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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

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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

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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-

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10 / The Behavioral and Social Sciences

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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.

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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,

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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

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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

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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-

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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-

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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?

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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

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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

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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.

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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

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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,

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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

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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, , ,

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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

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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.