This target article discusses the verbal working memory system used in sentence comprehension. We review the concept of working memory as a short-duration system in which small amounts of information are simultaneously stored and manipulated in the service of accomplishing a task. We summarize the argument that syntactic processing in sentence comprehension requires such a storage and computational system. We then ask whether the working memory system used in syntactic processing is the same as that used in verbally mediated tasks that involve conscious controlled processing. Evidence is brought to bear from various sources: the relationship between individual differences in working memory and individual differences in the efficiency of syntactic processing; the effect of concurrent verbal memory load on syntactic processing; and syntactic processing in patients with poor short-term memory, patients with poor working memory, and patients with aphasia. Experimental results from these normal subjects and patients with various brain lesions converge on the conclusion that there is a specialization in the verbal working memory system for assigning the syntactic structure of a sentence and using that structure in determining sentence meaning that is separate from the working memory system underlying the use of sentence meaning to accomplish other functions. We present a theory of the divisions of the verbal working memory system and suggestions regarding its neural basis.

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change are much more rapid than processes of genetic change, language constitutes a “moving target” both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG – the mesh between learners and languages – arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent “organism,” which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics.

Fundamental to spatial knowledge in all species are the representations underlying object recognition, object search, and navigation through space. But what sets humans apart from other species is our ability to express spatial experience through language. This target article explores the language of objects and places, asking what geometric properties are preserved in the representations underlying object nouns and spatial prepositions in English. Evidence from these two aspects of language suggests there are significant differences in the geometric richness with which objects and places are encoded. When an object is named (i.e., with count nouns), detailed geometric properties – principally the object's shape (axes, solid and hollow volumes, surfaces, and parts) – are represented. In contrast, when an object plays the role of either “figure” (located object) or “ground” (reference object) in a locational expression, only very coarse geometric object properties are represented, primarily the main axes. In addition, the spatial functions encoded by spatial prepositions tend to be nonmetric and relatively coarse, for example, “containment,” “contact,” “relative distance,” and “relative direction.” These properties are representative of other languages as well. The striking differences in the way language encodes objects versus places lead us to suggest two explanations: First, there is a tendency for languages to level out geometric detail from both object and place representations. Second, a nonlinguistic disparity between the representations of “what” and “where” underlies how language represents objects and places. The language of objects and places converges with and enriches our understanding of corresponding spatial representations.

As adults we believe that our knowledge of our own psychological states is substantially different from our knowledge of the psychological states of others: First-person knowledge comes directly from experience, but third-person knowledge involves inference. Developmental evidence suggests otherwise. Many 3-year-old children are consistently wrong in reporting some of their own immediately past psychological states and show similar difficulties reporting the psychological states of others. At about age 4 there is an important developmental shift to a representational model of the mind. This affects children's understanding of their own minds as well as the minds of others. Our sense that our perception of our own minds is direct may be analogous to many cases where expertise provides an illusion of direct perception. These empirical findings have important implications for debates about the foundations of cognitive science.

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends on high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research.

A comparative method of studying the biological bases of personality compares human trait dimensions with likely animal models in terms of genetic determination and common biological correlates. The approach is applied to the trait of sensation seeking, which is defined on the human level by a questionnaire, reports of experience, and observations of behavior, and on the animal level by general activity, behavior in novel situations, and certain types of naturalistic behavior in animal colonies. Moderately high genetic determination has been found for human sensation seeking, and marked strain differences in rodents have been found in open-field behavior that may be related to basic differences in brain neurochemistry. Agonistic and sociable behaviors in both animals and humans and the trait measure of sensation seeking in humans have been related to certain common biological correlates such as gonadal hormones, monoamine oxidase (MAO), and augmenting of the cortical evoked potential.

The monoamine systems in the rodent brain are involved in general activity, exploratory behavior, emotionality, socialization, dominance, sexual and consummately behaviors, and intracranial self-stimulation. Preliminary studies have related norepinephrine and enzymes involved in its production and degradation to human sensation seeking. A model is suggested that relates mood, behavioral activity, sociability, and clinical states to activity of the central catecholamine neurotransmitters and to neuroregulators and other transmitters that act in opposite ways on behavior or stabilize activity in the arousal systems. Stimulation and behavioral activity act on the catecholamine systems in a brain–behavior feedback loop. At optimal levels of catecholamine systems activity (CSA) mood is positive and activity and sociability are adaptive. At very low or very high levels of CSA mood is dysphoric, activity is restricted or stereotyped, and the organism is unsocial or aggressively antisocial. Novelty, in the absence of threat, may be rewarding through activation of noradrenergic neurons.

During active vision, the eyes continually scan the visual environment using saccadic scanning movements. This target article presents an information processing model for the control of these movements, with some close parallels to established physiological processes in the oculomotor system. Two separate pathways are concerned with the spatial and the temporal programming of the movement. In the temporal pathway there is spatially distributed coding and the saccade target is selected from a “salience map.” Both pathways descend through a hierarchy of levels, the lower ones operating automatically. Visual onsets have automatic access to the eye control system via the lower levels. Various centres in each pathway are interconnected via reciprocal inhibition. The model accounts for a number of well-established phenomena in target-elicited saccades: the gap effect, express saccades, the remote distractor effect, and the global effect. High-level control of the pathways in tasks such as visual search and reading is discussed; it operates through spatial selection and search selection, which generally combine in an automated way. The model is examined in relation to data from patients with unilateral neglect.

A broad range of evidence regarding the functional organization of the vertebrate brain – spanning from comparative neurology to experimental psychology and neurophysiology to clinical data – is reviewed for its bearing on conceptions of the neural organization of consciousness. A novel principle relating target selection, action selection, and motivation to one another, as a means to optimize integration for action in real time, is introduced. With its help, the principal macrosystems of the vertebrate brain can be seen to form a centralized functional design in which an upper brain stem system organized for conscious function performs a penultimate step in action control. This upper brain stem system retained a key role throughout the evolutionary process by which an expanding forebrain – culminating in the cerebral cortex of mammals – came to serve as a medium for the elaboration of conscious contents. This highly conserved upper brainstem system, which extends from the roof of the midbrain to the basal diencephalon, integrates the massively parallel and distributed information capacity of the cerebral hemispheres into the limited-capacity, sequential mode of operation required for coherent behavior. It maintains special connective relations with cortical territories implicated in attentional and conscious functions, but is not rendered nonfunctional in the absence of cortical input. This helps explain the purposive, goal-directed behavior exhibited by mammals after experimental decortication, as well as the evidence that children born without a cortex are conscious. Taken together these circumstances suggest that brainstem mechanisms are integral to the constitution of the conscious state, and that an adequate account of neural mechanisms of conscious function cannot be confined to the thalamocortical complex alone.

Functional specialization in the lower and upper visual fields in humans is analyzed in relation to the origins of the primate visual system. Processing differences between the vertical hemifields are related to the distinction between near (peripersonal) and far (extrapersonal) space, which are biased toward the lower and upper visual fields, respectively. Nonlinear/global processing is required in the lower visual field in order to pergeive the optically degraded and diplopic images in near vision, whereas objects in far vision are searched for and recognized primarily using linear/local perceptual mechanisms. The functional differences between near and far visual space are correlated with their disproportionate representations in the dorsal and ventral divisions of visual association cortex, respectively, and in the magnocellular and parvocellular pathways that project to them. Advances in far visual capabilities and forelimb manipulatory skills may have led to a significant enhancement of these functional specializations.

The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The evidence speaks strongly against bottom-up approaches to vision. In particular, the constraints suggest an attentional mechanism that exploits knowledge of the specific problem being solved. This analysis of visual search performance in terms of attentional influences on visual information processing and complexity satisfaction allows a large body of neurophysiological and psychological evidence to be tied together.

To explain social learning without invoking the cognitively complex concept of imitation, many learning mechanisms have been proposed. Borrowing an idea used routinely in cognitive psychology, we argue that most of these alternatives can be subsumed under a single process, priming, in which input increases the activation of stored internal representations. Imitation itself has generally been seen as a “special faculty.” This has diverted much research towards the all-or-none question of whether an animal can imitate, with disappointingly inconclusive results. In the great apes, however, voluntary, learned behaviour is organized hierarchically. This means that imitation can occur at various levels, of which we single out two clearly distinct ones: the “action level,” a rather detailed and linear specification of sequential acts, and the “program level,” a broader description of subroutine structure and the hierarchical layout of a behavioural “program.” Program level imitation is a high-level, constructive mechanism, adapted for the efficient learning of complex skills and thus not evident in the simple manipulations used to test for imitation in the laboratory. As examples, we describe the food-preparation techniques of wild mountain gorillas and the imitative behaviour of orangutans undergoing “rehabilitation” to the wild. Representing and manipulating relations between objects seems to be one basic building block in their hierarchical programs. There is evidence that great apes suffer from a stricter capacity limit than humans in the hierarchical depth of planning. We re-interpret some chimpanzee behaviour previously described as “emulation” and suggest that all great apes may be able to imitate at the program level. Action level imitation is seldom observed in great ape skill learning, and may have a largely social role, even in humans.

A review of research with chicks, songbirds, rodents, and nonhuman primates indicates that the brain is lateralized for a number of behavioral functions. These findings can be understood in terms of three hypothetical brain processes derived from a brain model based on general systems theory: hemispheric activation, interhemispheric inhibition, and interhemispheric coupling.

Left-hemisphere activation occurs in songbirds and nonhuman primates in response to salient auditory or visual input, or when a communicative output is required. The right hemisphere is activated in rats when spatial performance is required, and in chicks when they are placed in an emotion-provoking situation. In rats and chicks interhemispheric activation and inhibition occur when there is an affective component in the environment (novelty, aversive conditioning) or when an emotional response is emitted (copulation, attack, killing). An interhemispheric coupling (correlation) found in rats and rabbits implies that the hemispheres are two major components in a control system with a negative feedback loop. Early-experience variables in rats can induce laterality in a symmetric brain or facilitate its development in an already biased brain.

It is predicted that functional lateralization, when present, will be similar across species: the left hemisphere will tend to be involved in communicative functions while the right hemisphere will respond to spatial and affective information; both hemispheres will often interact via activation-inhibition mechanisms when affective or emotional processes are involved. Homologous brain areas and their connecting callosal fibers must be intact at birth and must remain intact throughout development for lateralization to reach its maximum level. Injury to any portion of this unit will result in hemispheric redundancy rather than specialization. One major function of early experience is to provide stimulation during development, which acts to enhance the growth and development of the corpus callosum, thereby giving rise to a more specialized brain.

One of the most intriguing and controversial observations in oculomotor research in recent years is the phenomenon of express saccades in monkeys and man. These are saccades with such short reaction times (100 msec in man, 70 msec in monkeys) that some experts on eye movements still regard them as artifacts or as anticipatory reactions that do not need any further explanation. On the other hand, some research groups consider them not only authentic but also a valuable means of investigating the mechanisms of saccade generation, the coordination of vision and eye movements, and the mechanisms of visual attention.

This target article puts together pieces of experimental evidence in oculomotor and related research – with special emphasis on the express saccade – to enhance our present understanding of the coordination of vision, visual attention, and the eye movements subserving visual perception and cognition.

We hypothesize that an optomotor reflex is responsible for the occurrence of express saccades, one that is controlled by higher brain functions involved in disengaged visual attention and decision making. We propose a neural network as the basis for more elaborate mathematical models or computer simulations of the optomotor system in primates.

All recent memory theories of hippocampal function have incorporated the idea that the hippocampus is required to process items only of some qualitatively specifiahle kind, and is not required to process items of some complementary set. In contrast, it is now proposed that the hippocampus is needed to process stimuli of all kinds, but only when there is a need to associate those stimuli with other events that are temporally discontiguous. In order to form or use temporally discontiguous associations, it is essential to maintain some memory of the first component until the second component has occurred. When the temporal gap to he spanned is small, and the number of items to be temporarily retained is low, a limited-capacity, short-term store is sufficient to allow associations to be formed. Such a store is presumed to operate in parallel with the hippocampus in normal animals. Hippocampal damage disrupts a much higher-capacity store that has a slower decay rate, and so leaves animals with only a very limited ability to form temporally discontiguous associations. Hippocampal damage, however, is not held to affect the long-term storage of associations of any kind, if they can be formed. Analyses of both new and existing data are presented to show that by classifying tasks in terms of the need to use a temporary memory store to retain temporally discontiguous information one can cut right across existing classifications as well as achieve a better fit to the data. The hippocampus thus seems best described as a high-capacity, intermediate-term memory store.

Investigations of the function of consciousness in human information processing have focused mainly on two questions: (1) Where does consciousness enter into the information processing sequence, and (2) how does conscious processing differ from preconscious and unconscious processing? Input analysis is thought to be initially “preconscious” and “pre-attentive” - fast, involuntary, and automatic. This is followed by “conscious,” “focal-attentive” analysis, which is relatively slow, voluntary, and flexible. It is thought that simple, familiar stimuli can be identified preconsciously, but conscious processing is needed to identify complex, novel stimuli. Conscious processing has also been thought to be necessary for choice, learning and memory, and the organization of complex, novel responses, particularly those requiring planning, reflection, or creativity.

The present target article reviews evidence that consciousness performs none of these functions. Consciousness nearly always results from focal-attentive processing (as a form of output) but does not itself enter into this or any other form of human information processing. This suggests that the term “conscious process” needs reexamination. Consciousness appears to be necessary in a variety of tasks because they require focal-attentive processing; if consciousness is absent, focal-attentive processing is absent. From a first-person perspective, however, conscious states are causally effective. First-person accounts are complementary to third-person accounts. Although they can be translated into third-person accounts, they cannot be reduced to them.

Theories of children's developing understanding of mind tend to emphasize either individualistic processes of theory formation, maturation, or introspection, or the process of enculturation. However, such theories must be able to account for the accumulating evidence of the role of social interaction in the development of social understanding. We propose an alternative account, according to which the development of children's social understanding occurs within triadic interaction involving the child's experience of the world as well as communicative interaction with others about their experience and beliefs (Chapman 1991; 1999). It is through such triadic interaction that children gradually construct knowledge of the world as well as knowledge of other people. We contend that the extent and nature of the social interaction children experience will influence the development of children's social understanding. Increased opportunity to engage in cooperative social interaction and exposure to talk about mental states should facilitate the development of social understanding. We review evidence suggesting that children's understanding of mind develops gradually in the context of social interaction. Therefore, we need a theory of development in this area that accords a fundamental role to social interaction, yet does not assume that children simply adopt socially available knowledge but rather that children construct an understanding of mind within social interaction.

We suggest that human culture exhibits key Darwinian evolutionary properties, and argue that the structure of a science of cultural evolution should share fundamental features with the structure of the science of biological evolution. This latter claim is tested by outlining the methods and approaches employed by the principal subdisciplines of evolutionary biology and assessing whether there is an existing or potential corresponding approach to the study of cultural evolution. Existing approaches within anthropology and archaeology demonstrate a good match with the macroevolutionary methods of systematics, paleobiology, and biogeography, whereas mathematical models derived from population genetics have been successfully developed to study cultural microevolution. Much potential exists for experimental simulations and field studies of cultural microevolution, where there are opportunities to borrow further methods and hypotheses from biology. Potential also exists for the cultural equivalent of molecular genetics in “social cognitive neuroscience,” although many fundamental issues have yet to be resolved. It is argued that studying culture within a unifying evolutionary framework has the potential to integrate a number of separate disciplines within the social sciences.

The Modularity of Mind proposes an alternative to the “New Look” or “interaetionist” view of cognitive architecture that has dominated several decades of cognitive science. Whereas interactionism stresses the continuity of perceptual and cognitive processes, modularity theory argues for their distinctness. It is argued, in particular, that the apparent plausibility of New Look theorizing derives from the failure to distinguish between the (correct) claim that perceptual processes are inferential and the (dubious) claim that they are unencapsidated, that is, that they are arbitrarily sensitive to the organism's beliefs and desires. In fact, according to modularity theory, perceptual processes are computationally isolated from much of the background knowledge to which cognitive processes have access. The postulation of autonomous, domain-specific psychological mechanisms underlying perceptual integration connects modularity theory with the tradition of faculty psychology, in particular, with the work of Franz Joseph Call. Some of these historical affinities, and some of the relations between faculty psychology and Cartesianism, are discussed in the book.

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, and only sustained empirical research in cognitive science will determine the extent to which that is true.