of asking only how best to measure the intelligence of people, researchers now ask about the nature of intelligent ac- tion, whether exhibited by humans, animals, computers, or robots. In addition to seeking laws that directly relate external stimuli to behavioral responses, researchers now attempt to unravel the basic processing that the brain must carry out in order to generate behavior and to simulate that processing on computers to formalize and test theories. These are the new questionswith their extensions into the details of visual and auditory processing, memory formation and retrieval, language, cognition, and action that drive the re- search investigations highlighted in this chapter. SEEING AND HEARING As you look around, you see a variety of objects at various distances, some still and others moving, some transparent and some densely colored, some partially obscured and some not. All is perfectly ordinary and seen without effort if the light is adequate. Your cat or dog sees these things, too, although somewhat differently from the way you do. And so does the fly that evades your swat. And when you listen to a musical recording, you have little trouble hearing the separate instruments. If someone speaks while you are listening to the music, you have no difficulty in understanding the words, unless the music is very loud or you suffer from a certain form of hearing loss that is common in older males. It is all so commonplace but no one yet knows exactly how the brain does any of these things. No one yet knows enough to program a computer to pick out a wide range of objects from a scene, to isolate a violin in an orchestral passage, or to separate speech from noise and to partition it into words. Ena- bling machines to do these things would surely affect the way people live as much as the telephone, the thermostat, or the radar have done. And it is clear these tasks can be done because the human brain does them, continuously and apparently effortlessly. One approach to studying how these tasks are carried out is to work with computers and sensing devices, without much regard for how the tasks are done in the brain. Another approach is to focus directly on unraveling nature's way of doing them. These tasks may be very complex. Or they may be simple but involve prin- ciples that scientists do not yet understand. For example, between one-quarter
Behavior, Mind, and Brain / 9 and two-fifths of the total cortex of the human brain is devoted to vision, suggesting that it is one of the most complex brain functions. However, abilities somewhat similar to human vision are exhibited by animal brains far more modest. For example, pigeons trained to identify the occurrence of trees (in contrast to bushes or other plants) in color slides- whether alone or in a forest, in whole or in part, leafy or bare are then able to identify trees as accurately as people can, in slides they have not previously seen. Pigeons can also be trained to recognize a particular person in slides of individuals or crowds. Yet, with similar training, pigeons cannot identify simple line drawings, such as cartoon characters. The difficult is easy and the easy difficult for that tiny brain, or so it seems. Hearing similarly involves complexity and simplicity. The only physical event on which hearing is based is the variation of air pressure at the ears. A plot of the sound pressure generated by a person saying "science" in a quiet room is completely different from the plot of that same word said by the same person against a background of white noise, such as cocktail party chatter. A person has no difficulty hearing the message in the noise, although the physical sound patterns are quite different. The ability of the human ear and brain to recognize the word in the noise is vastly superior to that of any machine. Understanding such abilities is the current focus of research on perception. This research includes innovative theoretical work and sophisticated experi- ments with animals, and it is increasingly able to use computers to develop theoretical models and simulate experimental tests. The research involves psy- chologists, biologists, physiologists, physicians, graphic artists, physicists, en- gineers, and computer scientists. The work is highly interactive: for example, behavioral analyses of sensory and perceptual processes provide evidence for functional distinctions that can then be sought in the workings of the brain. Another example comes from theoretical advances in the development of re- cursive computer models that capture the simultaneous use of multiple sources of information. These are often called activation models because each piece of information that plays a part in a particular mental process is viewed as an active influence on the direction of the process. These activation models are being applied to previously intractable problems in research on human and . . . an~ma . vision. Work with various species of animals commonly used in laboratory exper- iments is playing an important role in learning how brains accomplish the tasks of seeing and hearing. By recording the electrical behavior of single nerve cells and studying the wiring diagram of how these cells are arranged in the brain, researchers are beginning to understand the architecture of perceptual systems and how they process information. In addition to monkeys, animals such as cats, rabbits, goldfish, and barn owls have yielded valuable information about sensory systems. Which species is appropriate depends on the particular ques-
10 / The Behavioral and Social Sciences
Behavior, Mind, and Brain / 11 tion being asked and the similarity of that aspect of its perceptual system to the human system. Visual Analyzers The retina of the eye really a bit of exposed brain is a regular mosaic of five different layers of nerve cells whose spatial arrangement affects the nature of vision. Aided by recent technical advances in electronics, researchers have shown that in one early stage of visual processing, millions of small groups of neurons in the eye and the rest of the brain work as parallel microprocessors or analyzers. Each analyzer responds preferentially to stimulus components within a narrow range of size and orientation; they decompose the scene into a vast number of overlapping components. Precise quantitative models based on such analyzers can be explored by complex computer simulations and can now explain how the human eye and brain detect and identify low-contrast visual patterns, such as nighttime shadows. Some current work suggests that the brain may be able to rapidly select and regroup the analyzers, depending on what is being perceived. One application of such models is to evaluate, at the design stage, the relative clarity and efficiency of a variety of visual displays: flight simulators, video HEARING How do the senses, such as hearing, work? How does a per- son's auditory system identify a single voice in a buzz of conversation and pick words out of a vocal stream? The figures on the facing page show the sound pressure generated by a human male voice saying the word "science." They are digitized plots of the amplitude of a sound wave over time; the total time is 0.85 seconds; the amplitude is sampled at a rate of 10,000 observations per second. In the top figure, the person spoke in the stillness of a soundproof cham- ber. In the bottom figure, he spoke while his voice was masked by noise that simulated a roomful of people talking, such as would occur at a cocktail party. Neither the human eye nor any known form of sound filter or computer analysis can detect the wave form of the top figure in the bottom figure. That is, they cannot extract the vocal wave form from the noise. But a normal listener has no trouble hearing and understanding the word through the noise. How the human ear and brain perform the analysis needed to rec- ognize the word in the noise is a fascinating and complicated scientific problem.
12 / The Behavioral and Social Sciences terminals, warning lights, and information signs. Another application is image augmentation. The inherent inadequacies of electrical and optical imaging sys- tems such as blurring due to the atmosphere can be compensated for by computers. Information that is particularly useful to human perception can be improved at the expense of less useful information. These applications are aimed at speeding up such tasks as reading x-ray plates and satellite recon- naissance displays, tracing circuit diagrams, and following blueprints and maps, which are done slowly and are error-prone without augmentation. Another application in the future will be the possibility of more efficient transmission of visual images over telephone lines. Researchers have discovered that some visual tasks are so complex that humans, some primates, and possibly many other animal species use special- purpose brain areas to solve them efficiently. For example, the human ability to recognize and discriminate readily among a seemingly endless variety of faces is now known to make use of certain neural circuits in the right-posterior cerebral hemisphere. Facial recognition may be different from the recognition of most other kinds of objects in the world, but it may be that other forms of expertise in pattern recognition hinge at least in part on engaging those neural circuits. Researchers are beginning to explore in detail the extent and nature of such special-purpose systems in the human and animal brain and their relation to perception. Color Constancy An outstanding example of a very important special feature of visual per- ception is color constancy: color relations between objects in a scene seem relatively invariant to the eye, independent of the light playing on the scene. A blue shirt looks blue whether seen in sunlight or in a dimly lit restaurant. Yet this invariance cannot be replicated by color photographic media. Recently, some investigators have proposed a theory about how the eye and brain may separate the inherent color relations among objects from the light impinging on them. Certain newly defined mathematical algorithms, if carried out simultaneously over the entire visual field, presumably by millions of visual analyzers, have been shown in theory to be able to separate the inherent colors of objects from incident lighting. This theoretical model assumes certain math- ematical conditions that correspond to qualities of colors, of light, and of the high-level "programming" of the brain. Large-scale computations are now being carried out to test and refine the model and to find ways to simulate it in real time with new computer architectures. If, as the theory suggests, this decomposition works efficiently and if, as is anticipated, the electro-optical technology for recording a visual scene digitally can be made sufficiently compact, a new form of photography could result. Instead of the various "speeds" of film suited to different lighting conditions,
Behavior, Mind, and Brain / 13 one would need only one type of photosensitive medium that could be used under any circumstances. The "developing" process would then decompose what is inherent in the scene from the lighting that happened to exist at the time of the photograph. With such a process, one could display or print the picture with whatever lighting conditions one wanted. The developing and printing processes, carried out on a computer, would be analogous to what the brain does all the time. The ability to adjust lighting as if from the mind's eye would mean unprecedented expansion of the capabilities for the scientific study of vision and for applications in graphic arts, industrial design, and computer vision. Depth and Motion That the world is spatially three-dimensional while the retina is spatially two-dimensional creates inherent visual ambiguities. The eye cannot directly capture motion perpendicular to it; the eye and the rest of the brain must infer depth and motion from ambiguous clues. Resolving these ambiguities, which is usually essential for accurate vision, is possible because of certain constraints that occur in natural scenes concerning shading, motion, texture, and so on. Recent results of behavioral experiments with humans and animals, which have inspired corroborating neurophysiological experiments, reveal that higher-level neural analyzers of motion in visual images are sensitive to the global direction of a pattern's motion, even when parts of the pattern are moving in other directions. These analyzers give rise to moving optical illusions, such as rigid objects that are perceived as flexible and vice versa. Another example is the illusion that very large objects are moving more slowly than they actually are. Landing or taking off, a jumbo jetliner appears to be flying more slowly, by a sizable factor, than a small, executive jet, when in fact their speeds are very similar. This kind of size-speed illusion is believed to be the underlying cause of many railroad-crossing accidents when motorists drastically underestimate the speed of an approaching train. These illusions, which are difficult and in some cases virtually impossible to study experimentally except with modern computer-graphic technology, imply that immense distortion in visual displays may be tolerated or even go unnoticed by both humans and animals. Perceiving Objects The process by which visual analysis fills in a big picture from a collection of details means that mere fragments of objects suffice in normally cluttered scenes to permit observers to produce coherent, conceptually appropriate per- ceptions. Adults make use of several experimentally confirmed theoretical prin- ciples to do this, such as assuming that objects in a scene do not share bound- aries. People also tend to see correlated movement of disconnected parts in natural scenes as a single moving object partially masked by another object. This latter principle is apparently a deep-seated tendency and has even been
14 / The Behavioral and Social Sciences demonstrated in very young infants. Increasing knowledge about visual per- ception can be expected to improve the design of factory robots that must make complex identifications of objects in order to carry out their function without selecting the wrong object or inadvertently hurting someone. Temporal Auditory Patterns Hearing problems having to do with space (for example, distance and lo- calization) are very important in the design of sound equipment and audito- riums and have long been studied. Much of the current focus of research on auditory perception, however, concerns complex patterns of sound stimuli varying in time, such as speech and music. Auditory signals can now be de- signed and stimulated quite precisely by a computer driving a digital-to-analog signal coverter, and these artificial sound patterns are used to study specific aspects of the hearing process. One type of study measures a listener's ability to discriminate changes in the intensity of one of several tones that are played simultaneously. Initially, the ability to sense a change in intensity within a complex of other tones is far less than when a single tone is played by itself. But with practice in listening to complex tones repeated with little variation, the ability to recognize the vari- ations when they do occur becomes very good. Studies are now under way to see whether practice in listening to complex sound patterns is characteristic of how an infant reams to identify the particular phonemic differences that char- acterize its prospective language. An important area of application of research on the perception of auditory patterns (including speech recognition, described more fully below) is in the design of hearing aids. They have been greatly improved in the past decade by coupling what was known about the nature of hearing loss with modern elec- tronics. Whenever the auditory deterioration is peripheral rather than central, certain aspects of the loss, such as reduced loudness at certain frequencies, can be mitigated by appropriately altering the sound waves at the eardrum. Whether it will also prove possible to compensate for the inability to separate speech signals from background noise may depend similarly on the nature of the loss, which further research is likely to reveal. Music is the focus of much scientific research. Musical keys and scales are highly structured, and musicians, mathematicians, and philosophers have long speculated about the underlying nature of that structure. More recently, the rules of counterpoint and orchestration are being explained, not as arbitrary requirements of particular musical styles, but as selective adaptations to basic tendencies of the human auditory system to group sounds in certain ways as a step in auditory pattern recognition. Researchers some time ago postulated that a set of ratios corresponding to a helical geometric structure underlies tonal perception. Recently, far more systematic studies, using trained musicians as
Behavior, Mind, and Brain / IS respondents and multidimensional scaling methods (discussed in Chapter 5) to analyze the results, have led to a modified understanding of the geometric relations implicit in tonal perception; they appear to be conical rather than helical configurations. Stimulated by the success of linguists in analyzing lan- guage as a rule-governed system, behavioral researchers working with musi- cians have also successfully begun to define the deeply embedded rules that become internalized in the course of growing up in a musical culture, and they have demonstrated how such deep rule structures strongly affect listeners' perception and memory of what is heard. MEMORY Most people can readily kind their way around a once frequented neighbor- hood, improve a sporting skill with practice, or recall an old story. These deeds are possible because the capacity for memory storage is vast; indeed, virtually everything discussed in this chapter depends critically on humans having very large, readily accessible banks of organized information in the brain. Not only is the capacity large, but also much of its use is automatic: learning and memory often occur incidentally, with little special effort. Yet for some people memory failure can become an acute problem. In certain diseases, such as Alzheimer's, the ability to learn and remember is drastically impaired, and life becomes a series of unconnected moments. Some questions about memory are of long standing: How are memories organized? How does the brain code, store, and retrieve them? What are the computations and processes involved? What happens when the capacity for memory becomes impaired? How can memories be improved? For both these questions and newer ones, a whole new approach to the study of memory derives from the development of computers. However, although much has been learned from the way information is stored in computational systems, the analogy between computer memory and human memory is imperfect in many .~ secant ways. In the past 20 years, an interdisciplinary revolution has occurred in under- standing the organization of learning and memory and their biological foun- dations. Behavioral studies in animals and humans are characterizing the cat- egories and properties of learning and memory; research on human memory and the brain is identifying the neuronal systems that serve different categories of memory; memory trace circuits in the mammalian brain are being defined and localized in animal models; researchers are beginning to understand the neuronal, neurochemical, molecular, and biophysical substrates of memory in both invertebrates and vertebrates; and theoretical mathematical analysis of basic associative learning and of neuronal networks is proceeding rapidly. Better mathematical and computational modeling of elaborate memory pro-
16 / The Behavioral and Social Sciences cesses, carried out to simulate aspects of specific brain architecture, has become feasible because of the "computer revolution." The newest phase of that revo- lution the availability of massive, parallel computer architectures, in which many specialized unit devices process pieces of information simultaneously, seemingly analogous to the way in which neural memories operate- will almost certainly facilitate future work on memory. Types of Memory Of the many questions about memory, one of the most fundamental concerns the types or varieties of memory. In recent years, both psychological and neu- robiological work have suggested that memory is dissociated into processes or systems that are fundamentally different. For example, amnesic patients with brain injury or disease exhibit severe inabilities to recall and recognize recent events and have difficulty learning new facts or other kinds of information. But, these patients possess some relatively intact reaming and memory abilities: for example, on tasks such as manual-dexterity learning trials, they perform as well as healthy and uninjured people, even though they may have no conscious memory of having performed the task before. This evidence that some kinds of reaming can proceed normally even when the brain structures that mediate conscious remembering are damaged supports the general proposition that there are distinct, dissociated types of memory. Analysis of recall performance shows that memory is an active process of seeking and reconstructing information, not a passive recording and repro- ducing of events. Thus, expectations of what things should look like or the way events should happen influence what people notice and remember. For example, after listening to a story presented in jumbled order, people still tend to remember it as being told in proper sequence, following certain widely accepted schemes for what constitutes a story. People also tend to pay little attention to the details of routine situations; consequently, people often re- member that the most probable things happened even when they did not. This phenomenon has been demonstrated clearly in the context of eyewitness court testimony. And because people tend to remember events and places in terms of expectations and general knowledge of the world, experiments have shown that memory of an event can be modified or distorted by the manner in which questions about the event are posed. Such experimental findings have impor- tant theoretical implications for understanding the formal structure of memory, and they have practical implications for legal proceedings (see "Small Groups and Behavior" in Chapter 23. Behavioral studies in animals have also revealed certain persistent constraints on reaming and memory. Many species, ranging from invertebrates to primates, can learn very quickly to associate or connect distinctive tastes with subsequent nausea, but they are much slower to associate those tastes with prompt threats
Behavior, Mind, and Brain / 17 of pain. In contrast, certain visual and auditory signals are readily associated with pain episodes, but are not so quickly associated with subsequent nausea. These findings also support the general proposition of different types of mem- ory. Animal studies have illuminated other important aspects of natural learning. In foraging, for example, animals search efficiently among many possible food sources, using past experience to reckon the best trade-offs between relative distances (and associated caloric costs), probability of finding food, and relative nutritional quality (especially caloric content) available at alternative sites (see "Patterns of Food Consumption" in Chapter 29. Imprinting provides an example of biological adaptive mechanisms for nat- ural learning. Song learning in birds that have a species-typical song is perhaps the most striking example of biological preparedness to learn. Young birds apparently have a "song template" encoded in the brain so that they best learn the species-typical song during a critical period early in life. Some birds, like the canary, learn a new song each year. This capacity for annual song learning has recently been found to depend on an extraordinary biological mechanism. Neurons in the "song circuits" of the brain grow during a period of song learning, extending their connections to other cells and increasing the oppor- tunity for interaction among neurons, and then shrink at the end of the period. These findings may be relevant to examples of human learning that appear to operate under strong biological constraints and occur best during early years- like language learning. Brain Structure and Neurotransmitters Memory is under intense investigation at the neurobiological level as well as at the behavioral level. Recently developed techniques for inducing amnesia in nonhuman primates offer great promise for understanding the neural circuits underlying particular aspects of memory. Surgical brain lesions in monkeys, involving the hippocampus and related structures, produce the same selective impairment in memory as that which occurs in human patients who have experienced comparable cerebral damage due to head injury or stroke. Per- formance is poor in memory tests that require stimuli to be recognized as familiar or after a long delay, but skill learning is intact. This research will lead to identification of the precise set of brain structures and connections that, when damaged, causes human amnesia. At the same time, parallel work on other mammals, especially rats, will be useful in identifying the neural systems involved in acquiring and storing different kinds of memory. This work should make it possible to specify clearly what these systems' functions are and to investigate how these systems work at the cellular/neurophysiological level. Neural accounts of learning depend heavily on and benefit importantly from the highly developed study of learning at a behavioral level. Once memory
18 / The Behavioral and Social Sciences circuits are defined in invertebrate and vertebrate nervous systems, their per- formance capabilities have to be measured. How neural circuits are organized is a mathematical problem of enormous complexity that can only be solved by mathematical and computational modeling. One such complex network model, an approximation to visual cortex, was shown a few years ago to be compu- tationally in agreement with a large number of experimental results. Recent, unexpectedly rapid progress has been made in identifying essential memory trace circuits that code, store, and retrieve associative memory in the brains of birds and mammals. The kinds of memory under study include the reaming of discrete, adaptive behavioral responses and the conditioning of involuntary responses. For one well-studied type of associative learning, clas- sical conditioning of the eye-blink response, the essential neural circuitry re- quired for the reflex has been partly identified. Moreover, locations have been found within that circuitry where memory traces are likely to be stored when conditioning of the reflex occurs. In this case, there is growing evidence that at least one site where memory traces are stored is the cerebellum, and neu- rophysiological research is being carried out on the interpositus nucleus where changes related to learning can be studied within a volume of one cubic mil- limeter. Most of this work involves pigeons, rabbits, and baboons. Other active research is clarifying the role that the brain's neurotransmitters and neuropeptides play in modulating memory. Studies with drugs and ex- perimental animals show that memory can be amplified or diminished by specific pharmacological treatments. Full identification of the core-memory circuits for basic associative learning in mammals is very likely in the next few years. As these circuits are identified and the storage sites located, scientists can make substantial progress in analyzing the detailed storage mechanisms, particularly those underlying long-term and permanent memory. These basic cellular and molecular mechanisms are now the focus of great interest and excitement. For example, in a well-studied invertebrate, the sea hare, simple, biologically universal forms of learning like habituation and sensitization are being related to changes in the readiness of particular neurons to release a transmitter. From work in both invertebrate and mammalian preparations, the general picture emerging is that learning involves the reduction of one or more kinds of potassium conductance through the membranes of nerve cells. Such a reduction in ion conductance may constitute an essential step in how nerve cells change in response to input, thereby profoundly altering the way those cells receive and transmit information. This process is thought to be brought about by phosphorylation of specific substrate proteins, mediated by "second messengers," which can give rise to long-lasting neuronal changes. Second messengers are attractive molecules because they themselves can serve as the agent for short-term memory, while their intracellular effects can include the genomic regulation involved in the cellular changes that occur in the foundation of long-term memory.
Behavior, Mind, and Brain / 19 The cellular and molecular mechanisms emerging as important in animal- model systems appear to be recurrent in the evolution of species, offering the promise that these models may be of general significance to the question of how human memory is formed and retrieved, contributing ultimately to greater understanding about the functioning of the human mind and brain. Work is proceeding at all levels from abstract mathematics to exploration of molecular and biophysical substrates. Continuing advances in such work may lead to significant applications in the treatment of memory disorders, such as those associated with amnesia, seizures, stroke, and Alzheimer's disease. COGNITION AND ACTION New questions about the mind have emerged in this century: How do people acquire knowledge, use it in reasoning, and turn it into practical action? How do human beings and other animals construct mental categories in a world of particular objects and episodes? How do people manipulate images in their minds, train their fingers to perform delicate handiwork, or judge probabilities and decide which risks to take? Recent discoveries regarding these mysteries have resulted from new sci- entific methods for observing, describing, replicating, and analyzing cognitive structures and processes. To study human infant abilities, for example, re- searchers exploit the funding that infants look preferentially at novel objects and events, work at sucking or turn their heads to hear a sound or bring a picture into focus, and give characteristic responses to changes in the environ- ment. For studies of adult attention, researchers take advantage of small but consistent differences in the time-course of mental events. To map the rules that guide behavior, researchers rely on the human ability to detect errors in rule application. Neuroscience data suggest that complex behavior and mental activity emerge from simultaneous and parallel contributions of many specialized component parts. One possibility is that the basic processing units are neurological "col- umns" or "modules," each containing 1,000 or fewer nerve cells; if this is true, then there are more than 10 million such functional units in the human brain. A major challenge for future study is to identify more fully the functional units of organization in the cortex, the most highly evolved and complex part of the primate brain. This effort, which is already under way, involves neuroanatomy and physiology together with the analysis of cognition and perception. Studies of complex intellectual task management take advantage of a wide variety of methods, such as computer simulations. With the increasing avail- ability of powerful computers oriented toward symbolic processing, theories can be tested in the form of programs that simulate the hypothetical mental activities involved in understanding and reasoning tasks. Similarly, mathe-
20 / The Behavioral and Social Sciences matical, logical, and other formal models serve to make hypotheses about mental structures explicit and precise. Empirical methods for testing such hy- potheses use detailed observations, including protocols that have individuals think aloud while they work, complex tracking systems that record and analyze eye fixations while a person is examining visual information, and repeated runs of computer models to see how well they perform in processing a variety of materials, such as texts to be analyzed or symptoms to be diagnosed. Early Cognitive Development and Learning Studies of early human development give some of the strongest examples of how new observational methods have led to new knowledge. The once-com- mon belief that the experiential world of an infant is mostly sensory chaos has been displaced as evidence has accumulated showing that infants are especially sensitive to those subtle distinctions among oral sounds that are important in learning to speak, to cues of visual depth and distance, and to other precursors of complex perception. The techniques used to show these facts make use of an infant's innate curiosity and tendency to prefer novel sights and sounds over very familiar ones. Experiments built around these techniques are now able to investigate infants' ability to form abstract concepts. For example, infants as young as 6 months are able to match the number of items they see in a display with the number of drumbeats they hear. In a series of studies, infants were sat either on their mother's lap or in an infant seat and shown pairs of slides, one dis- playing three objects, the other two objects. The pictures of familiar objects used included a comb, apple, scissors, crayon, and book. The objects in the slides varied from trial to trial, and on each trial the infants heard either two or three drumbeats emanating from a hidden, centrally placed speaker. In one set of experiments, infants consistently tended to look at the visual display in which the number of items matched the number of drumbeats played. In experiments similar in design but with significant changes in conditions such as exposure time, infants consistently preferred to look at the display that differed in number from the number of sounds they heard on a trial. Thus, infants can respond to numerical information, in terms of whether pairs of stimuli are equal or different in number. How they do this and whether they use adultlike numerical processes is the subject of much current research. This line of study at first evolved an elegant theory that young children progress through relatively well-defined stages of understanding in which fun- damental structures not present at one stage come into being virtually discon- tinuously at a later age. Over time, the theory has changed as new evidence has led to new hypotheses and more sensitive methods to testing them have been developed. Evidence now exists that even 3-year-old children can use general principles to understand the structure of stories, organize learning
Behavior, Mind, and Brain / 21 about cause and effect, represent numbers and space, analyze and reason about event sequences, and rapidly acquire the meanings of words. These findings have provided a basis for fundamental reconceptualizations of early childhood learning, which now appears to be enabled and constrained by available mental structures and fostered by a pronounced tendency of the young to seek out particular environments that challenge and nourish cognitive development. Instead of leaps across cognitive gaps, development involves the gradual ac- cumulation of insights and adjustments that cumulatively constitute profound increases in cognitive capability. Current efforts to spell out the mechanisms of such learning benefit from detailed descriptions of development within par- ticular domains of knowledge as well as formal innovations (for example, the- ories describing the conditions that make a language learnable), computer simulations of change, and the investigation of social-environmental conditions that foster or interfere with self-motivated learning, knowledge transfer, and problem solving. (The case of language learning is discussed later in this chap- ter.) Categorical Knowledge and Representation One aspect of development is the creation of categorical knowledge con- cepts and relations among them which is the preeminent form of mental framework for interpreting and understanding experience. How are categorical ideas represented in human knowledge? A traditional view holds that categories are defined by a list of necessary and sufficient properties that an object must have in order to be a member. Scientific categories (for example, mammal) often have this characteristic. However, categories in natural language generally do not. This is true of relatively concrete ideas such as dogs, trees, and chairs; more so for somewhat more abstract categories such as animals, fruit, and furniture; and completely for thoroughly abstract concepts such as freedom, happiness, and justice. Empirical studies point to the possibility that categorical ideas are stored in several different ways. Some appear to be hierarchically organized, allowing people to infer that whatever is true of a superordinate concept is true of those of a subordinate level. For example, whatever an "achida" may be, if it is an animal, it must eat and breathe. Other categories are partly organized around spatial relationships: in order to form a forest, trees must be physically close to each other. Still others are represented in memory as a collection of exem- plars, and a new object can be classed as belonging or not belonging to the category according to how well its features match those of remembered ex- amples. People sometimes also form a prototype or a schematic representation by a process of abstraction, and a new object is classified by judging its similarity to the prototype or its goodness-of-fit into the schema. A designer seeking the right "look" or a judge seeking to determine the equities in a tort case may use
22 / The Behavioral and Social Sciences GLASS I \J MUG VASE BOWL CUP as- ~ ,
Behavior, Mind, and Brain / 23 this kind of thinking. Experiments have shown that exemplar-based concepts, schematic or prototypical representations, and associations of features with conceptual categories (including probabilistic associations) are all forms of human knowledge processing, used in different combinations, in different tasks, and by different individuals. Investigators do not yet know what principles govern conceptual organization in human beings (or other animals); discov- ering those principles is a key to understanding many human mental functions, including speech perception, the organization of memory, and learning, and it will also contribute to a variety of computer applications to problem solving. Imagery Not all human knowledge consists of propositions, concepts, and principles that can be expressed verbally. Crucial components of knowledge are based on visual and auditory imagery and on patterns of motor activity. Research during the past IS years has made major advances in understanding the prop- erties of spatial cognition and action and ways in which brain structures and processes are involved in cognitive functioning in different domains. Major advances in the study of visual imagery have included identification of specific mental operations for manipulating spatial information. A landmark CATEGORIZATION How are categories defined in the mind? How do people recognize instances of categories? These questions are fundamental to understanding human thought, since reasoning about things is based on knowledge about them, and knowledge about things is largely knowledge about categories of things. Sharp boundaries between categories, based on strictly defined sets of properties that an object must have to belong to the category, occur in many scientific concepts but rarely in the world of experience that is expressed in natural language. For example, what makes something a "cup"? The evi- dence of numerous experiments in several languages is that it helps for the object to have a handle, to have sides that bow inward, to contain a beverage, to be made of ceramic, and to look slightly wider than deep. A tall glass cylinder with no handles and a flower in it is clearly not a cup, but something can still be a cup if it has straight sides, or if it lacks a handle, or if it has a flower in it as long as it has most of the other properties associated with cups. As particular properties change, an object tends to be recategorized into distinctly different categories such as glass, bowl, or vase, sometimes passing through transitional or subordinate concepts such as mug. This figure shows such categories and characteristics. From a wealth of such findings arose the idea that, in natural language, category membership is a graded function of the typicality of the properties of an object relative to other members of the category; a category is thus represented in the mind by an abstract prototype and specifically remem- bered examples, and a new object is compared to both.
24 / The Behavioral and Social Sciences demonstration based on a typical performance IQ test item established that the decision as to whether two simple figures are the same or different is based on an imaginary mental rotation of the image, much as one would physically rotate an object with one's hands. The time required for such judgments has been shown to depend approximately linearly on the angle through which a figure has to be rotated in the mind's eye. This finding is consistent with the hypothesis that such mental operations are analogous to spatial ones. Other tests about the nature of spatial reasoning draw on quite different spatial operations, such as expanding or compressing the size of an image or inferring the appearance of a scene from different perspectives. These tests are also consistent with the hypothesis of some sort of analog representation, although in each case one can also devise explanations in terms of descriptive statements about the object. Not all physical properties of objects need be encompassed by the cognitive mechanisms of imagery. Researchers are now working on such questions as: Which properties of physical transformations are preserved in mental images? What are the differences in imagery skills among individuals? How do these differences arise? It is now established that imagery is not a unitary, undiffer- entiated phenomenon but consists of distinct spatial abilities. Individuals can be good or bad at a given component of imagery ability independent of the other components. Research on imagery is leading toward an increased un- derstanding of the cognitive deficits that can result from brain damage, as well as useful characterizations of intellectual differences that may be relevant to observed male-female differences in intellectual style, science and mathematics education, and other scientific and practical questions. As the imagery example illustrates, one legacy of research on intelligence testing is the idea that there are different kinds of intelligence. Some theorists are exploring the related hypothesis that there are specialized modules of thoughts, each with separate sets of principles, not only in language but in other forms of symbolic processing,.such as in the way all living creatures learn to find their way in space. It is striking but taken for granted that people can recognize places while apparently lacking detailed information about them. For example, many people can retrace a route along city streets, knowing when to turn at a particular corner, without knowing street names or being able to recall in detail what is at that or any nearby corners. What does this mean and how does it relate to imagery? To what extent could things be scrambled or replaced and a location still be recognized as the same place? How can robots be programmed to recognize readily where they are? The problem of recognition is clearly important and most likely complicated, even though many animals seem to possess the skill. Work on this topic is pursued fruitfully by researchers at many levels of analysis, from neurophysiologists mapping the locations of these functions in the brain to psychologists, linguists, anthropologists, city planners, and ethologists describing and modeling the behaviors involved in moving efficiently and communicating efficiently about location.
Behavior, Mind, and Brain / 25 Individual Decision Making Decision making choosing among options is a central topic of research on modern life. Studies of the decision making of individuals have followed two broad, intertwining pathways- normative and descriptive. Research in a normative vein seeks to define the conditions, practices, and procedures under which decision makers can achieve some prescribed goal, such as maximizing expected utility or satisfaction, achieving economic efficiency, or securing dem- ocratic representativeness. A central line in normative research is to illuminate rational selection among alternative actions that have complex patterns of pos- sible outcomes depending in part on chance and uncertainty in the environ- ment. Research in a descriptive vein seeks to understand the mechanisms and procedures actually followed by individuals in reaching decisions, particularly when normative approach is difficult to specify or calculate. Each mode of research stimulates the other, and many assumptions, hypotheses, and findings are common to both. Normative research has traditionally been guided by a theory based, in part, on the principles of mathematical probability and, in part, on calculation of trade-offs between the values of outcomes and the probabilities of their actual occurrences. The modern development of normative decision theory began in the 1940s with the introduction of an elegant mathematical theory of games and economic behavior that laid out a rational basis for making choices among actions whose outcomes are partially determined by chance events with known probabilities of occurring. This theory reduces in practice to a rather simple numerical model for computing which alternative move in a situation has the largest average utility and should therefore be the one selected. Despite its logically compelling character, however, the theory does not seem to be fol- lowed by most people when they make individual decisions. As a result, a noteworthy line of experimental study is trying to formulate and systematically understand in what ways people depart from the normative theory. A considerable body of economic and statistical work has been built on normative decision theory, and it has proved powerful when applied to be- havior in various financial and insurance markets. But objections have been raised against applying the theory in other areas, both by decision theorists on formal grounds and by experimentalists carrying out carefully designed studies of the choices people make under well-controlled conditions. In the past 10 years, the empirical results consistently showed departures from rationality postulates, and these findings have created a new challenge for theory devel- opment. Because the empirical findings are complicated, it is as yet unclear exactly which one (or more) of the basic postulates of rationality is the principal culprit and needs to be modified. Further experimental studies and develop- ment of more satisfactory theoretical fundamentals are proceeding.
26 / The Behavioral and Social Sciences A study by physicians and behavioral scientists of how people use statistical information in decision making highlighted the importance of how the possible outcomes are perceived. More than 1,000 people graduate students in busi- ness school, physicians, and medical patientswere asked to imagine that they were suffering from lung cancer (none was known to have this disease) and could elect one of two treatments: surgery or radiation. The subjects were presented with the statistical prognosis for each treatment: for one group, the outcome was stated in terms of the probability of surviving for various lengths of time (for example, a two-thirds chance of living at least 1 year following treatment); for the other group, the outcome was stated in terms of the com- plementary probabilities of dying within those lengths of time (for example, a one-third chance of dying during the first post-treatment year). When presented with the two therapeutic options framed in terms of survival chances, the students chose radiation over surgery only 17 percent of the time, while the students presented with the identical prognoses framed in terms of the chances of dying chose radiation 43 percent of the time. When radiologists were the subjects, the contrast was just as pronounced: 16 percent chose ra- diation when presented the survival prognosis and SO percent chose it when presented the mortality prognosis. Among patients with chronic medical con- ditions, a considerably older group, the results were 20 percent and 40 percent in preference for radiation. Since the situations described to the subjects were simple and logically identical, these data clearly contradict a postulate of tra- ditional decision theory that identical situations be treated the same. The fram- ing of the problem clearly matters. Various studies are now in progress to expand and test several alternative theories of these framing effects, and re- search in the next several years is likely to bring major developments in this fundamental area of inquiry. A major line of work is focused on the fact that individuals often appear to rely on conventional biases, simplified concepts, and common rules of thumb in making decisions, rather than developing close probabilistic calculations or estimates. Although such heuristics typically reduce informational and cogni- tive demands for reaching decisions, they lead to demonstrably and system- atically incorrect results in certain very common situations. For example, the heuristic of representativeness leads people to think that a more "typical" event is also a more probable one, even when this is logically impossible. In one experiment, respondents were asked to report on the relative likelihood of various possible events, an example being the performance of championship tennis player Bjom Borg in a hypothetical Wimbledon match. A substantial fraction of subjects thought it more likely that (a) Borg would lose the opening set but still win the match than that (b) he would lose the opening set, whatever the final outcome. Yet possibility b has a likelihood equal to or greater than a, since b includes every instance of a as well as the additional possibilities of losing both the first set and the match. This kind of "cognitive illusion," at-
Behavior, Mind, and Brain / 27 tributed to people using the heuristic of representativeness, has been confirmed m many experiments. Two other common heuristics are availability and anchoring. Availability refers to the fact that estimates of the likelihood of an outcome are unduly influenced by the ease with which examples of particular outcomes are brought to mind. For example, most people will conclude that there are more words with r as the first letter than the third because it is easier to build a list of the former, but the latter are in fact more numerous. In anchoring, an individual's final estimate or judgment of a situation is overly influenced by the first of multiple examples or reference points that are observed; for example, extra weight is attached to the first of a series of numbers whose average (mean) is to be estimated. Knowledge about these and other heuristics and framing effects is laying the foundation for a more general theory of how information is used by individuals, and consequently, for a more thorough and precise understand- ing of individual decision-making behavior in general. Framing effects are recognized and manipulated on an intuitive level by publicists, advertising specialists, and politicians, among others. However, new formal models incorporating framing effects and decision-making heuristics are likely to have important new policy applications. For example, studies of framing effects may affect how ingredient or warning labels are written, how truth-in-lending laws are formulated, how unit prices are displayed in super- markets, and how election ballots are designed. Progress in understanding decision making has relied heavily on theoretical analysis and questionnaire-based experiments; there have been only limited observations of behavior in real decision situations. Now, however, researchers are beginning to use more complicated and realistic methods of dynamic study, including interactive computer-run experiments, improved field observation methods, and refined techniques of statistical inference to study actual behav- ior. A unified understanding of framing, biases, and heuristics, including the conditions that generate them, their robustness and their consequences, will become more possible as researchers are able to characterize choice behavior as a multistage process that involves information, evaluation, expression, and feedback. A promising parallel development is the fuller inclusion of these characteristics of choice behavior in systems models, working out their impli- cations for market efficiency and other aspects of organizational performance. Reasoning, Expertise, and Scientific Education How can general science education provide more students with durable scientific concepts and principles? It is widely recognized that such instruction often fails to communicate the fundamental meaning of scientific concepts. Indeed, recent research has dramatically shown that many people interpret physical phenomena in ways that are contrary to principles that they have
28 / The Behavioral and Social Sciences apparently learned well, at least to the extent of being able correctly to solve typical textbook problems. For example, many students who know how to calculate the Newtonian formulas fail to invoke the Newtonian principle of inertia when asked to sketch roughly the path followed by an object dropped from an airplane in flight. Researchers ask: Do people base their incorrect judgments on fragments of knowledge that come from experience, such as the way in which objects ordinarily fall when they are dropped? Or, do people have relatively coherent, but incorrect, naive theories about motion, gravita- tional force, and the like? Since people cannot report how their judgments in these matters are formed, current researchers are attempting to find out through indirect approaches. The answers have important implications for science ed- ucation because one uses quite a different set of instructional methods to teach students when to apply conceptual schemes than one uses to bring about major reconstructions of the students' naive theories. The handling of concepts, reasoning, and skills by "experts" is of great in- terest to information technologists and educators. Initially, two complementary ideas about experts were prevalent: that they have exceptional mental capaci- ties, such as an innate or trained ability to retrieve more facts or consider more possibilities at a time than do nonexperts; and that they have accumulated more knowledge about their subject than nonexperts, often because they have many years of experience. These ideas were incorporated into the design of early programs in artificial intelligence, in particular those for chess, for which the main goal was believed to be an ability to selectively consider many moves in advance. These ideas also underlie the design of contemporary computa- tional "expert systems," most of which incorporate large collections of knowl- edge. These same ideas are also reflected in many features of the educational system, where achievement in teaching and learning is often assessed exclu- sively with tests of factual knowledge or computational accuracy. However, researchers have shown that the underlying structure of knowl- edge is at least as important as the amount of information. Although experts do remember a great deal of specific information, their capacity to do this mainly depends on their having acquired elaborate, highly organized structures of knowledge. For example, chess experts are hardly better than nonplayers at remembering a randomly jumbled set of pieces on a chess boardbut they are far better at remembering a coherent board. Furthermore, experts, like novices, are typically not fully aware of the principles by which their knowledge is organized and used, so these tacit forms of knowledge are not reported by them. Thus, most expert systems now in use neglect some of the most important aspects of expert knowledge. One such well-known system was designed to assist in the diagnosis of infectious diseases and prescription of antibiotics. Initially, the knowledge sim- ulated in the system was a set of relatively simple rules of inference and a program that evaluated hypotheses simply by accumulating the positive and
Behavior, Mind, and Brain / 29 negative evidence it received. It matched reasonably well the judgments of successful physicians about the specific knowledge they used in their diagnostic work. But when the system was extended to aid in the training of physicians, it did not work well; it became evident that the organization of its knowledge and its methods of reasoning were seriously deficient. The program was reor- ganized based on more thorough analyses of the knowledge and real-time reasoning sequences of physicians in their diagnostic and training activities. These analyses showed that diagnostic strategies, including the use of hypoth- eses in selecting questions in interviews and the comparison of symptom pat- terns with the physician's mental representation of disease conditions, play a crucial role in diagnostic performance. These usually tacit components of knowledge have to be explicitly considered in physicians' training; the latest version of the expert system attempts to bring such tacit knowledge into play. The importance of general concepts and principles in expert knowledge is also demonstrated in recent research on problem solving in physics, in which expert and novice performance has been contrasted. An expert's understanding of problems includes the general qualitative concepts and principles that the problem illustrates, such as conservation of energy and laws of force, and these principles are used to organize the expert's reasoning in the problem-solving process, leading to calculations as a final step. In contrast, a novice's under- standing of problems mainly involves more superficial features, such as the kinds of objects in the problem. The novice typically seeks solutions by trans- lating the available information directly into formulas that allow the quick calculation of an answercorrect or not. Indeed, as noted above, students' knowledge of formulas is often quite disconnected from their understanding of general principles. People tend, as they become expert, to reorganize their knowledge of a given domain, and this tendency is not restricted to adults. For example, young children have much implicit knowledge of the difference between animate and inanimate objects. They know that animals move by themselves, that trees cannot have feelings, that dolls lack brains. But they do not assume that all animals breathe, reproduce, and so forth. Neither do they classify plants and animals together. They come to do these mental tasks, around ages 8 to 10, when they reorganize their knowledge about objects in the world, independent of explicit formal instruction, in accord with an intuitive theory of biology. The growing realization that children regularly reorganize their knowledge is of considerable import. These naturally occurring mental processes help uncover the laws of theory construction and concept reorganization that underlie the . . . r acquisition ot expertise. Research has begun to clarify some of the ways that understanding of general principles contributes to expert problem solving and reasoning, and it has also begun to show how children develop intuitive understanding of important general concepts and principles. Researchers are just beginning to be able to
30 / The Behavioral and Social Sciences characterize that understanding in explicit, testable ways. The crucial issue now is constructing a rigorous theory of the cognitive processes that are usually categorized as "intuition," involving qualitative reasoning about quantitative and other abstract concepts. A promising start has been made in formulating such theories, which will enable experimenters to test hypotheses about the properties of this form of expert reasoning that previously eluded systematic study and theoretical analysis. Complex Action The miracle of action is the ability of the mind to produce organized acts related to plans of action, perceptions of the world, and motives. People are not born with this ability. Newborn behavior appears to be comprised primarily of random movements and rhythmic stereotypes; over the first year of life they are gradually transformed into voluntarily guided, intentional, purposive ac- tions. The study of such motor skills from infancy to advanced performance is exploding after a long, relatively dormant period. The basic research interest in this area is complemented and invigorated by advances in robotics, by searches for a better fit between people and machines, by problems that occur in the manufacture and use of motor prosthetics, and by medical concern with motor disorders ranging from stuttering to Parkinson's disease. Exciting and promising results have been facilitated by new optical, magnetic, ultrasonic, and x-ray technologies for transducing motion, for storing the massive amounts of data collected, and for analyzing these large data bases, sometimes using artificial intelligence methods. Researchers are addressing a wide variety of questions, such as: What aspects of movement does the nervous system control? In accomplishing an action, how does the system constrain the many motions that are biomechanically available? What determines the accuracy of reaching? How are limbs coordi- nated? How is serial order represented and realized in planned movement sequences? How do errors in speech and typing come about? Consider a person reaching his or her hand toward an object, a motion controlled by an interplay of elbow and shoulder rotations. Biomechanically, the hand can approach the object along any of a vast number of paths; one might expect the actual path and the velocity profile along that path to reflect this complexity of control and to vary with the conditions of movement. Yet in the horizontal plane, the path is essentially a straight line, exhibiting a single- peaked, bell-shaped velocity curve. More generally, it is the overall movement itself, and not the pattern of activity in individual muscles, that is invariant during compound arm movements. Such simplicity suggests planning at the hand level rather than the joint level, with the system generating complex, coordinated joint-angle changes to achieve simple hand trajectories.
Behavior, Mind, and Brain / 31 Also in the domain of single actions, there is a new understanding of the remarkably general logarithmic trade-off between the speed and spatial accu- racy of limb movements. The prevailing theory had been that precision slows a movement because of an increase in the number of visually guided corrective submovements, with each submovement independent of precision. However, current experiments, growing out of a new mathematical theory, show that the trade-off occurs without visual feedback and that submovement speed varies with precision. How are single actions combined into ordered sequences? Studies of speech and typing during the past few years have revealed advance planning of entire sequences and the hierarchial organization of actions in multiaction units. For example, in rapid utterances in languages such as English, the unit is not the syllable, or the word, but the stress group, a sequence of syllables containing a primary stress, which usually corresponds to a grammatical phrase or clause structure. This supports the traditional hierarchical model of speech produc- tion, but it has also led some researchers to posit a network model, in which activation spreads both "up" from the sensors and "down" from the control nodes of the network. Only a hierarchical model can thus far explain facts of slips of the tongue, and new methods of inducing speech errors under labo- ratory conditions have facilitated research of this topic. In a similar vein, a model of typewriting, based on parallel distributed processing that converts a sequence of discrete symbols into continuous and temporally overlapping movements of fingers and hands, explains many features of timing and errors in the performance of skilled typists, including how a stroke by one finger can be accompanied by movements of other, then irrelevant, fingers to position them more favorably for action two or three strokes later. This is an active and exciting period in the study of complex human action. New findings are expected to improve person-machine interfaces (for example, instrument panels and keyboards), skill training, implementation of artificial movement systems (prosthetics, manipulators, robots), the diagnosis and treat- ment of movement disorders, and understanding of other complex skills like talking and walking. LANGUAGE To be fluent in a language is to be able to produce and understand an indefinite number of sentences never spoken or heard before. As one compo- nent of this ability, every spoken word can be identified by hearers in less than one-third of a second, drawing on the more than 100,000 forms stored in the mental dictionary of a typical monolingual adult (bilingual or multilingual people store hundreds of thousands of word forms). In little more time than it takes to process the sounds themselves, the words are then assembled into
32 / The Behavioral and Social Sciences meaningful sentences that more or less correctly represent the message in- tended by the speaker. This casual miracle of communication is possible in part because the human brain is uniquely suited to acquire and use language. Chimpanzees and gorillas are now widely viewed as having greater nonlinguistic cognitive abilities than previously thought, but they are unable, even with the most intensive human training (in sign language), to learn 1 percent of the vocabulary that is acquired by virtually any 3-year-old human child. Nor can these primates learn even the simplest of the complex grammatical rules known to nearly any 2- or 3- year-old human child. Since nearly all humans are fluent in at least one language and, except whe learning a new one, seldom consider what makes this possible, the complexity of the knowledge underlying the ability to speak and understand, and to read and write (abilities derived from spoken or signed language), is often not fully appreciated. Though the question of language acquisition and use has puzzled philosophers, educators, and scientists throughout modern history, answers to the puzzle have proven elusive until recent advances that rest, in part, on a sophisticated modular conception of language and its relationship to other cognitive faculties. While it was once commonplace to view the grammatical properties of lan- guage as essentially derivative a by-product of the general cognitive, phys- iological, and other nonspecific systems underlying human intelligence new evidence has convinced a growing number of scientists that linguistic capacity (and possibly, the mastery of grammar itself) is best viewed as an autonomous cognitive system, serving other systems but governed by its own set of distinct principles. For example, discourse patterns have been discovered that suggest that speakers can accommodate only one item of new information in a gram- matical clause. Moreover, it appears that speakers restrict the appearance of this new item to certain specific grammatical roles within the clause. This and related results have led to proposals of specific models of cognitive resources that both enable communicative processes and limit their scope. Principles of language performance and processing by no means exhaust the realm of possible knowledge about language, which is perhaps our richest cultural heritage, produced collectively over thousands of years and used for a great variety of social purposes. But this approach has led to entirely new methods of investigation that underlie some of the most important recent . c .lscoverles. . . . Acquisition The remarkable human facility to acquire language depends on a rich genetic endowment. People are well equipped for fluency in language (speech and gestures), just as birds are especially equipped to acquire and perform the
Behavior, Mind, and Brain / 33 songs of their species. Newborn infants, for example, respond to acoustic dis- tinctions that are systematically used in some human languages even though not necessarily in the child's own linguistic environment in a way that is different from their responses to distinctions that are not linguistically signif- icant in any known language. In a study of speech perception in 4-month-old infants, the child sucks rapidly to hear "pa" or "ha." As infants become habit- uated, the sucking rate drops. When a new stimulus is substituted ("ba" for "pa" or"pa" for"ba"), the infant dishabituates and sucks quickly once again. Similar results have been obtained for 1-month-old infants. These American infants thus show a sharp boundary in discriminating be- tween the sounds /ba/ and /pa/, a phonemic boundary in the English language. But these same American infants have an analogous sharp discrimination boundary in a prevoicing region that is not a phonemic contrast in English but is in certain other languages, such as Thai. Adults have considerable difficulty mak- ing such discriminations when they are not phonemically contrastive (func- tionally important) in their language. This indicates that certain aspects of phonological sensibility may be "prewired." Linguistic abilities can also be dissociated developmentally from other cog- nitive abilities. There are numerous cases of children who have few cognitive skills and virtually no ability to use language in sustained, meaningful com- munication and yet have extensive mastery of linguistic structure. For example, one severely retarded young woman with a nonverbal IQ of 41 to 44 who lacked almost all number concepts including basic counting principles, drew at a preschool level, and possessed an auditory memory span of three units (for example, syllables such as "two, three, one") could nonetheless produce syntactically complex sentences like "Last year at school when I first went there three tickets were gave out by a police." In a sentence imitation task she both detected and corrected surface syntactic and morphological errors. But she did not know how many "three tickets" were and was not sure whether "last year" occurred before or after "last week" or "an hour ago." Conversely, there are cases of children with little grammar but with other verbal abilities. One girl who was physically and socially isolated from the world from approximately age 1 to 14with no language input during that period rapidly acquired a large vocabulary following her liberation, but her utterances remained nongrammatical, devoid of morphological endings (for example, past tense or plural markers) or syntactic operations (for example, converting statements into questions). This contrast between word lists and grammatical rules is indicative of different and distinct abilities. Clinical studies of aphasia have given dramatic confirmation to these new fundamental theories. For example, local damage to certain regions of the left brain do not lead to across-the-board reduction in language ability, but to selective, deep deficits, consistent with the idea of independent grammatical components or modules. Some patients with left-brain damage make many
34 / The Behaviom1 and Social Sconces semantic substitutions in reading words: saying "pixie" when asked to read "gnome," "sick" Twill," "prison" for 'jail". Some can read a word like "tortoise" per~cOy but cannot say what it means: some speak Ouently but Ash non- sensical content: others speak in telegraphic sale, leaving out aL the short ~ncdon words. Clinicians are able to use linguistic phenomena such as these, together with analog of the know brain damage and previously observed patters of correction between such symptoms and brain damage discoveries in autopsies, to improve the diagnose and treatment of aphasia. The dramatic new technologies of neuroimaging, such as computerized to- mography (CT), magnetic resonance (NOR or WRIT and emission tomography using positrons (FET) or Single photons (SPET), now make possible the exact deUneadon of brain structures involved in various language ~ncdons. A major stimulus to Ocher progress in this held may take place when imaging tech- nology becomes more widely available far research with a variety of popula- dons. For example, since aphasias occur among speakers of all languages, research on aphasia on help isolate the basic, universal capacities sad neural substrates underlying human language. Because languages bee English rely heavy on word order to convey in~rmadon that languages like Lesson signal through inOechons Pouffes, pretest an important question ~ whether pa- dens with neurologicady similar brain lesions (discoverable through imaging) but who speak very different languages ~1 exhibit mani~stadons of the lesion that seem very different yet correspond to the same underlying abstract ~nc- tions. The organization of language mechanisms ~ also being studied using elec- trophysiological techniques, such as scalp recordings of event-related brain potentials (ERPs), which measure the electrical Relds that arise Tom coordi- nated groups of neurons engaged in processing sensor, cognitive, and lin- guisUc in~adon. By studying how ERPs van in fume, it has been possible to di~renthte among certain UnguisUc operadons. The Odious component of ERPs exhibit as~mecdes over the leg and right Odes of the brain and are sensitive to such factor as handedness and mode of language acquisition ~po- ken versus signed). Another important new line of research links language acquisition studies with theoretical work in cognitive science and arOhcial intelligence. One emerg- ing area ~ the theory of machine inductive inference, which invest/gates how inteHigent systems develop logical models or schemes based on evidence Mom their environment: far example, the inferring of the grammatical structure of a language based on utterances heard and overheard. This theory provides a framework for systematic comparison of various reaming algorithms in terms of their relative strengths, resource requirement, and behavior in Odious en- ~ronmeno. When combined with empirical studies of language acquisition, the theory of machine inductive inference provides constraints on the character of reaming strategies implemented by children and reOects on the character of
Behavior, Mind, and Brain / 35 the class of languages that can be acquired. Such studies are important to system builders in artificial intelligence. Sign Language Linguistic research on the sign languages of the deaf, particularly American Sign Language (ASL), is only 25-years-old, and it has opened a very important avenue toward a deeper understanding of all language. In spite of its name, ASL is not a signed version of American English, but rather a complete language in itself. It is more closely related to French sign language than to spoken English or British sign language, which is logical because it was first brought to the United States by teachers of the deaf from France. ASL has all the crucial properties common to spoken languages, including highly abstract underlying grammatical and "phonological" principles. The relationship between the form of a sign and its meaning is as arbitrary as that between the sound of a spoken word and its meaning. Sentence formation in ASL is just as rule governed as it is in spoken languages. ASL uses facial and other simultaneous body gestures (for example, lifting of eyebrows) to convey linguistic information similar to the morphological inflections that occur in spoken language. Variations in tone and emphasis convey additional layers of meaning in both spoken and sign languages in the latter, through the pacing and shaping of the gestures. Like hearing children with speaking parents, deaf children with signing parents acquire their native language without formal instruction and in similar stages. Brain studies of normal signers and deaf aphasics (patients suffering language loss following left-side brain damage) show that the left cerebral hemisphere is just as dominant for sign language as for spoken language. This finding has been a definitive result in proving that the left-hemisphere spe- cialization in the brain in language acquisition is not due to its capacity for fine auditory analysis, but for language analysis as such. Grammatical Universals Work on formal theories of grammar in the past 25 years has considerably sharpened understanding of linguistic universals principles that are common to all languages. For example, despite the fact that the rules to form passives ("The ball was thrown by John"), questions ("Who threw the ball?" or"The ball was thrown by whom?"), and imperatives ("Throw the ball!") differ mark- edly from language to language, modern theory and data argue that such con- structions are manifestations of simple but highly abstract underlying principles of grammar that differ only slightly across tongues. Work on languages related to English- such as Dutch, French, Spanish, and Italian and nonrelated lan- guages such as Japanese, Chinese, Arabic, Hausa (of West Africa), and Warl- piri (of Australia)support this view. Data on a wide variety of languages, as well as observations about how languages are acquired, are expected to con- tribute in a major way to the development of a viable formal language learning
36 / The Behavioral and Social Sciences theory. In particular, these data will permit the testing of various proposed theories of the learning process, including computer simulations of language acquisition, models evaluating the chances of learning a grammar from ob- serving a modest sample of the language, efficient forms of artificial intelligence, and explicit behavioral models of language performance and proficiency. Gram- matical and word acquisition studies in children should help to resolve con- troversies regarding the species-specificity of language, language-specific innate constraints, and the relative contribution of the child and the environment to the reaming process. The improvement of communication between people and computers by developing programming modes closer to "natural language" will also benefit from this work. A major research task in the next decade is to explore more completely the hypothesis of grammatical universality, through intensive investigation of lan- guages that are just now being fully described and are historically unrelated to the commonly studied ones. This work will involve considerable coordination and a stronger international basis between theoretical linguists and those de- scriptive linguists whose research is directed toward these frontier languages. It is also vitally important to this work to add to the relatively sparse instances of longitudinal studies that cover the same people over a period of many years and across a variety of linguistic learning environments. Machines That Talk and Listen Shortly after World War II, attempts were initiated to devise computer schemes to translate from one language to another, to recognize spoken and handwritten language, and to convert text into natural-sounding speech. Abortive and highly expensive early approaches to automatic machine translation and speech rec- ognition were made in electrical engineering projects, but they did not address the complexities of human language; participants in these efforts came ruefully to appraise their results as "language in garbage out." After engaging linguistic and phonological expertise to diversify the lines of research undertaken, team efforts ultimately did make good progress, leading to the scientific and practical successes seen to date. At present, interdisciplinary research aims to explain the intricate relations that hold between language, the world, and intelligent systems (whether natural or artificial). In one line of research, formal linguistic models are being devel- oped that make explicit provision for the varying computational requirements of language understanding. Relating linguists' grammars to existing computer systems enables computer scientists to provide a new generation of interpreter programs that run much more efficiently than their predecessors. A new theory of the semantics of programming languages promises to unite two formerly separate analyses: the denotational meanings of terms in natural language and the functional meanings of instructions in a computer program. Other devel-
Behavior, Mind, and Brain / 37 opments in this work include knowledge about the recursive (looping-back) nature of computational processes, symbolic systems, and the importance of shared knowledge and beliefs in conversational face-to-face interactions. In recent decades, collaboration between linguists, communication engi- neers, and computer scientists has led to dramatic increases in knowledge and new methods for analyzing and synthesizing acoustic speech signals. The com- puter revolution has made it possible to acquire and analyze in hours or days, rather than months or years, the large phonetic data bases needed to study the sound structures of language. As a result of the investigation of intonational and other phonetic properties of speech, undertaken with the goal of con- structing machines that talk and listen, there is a better understanding of how the units of a linguistic system relate to acoustic signals, leading to more natural- sounding, machine "voices" and more capable machine "ears." However, the present ability to synthesize speech far exceeds the ability to automate speech recognition and understanding, because the normal acoustic flow of speech cannot be readily divided into neat, uniform segments corresponding to dis- crete sounds, syllables, words, or even phrases, as is readily apparent by lis- tening to unfamiliar languages. At any instant of speech production, several articulators (larynx, tongue, velum, lips, jaw) are executing a complex, inter- woven, rhythmical pattern of movements, blurring the boundaries between words as well as between the phonemic segments that compose words. The problem is further complicated because each perceived unit sound, syllable, word, or phrase varies widely with phonetic context, stress or emphasis, and the rate of speech, style, dialect, and gender of individual speakers. (The ad- ditional problem of discriminating a speech signal from background noise, including other speech, was noted above.) What is invariant that enables people to recognize and understand speech? The discoveries of the last several decades have contributed to speech-recog- nition schemes, but they are still far from satisfactory; since they can deal at most with 5,000 words, compared with the 14,000 known by a 6-year-old or the 100,000 to 150,000 used by monolingual adults. The current solutions are still not very subtle. It is expected that dramatic improvements will accompany increased understanding of how the brain carries out the segmentation and analysis provided by the linguistic system. Reading Reading incorporates a complex hierarchy of skills, each raising a long list of questions in its own right. What are the fundamental perceptual processes involved in registration of visual print? How does word recognition occur? In the absence of aural and gestural cues, how do readers accomplish phrase interpretation? How are processes of inferential reasoning, critical thinking, and behavioral response catalyzed by the text? How predictable are these re- sponses?
38 / The Behavioral and Social Sciences There have been fairly dramatic advances recently in understanding each of these interactive processes linking reader and text, especially as a result of developments in the cognitive sciences. These advances have yielded new in- sights into what the eyes and brain do that enable a reader to comprehend written language. These insights have progressed to the point that computer simulations can pinpoint exactly where and why a given reader (with known skills) encounters difficulty in a text and disclose what might be done to avoid or ameliorate those difficulties. Knowledge from this research has led to educational strategies that result in improved reading skills in children. For example, in some projects, children who are poor readers have been taught particular cognitive strategies discovered in the skilled adult reader, such as how to identify and retain the most central information in a text. Children given this training show large and general improvements in comprehension. Other studies are implementing new pro- grams to teach word recognition, taking advantage in some instances of com- puter-based technology for practice, drill, and individual tailoring of the cur- riculum. The research has practical importance for scientific and technical documentation, display technologies, and instructional methods, and it also provides a major opportunity to expand the frontiers of knowledge about interactive multilevel reaming. Decoding and Dyslexias The process of decoding letters and words is critical in learning to read and has received a great deal of attention over the years, constituting the bulk of the research relating to reading. One central issue in research and pedagogical practice is whether a reader must use the printed words to retrieve a sound and then use the sound to retrieve the meaning of the word. Most of the evidence shows that a mature reader needs an intervening phonological code only if a word is unfamiliar or if the material is particularly difficult. But phonological decoding is critical when first learning to read. For example, awareness of the phonological structure of language is one predictor of the rapidity of early reading progress; S-year-old prereaders who can segment a spoken word into its constituent phonemes (who can, for example, follow an instruction to say "table" without the t) tend to be better at word recognition at the end of second grade. Such results reinforce the importance of a phonics approach at the earliest stages of reading instruction, when fluency of word recognition is the key factor to rapid progress. By third or fourth grade, children have generally mastered recognition skills sufficiently so that individual differences in reading skills no longer closely reflect differential word-decoding abilities. At these stages, knowledge of par- ticular kinds of text structure, such as narrative, becomes increasingly impor- tant to comprehension, and these matters are now receiving greatly increased attention. Even very young children are aware of narrative conventions and
Behavior, Mind, and Brain / 39 use this knowledge in understanding stories that are read or told to them. Recent analyses of grade-school materials suggest that many selections violate conventional story structures, making it difficult for a learning reader to estab- lish the coherence of the story. Research on reading comprehension will lead to better selection of useful texts for teaching. Some grammatical structures are known to be used much less in speaking than in writing. For example, cleft constructions like "It was John who won the trophy" are rarely spoken in English; rather, vocal stress on the name- "]ohn won the trophy" is sufficient to convey that the identity of the winner is the key information in the sentence. These differences between reading and speaking seem small, but for some dialects they may result in serious interfer- ence between the spoken language and comprehension of the written language. Such difficulties have been noted in some speakers of black English and some deaf children, for whom written English primers are virtually samples of a foreign dialect. While learning to read a second language without first knowing how to speak it is not uncommon for adults who are already literate in their native speech, it is a very unusual and difficult hurdle for children who are first reaming how to read. Explaining the wide variation among early and middle readers in the rates at which basic skills become automated and more advanced ones develop and finding the causes behind reading disabilities (dyslexias) are major challenges. Research on reading disability has proven to be especially difficult. There is still no general consensus about the nature or definition of dyslexia, and indeed there are probably several distinct kinds of dyslexia, some of which are cor- ollaries or causes and some of which are effects of reading dysfunctions. The field has discarded numerous theories that have not stood up to close testing, such as the hypothesis that the disorder is visual, involving reversals between letters such as b and d or words such as "saw" and "was"; that the disorder involves particular difficulty in associating visual and verbal elements; or that poor readers have difficulty in maintaining information about sequences. Other theories that have some support, but not full assent, include the idea that there is a deficiency in the specifically auditory-linguistic background and that the problem results from contracted vocabulary, low verbal fluency, inappropriate grammar or syntax, or difficulty or slowness in word retrieval. The most prom- ising approaches to these tangles of cause and effect appear to be continued fundamental research on normal acquisition of reading skills, more detailed examination of disabled individuals by interdisciplinary terms psychologists, cognitive scientists, medical researchers, and educators and more longitu- dinal research, starting with prereading children. Interpretation and Comprehension A number of techniques for studying human reading skills have in recent years achieved high levels of sophistication, enabling progress in areas that had
40 / The Behavioral and Social Sciences Typical Colleg - Level Reader Flywheels are one of the oldest mechanical devices known to man. Every ~ ~ ~$ ~3 ~ ~ internal-combustion engine contains a small flywheel that converts the jerky motion of the pistons into the smooth flow of energy that powers the drive shaft. Trained Speed Reader Colter understood enough of what they said to realize that some of them were proposing to set him up as a shooting target. Others were arguing for a more lingering death by tomahawk. Colter waited. Dyslexic Reader In appearance the surface of Mars is more like rocky ~)~ (by) , - - volcanic deserts on the earth than it is like the highly cratered surface of the moon, yet Mars, once visualized as being largely a world of gently rolling dunes, seems to possess little sand.
Behavior, Mind, and Brain / 41 seemed quiescent for many decades. One such technological advance is eye fixation research, which provides a detailed characterization of where in a text and for how long a reader looks, pauses, skips, or looks back. This kind of research was impossibly cumbersome before the availability of laboratory com- puters and precision optical and video devices and is providing clear answers to questions that have been on the table since early in this century. Eye fixation READING How do a reader's eyes move across the written page? What does the mind do as the eye moves? How are marks on paper interpreted as words that convey ideas? Researchers have developed methods to mechanically track a person's eye movements while reading a text and to meticulously analyze the patterns of gaze and subsequent accuracy of comprehension of the material. Such ex- periments are used to test and develop theoretical models of how people process what they see on paper. The different gaze patterns in this figure, represented by the pause durations (in milliseconds) and retracking lines, are typical of different kinds of readers. (There is no significance to the different texts shown; they are standard passages used in experiments.) Though texts differ in complexity, a given reader processes them the same way and at relatively small variation in overall speed. Most people sample a written text densely, fixing their gaze (for more than 50 milliseconds) on about two-thirds of the words and rarely skimming past more than one word at a time; in most cases, the skimmed words are articles, prepositions, and conjunctions, "function words." Nearly all readers interpret each word immediately, inferring its meaning even when important clues to that meaning come later in the text. The duration of gaze on each word depends on the word's length, familiarity, and grammatical or contex- tual clarity. There is also a tendency to pause longer on the word at the end of a printed line rather than at the end of a sentence- to "wrap up" any loose ends in interpretation. Normally, readers retrace their gaze only when a grammatical or semantic ambiguity leads them to rethink how to interpret a phrase. Readers trained to "speed read" fixate on fewer words and spend less time on each fixation. Like normal readers, they retain very little information from words they do not fixate. The major skill that speed readers learn is to infer the meaning of a line of text based on a smaller sample of the words in it than before and not to tarry or retrack in order to resolve local ambi- guities in meaning. The cost of these rapid inference procedures is less accurate comprehension, especially for nonrecurrent details. Dyslexic readers seem to have trouble mainly in decoding written words, that is, segmenting the letters into syllables and retrieving their sounds correctly. These readers spend extra time on each word and frequently re- track in order to reinterpret inaccurately perceived words. And even at their slower reading rates, dyslexic readers generally develop a much less accurate understanding of a written text than other readers a problem they do not necessarily have in interpreting spoken words. r --r ~ r
42 / The Behavioral and Social Sciences research has revealed that the instantaneous perceptual window during reading is only two or three words wide even for highly literate readers, and that readers fixate on 70 to 85 percent of the content words of an unfamiliar or technical text, but only 40 percent of the short function words, such as "an" and "of." Also, readers attempt to understand the meaning of each word as soon as they see it rather than postpone a choice of interpretation until more data (from the remaining parts of the sentence) are collected. If the interpretation proves incorrect, readers then seek the source of the problem and choose an alternative interpretation that works better. The characteristics of each content word, such as its familiarity and the moment-to-moment demands of linguistic and task processing, control the duration of pausing on the word. Pause duration is thus a gauge of processing load or difficulty at each point in a text. Since a reader is constructing a mental representation of a text while pro- cessing only a single phrase or sentence at a time, short-term memory limita- tions may play an important role in reading comprehension. This is not a new hypothesis. But the original theoretical claims that short-term memory may be an important bottleneck for comprehension processes were contradicted by the fact that standard short-term memory tests (for example, digit span) did not correlate with reading comprehension skills. The more recent experimental work does not evaluate short-term memory capacity in static contexts or at nonreading tasks; rather, it evaluates how much excess capacity different read- ers have available during the actual reading process: the resulting measures are highly predictive of comprehension levels. Detailed temporal analyses of this sort have also made it possible to write a computer program that reads newly encountered though very carefully edited and prepared texts about as well and as rapidly as human readers. The program "pauses" taking longer to process a passage when there is difficulty in com- prehension and speeds up when comprehension is easy. It can produce a summary or answer certain kinds of questions about the content of texts about as well as humans can. Efficient readers adapt their expenditure of effort and ingenuity to their goal in reading, such as "light" reading for relaxation, reading to learn, or reading to react to an action document, such as a request for funds. Mature readers possess a complex repertoire of reading and study strategies for enhancing understanding and for detecting and overcoming comprehension difficulties. Considerable advances have been made in understanding of how these learning activities develop and how they can be enhanced by instruction. All of these advances can now be described and measured in terms of scientific theory rather than just intuitively, as was once the case. No artificial intelligence reading program comes close to the seemingly ef- fortless way in which humans seem able to call up just the right information needed to interpret a text and ignore the mass of irrelevant data. But recent work has begun to create substantially better insight into how people do this,
Behavior, Mind, and Brain / 43 and one interesting fact is that readers do not simply ignore irrelevant infor- mation. Consider the sentence: "Thieves broke into the vault of a bank and stole a million dollars." Do you even consider interpreting"bank" in the sense of "river bank?" No? Sophisticated methods show otherwise. If a person is {lashed the word "bank" and then, immediately, "money," the response to "money" is about 40 milliseconds faster than when an unrelated word (say, "bark") comes first. This is called a priming effect. In a context like the sentence above, if"bank" is followed quickly by "river," instead of"money," the priming effect on recognition is present for this word as well, showing that both possible meanings had been activated. After a 300 millisecond interval, however, prim- ing would occur only for the contextually appropriate meaning ("money"~. The results of such laboratory experiments suggest that a rich knowledge of rela- tionships among words may facilitate decoding and perhaps other levels of processing, even though there is no conscious awareness by a reader of how such knowledge is being processed in the course of reading. A recent goal of language research is to develop a scientific basis for writing comprehensible texts. Previously, the classical view was that texts are less readable when they contain long sentences and use uncommon words. But research shows that revising a difficult text by shortening its sentences and simplifying the vocabulary does not make it substantially (or sometimes even at all) more comprehensible. One idea being studied is that some texts may be hard to read because the reader must repeatedly search in long-term memory for specific information needed to interpret phrases or sentences. Other re- search focuses on how well the syntactic devices and cues in a text focus the reader's attention on its major themes or most important information. Related research has shown that successful didactic writing highlights information that the reader needs in order to act or that sets forth specific examples that the reader will most likely have encountered or expect to encounter. Continued work along these lines should lead to improved and simplified models of how to make written documents more comprehensible, but this is only a proximate goal. Making a text comprehensible for a given reader will certainly contribute to understanding, but it will not necessarily lead to learn- ing. People can comprehend, remember, and summarize a text and still be unable to use the information acquired; learning requires the integration of textual information with previous knowledge. There is much work to be done to discover how people learn, how they use the information acquired from a . . . text in new situations. OPPORTUNITIES AND NEEDS The results of research on basic processes linking the mind, the brain, and behavior have grown impressively in the recent past and show even more
44 / The Behavioral and Social Sciences promise in the immediate future. Some of those results have led or soon will lead to valuable applications, such as new types of photography; economical telephone-line transmission of video pictures; better hearing aids; ways to im- prove normal and impaired memory; enhanced computer abilities to synthe- size, decode, and translate natural speech; vastly improved expert systems to aid in such matters as medical diagnosis and car repair; and innovations in teaching students across all areas and levels of learning. But the major contri- bution of this research is that of sheer knowledge about human beings and other intelligent beings a wealth of insights into the nature, possibilities, and limits of intelligent individual action. In this section we propose increased expenditures of approximately $61 million annually for this research: for equip- ment, investigator-initiated grants, new data collection, research centers, pre- doctoral and postdoctoral fellowships, postdoctoral training institutes, and multidisciplinary collaborative activities. Research in these areas depends heavily on instrumentation for simulating, modeling, and controlling experiments, generating stimuli, recording and ana- lyzing data, and developing new theoretical models, which require substantial amounts of computational power. Some of this equipment is currently only available, if at all, in such special settings as clinics, national laboratories, or expensive commercial centers. Increasingly, there is a call for greater access to powerful workstations and supercomputers. There is also a lively expectation that massively parallel computer architectures will be especially well suited to many behavioral and cognitive research problems. To some extent the com- putational need is filled by machines available at major research universities, but during the recent period of serious funding cutbacks and stringencies imposed on the behavioral and social sciences and the increased regulatory demands on research involving animals and humans, the overall level of in- strumentation in laboratories has fallen seriously short of the research needs. Many formerly up-to-date university laboratories are no longer adeauatelv equipped to do the research that is now possible. In light of the increasingly advanced and specialized technology required to carry out experiments on behavior, mind, and brain, an estimated $25 million in new funds annually are needed to acquire or provide access to new equip- ment. We estimate that about one-half of this amount ($12 million) should be allocated to new and upgraded laboratory equipment and service facilities, about one-fourth ($7 million) to new computer hardware and software devel- opment, about $4 million to the improvement of animal care for research animals, and about $2 million for access to major neuroimaging devices. The principal mode of studies on behavior, mind, and brain is carried out by small groups of investigators: one or two principal investigators working on a separately funded project (though each investigator may have more than one project) with one or a few assistants, who may range in level of training, skills, C, , ,
Behavior, Mind, and Brain / 45 and independence from technicians to postdoctoral scientists. This approach has worked well, and we do not recommend major changes. Such research by small groups is largely supported by investigator-initiated grants. The aggregated funding level of these grants has been somewhat buff ered from roller-coaster trends in behavioral and social sciences spending at the federal level, due partly to the linkages and overlaps with life science and computer science research, which have been on more monotonic funding paths. Cognitive and behavioral sciences support nevertheless has not kept up with the growth in scientific opportunities, such as the rapid shifts in technological capabilities that have resulted from the microprocessor revolution. A rapid increase in funds for investigator-initiated grants- by about $20 million an- nually is a high priority. These funds should be used to increase research productivity in three ways. First, they should be used to reverse the lack of change or actual reduction in the size of grants that has occurred at a time when real costs are increasing. Those real cost increases have resulted from improvements in animal care, the need for auxiliary staff in experiments in- volving infants and children, and the routine costs of supplies and services, among other matters. Second, they should be used to increase the duration of a typical grant to an experienced investigator from 3 to S years. Such an increase will sharply reduce the burden of time imposed both on investigators preparing renewal grant proposals and on the individuals asked to read and evaluate each proposal (generally 6, but sometimes as many as IS), which is a nonnegligible cost in research time. Third, they should be used to increase somewhat the total number of grants available because many promising proposals are now being turned down due to lack of funds. A great deal of the pioneering research lies at the interface of disciplines and often requires a great deal of highly specialized technical expertise in fields ranging from biochemistry and physics to neuroscience, physiology, psychol- ogy, linguistics, economics, statistics, mathematics, and computer science. This inherent feature of much current work on behavior, the mind, and the brain calls for a number of developments to foster and facilitate more collaboration among people from very different backgrounds. This facilitation may take dif- ferent forms, such as short-term visits, new centers of research, interdisciplinary training in the predoctoral curricula of universities, or the growth of postdoc- toral programs that broaden rather than intensify the focus of new scientists' thesis work. We especially note the need for advanced training institutes for younger postdoctoral-level researchers working on newly emerging methods in highly technical specialities and recommend an additional $1 million be spent annually for such institutes. Given the geographical dispersion of inves- tigators, collaboration can often be sustained only if there are opportunities to come together periodically in joint working sessions. Short-term workshops, seminars, and conferences focused on exchanges of current ideas and methods
46 / The Behavioral and Social Sciences are the ideal medium to encourage this, and we recommend that $1 million be added to current levels of funding for such activities. The picture of recruitment into graduate schools in the behavioral, cognitive, and brain science disciplines continues to reflect a growth trend. But much of this growth leads toward clinical and other nonresearch employment, and there is growing concern about the number of highly motivated and talented young people who are entering research careers. In particular, there is a relative lack of opportunity for individuals to gain intense experience at the predoctoral or postdoctoral levels in a variety of research methods and theoretical disciplines. This is only in small part a problem of curriculum: it is in large part a problem of funding, which is available more for teaching and clinical or applied work than for research apprenticeships. We therefore recommend that an additional $5 million annually be invested in research fellowships at the predoctoral and postdoctoral levels, with the majority share ($3 million) directed to the post- doctoral level. There is in certain areas a critical need to inaugurate new data bases that can be accessed by large numbers of investigators; in particular, longitudinal data bases concerning cognitive and educational development. The cost of these new data collection effort would be about $5 million annually. Finally, there is at present momentum in certain fields toward major new interdisciplinary research enterprises. In the recent climate of restrained budget growth, it has not been possible to organize the sort of stimuli either in the form of planning grants or competitive announcements for new center pro- grams that would lead to competitive, full-fledged center proposals. We rec- ommend that there be an initial commitment of $4 million to create two to three new interdisciplinary centers, with a view toward increasing this by as much as threefold if the experience of productivity warrants. We should note that some increment in support staffing in research agencies is a necessary element to generate, evaluate, and monitor good center grants.
