In the past decades, reductionism has dominated both research directions and funding policies in clinical psychology and psychiatry. The intense search for the biological basis of mental disorders, however, has not resulted in conclusive reductionist explanations of psychopathology. Recently, network models have been proposed as an alternative framework for the analysis of mental disorders, in which mental disorders arise from the causal interplay between symptoms. In this target article, we show that this conceptualization can help explain why reductionist approaches in psychiatry and clinical psychology are on the wrong track. First, symptom networks preclude the identification of a common cause of symptomatology with a neurobiological condition; in symptom networks, there is no such common cause. Second, symptom network relations depend on the content of mental states and, as such, feature intentionality. Third, the strength of network relations is highly likely to depend partially on cultural and historical contexts as well as external mechanisms in the environment. Taken together, these properties suggest that, if mental disorders are indeed networks of causally related symptoms, reductionist accounts cannot achieve the level of success associated with reductionist disease models in modern medicine. As an alternative strategy, we propose to interpret network structures in terms of D. C. Dennett's (1987) notion of real patterns, and suggest that, instead of being reducible to a biological basis, mental disorders feature biological and psychological factors that are deeply intertwined in feedback loops. This suggests that neither psychological nor biological levels can claim causal or explanatory priority, and that a holistic research strategy is necessary for progress in the study of mental disorders.

Ethologists and comparative psychologists have found that the social behavior, discrimination learning, and especially the communicative behavior of many animals are sufficiently versatile to call into question the customary denial that animals have mental experiences comparable to our own. Many of their behavior patterns suggest that animals have mental images of objects, events, or relationships remote from the immediate stimulus situation, as well as self-awareness and intentions concerning future actions. Our behavioristic Zeitgeist has inhibited investigation of such possibilities, but reopening these long-neglected questions requires no departure from the materialistic approach to biological and behavioral science. The basic question at issue involves a comparison of those aspects of human and nonhuman brain function that sometimes lead to what we call mental experiences, at least in our own species. It seems more feasible to devise objectively verifiable tests for the existence of these general categories of mental experiences than for that of many others. While many other kinds of evidence could well be used (with appropriate caution and all possible controls) to weigh the likelihood that animals sometimes know what they are doing, the experimental use of communicative behavior seems especially promising, because the latter could serve a function analogous to human language, which provides our best evidence about the mental experiences of our fellow men.

The study of neuronal specialisation in different cognitive and perceptual domains is important for our understanding of the human brain, its typical and atypical development, and the evolutionary precursors of cognition. Central to this understanding is the issue of numerical representation, and the question of whether numbers are represented in an abstract fashion. Here we discuss and challenge the claim that numerical representation is abstract. We discuss the principles of cortical organisation with special reference to number and also discuss methodological and theoretical limitations that apply to numerical cognition and also to the field of cognitive neuroscience in general. We argue that numerical representation is primarily non-abstract and is supported by different neuronal populations residing in the parietal cortex.

In visual science the term filling-in is used in different ways, which often leads to confusion. This target article presents a taxonomy of perceptual completion phenomena to organize and clarify theoretical and empirical discussion. Examples of boundary completion (illusory contours) and featural completion (color, brightness, motion, texture, and depth) are examined, and single-cell studies relevant to filling-in are reviewed and assessed. Filling-in issues must be understood in relation to theoretical issues about neural–perceptual isomorphism and linking propositions. Six main conclusions are drawn: (1) visual filling-in comprises a multitude of different perceptual completion phenomena; (2) certain forms of visual completion seem to involve spatially propagating neural activity (neural filling-in) and so, contrary to Dennett's (1991; 1992) recent discussion of filling-in, cannot be described as results of the brain's “ignoring an absence” or “jumping to a conclusion”; (3) in certain cases perceptual completion seems to have measurable effects that depend on neural signals representing a presence rather than ignoring an absence; (4) neural filling-in does not imply either “analytic isomorphism” or “Cartesian materialism,” and thus the notion of the bridge locus – a particular neural stage that forms the immediate substrate of perceptual experience – is problematic and should be abandoned; (5) to reject the representational conception of vision in favor of an “enactive” or “animate” conception reduces the importance of filling-in as a theoretical category in the explanation of vision; and (6) the evaluation of perceptual content should not be determined by “subpersonal” considerations about internal processing, but rather by considerations about the task of vision at the level of the animal or person interacting with the world.

This target article draws together two groups of experimental studies on the control of human movement through peripheral feedback and centrally generated signals of motor commands. First, during natural movement, feedback from muscle, joint, and cutaneous afferents changes; in human subjects these changes have reflex and kinesthetic consequences. Recent psychophysical and microneurographic evidence suggests that joint and even cutaneous afferents may have a proprioceptive role. Second, the role of centrally generated motor commands in the control of normal movements and movements following acute and chronic deafferentation is reviewed. There is increasing evidence that subjects can perceive their motor commands under various conditions, but that this is inadequate for normal movement; deficits in motor performance arise when the reliance on proprioceptive feedback is abolished either experimentally or because of pathology. During natural movement, the CNS appears to have access to functionally useful input from a range of peripheral receptors as well as from internally generated command signals. The unanswered questions that remain suggest a number of avenues for further research.

The “radiator” theory of brain evolution is proposed to account for “mosaic evolution” whereby brain size began to increase rapidly in the genus Homo well over a million years after bipedalism had been selected for in early hominids. Because hydrostatic pressures differ across columns of fluid depending on orientation (posture), vascular systems of early bipeds became reoriented so that cranial blood flowed preferentially to the vertebral plexus instead of the internal jugular vein in response to gravity. The Hadar early hominids and robust australopithecines partly achieved this reorientation with a dramatically enlarged occipital/marginal sinus system. On the other hand, hominids in the gracile australopithecine through Homo lineage delivered blood to the vertebral plexus via a widespread network of veins that became more elaborate through time. Mastoid and parietal emissary veins are representatives of this network, and increases in their frequencies during hominid evolution are indicative of its development. Brain size increased with increased frequencies of mastoid and parietal emissary veins in the lineage leading to and including Homo, but remained conservative in the robust australopithecine lineage that lacked the network of veins. The brain is an extremely heatsensitive organ and emissary veins in humans have been shown to cool the brain under conditions of hyperthermia. Thus, the network of veins in the lineage leading to Homo acted as a radiator that released a thermal constraint on brain size. The radiator theory is in keeping with the belief that basal gracile and basal robust australopithecines occupied distinct niches, with the former living in savanna mosaic habitats that were subject to hot temperatures and intense solar radiation during the day.

The principles of sexual selection were used as an organizing framework for interpreting cross-national patterns of sex differences in mathematical abilities. Cross-national studies suggest that there are no sex differences in biologically primary mathematical abilities, that is, for those mathematical abilities that are found in all cultures as well as in nonhuman primates, and show moderate heritability estimates. Sex differences in several biologically secondary mathematical domains (i.e., those that emerge primarily in school) are found throughout the industrialized world. In particular, males consistently outperform females in the solving of mathematical word problems and geometry. Sexual selection and any associated proximate mechanisms (e.g., sex hormones) influence these sex differences in mathematical performance indirectly. First, sexual selection resulted in greater elaboration in males than in females of the neurocognitive systems that support navigation in three-dimensional space. Knowledge implicit in these systems reflects an understanding of basic Euclidean geometry, and may thus be one source of the male advantage in geometry. Males also use more readily than females these spatial systems in problem-solving situations, which provides them with an advantage in solving word problems and geometry. In addition, sex differences in social styles and interests, which also appear to be related in part to sexual selection, result in sex differences in engagement iii mathematics-related activities, thus further increasing the male advantage in certain mathematical domains. A model that integrates these biological influences with sociocultural influences on the sex differences in mathematical performance is presented in this article.

When cognitive neuropsychologists make inferences about the functional architecture of the normal mind from selective cognitive impairments they generally assume that the effects of brain damage are local, that is, that the nondamaged components of the architecture continue to function as they did before the damage. This assumption follows from the view that the components of the functional architecture are modular, in the sense of being informationally encapsulated. In this target article it is argued that this “locality” assumption is probably not correct in general. Inferences about the functional architecture can nevertheless be made from neuropsychological data with an alternative set of assumptions, according to which human information processing is graded, distributed, and interactive. These claims are supported by three examples of neuropsychological dissociations and a comparison of the inferences obtained from these impairments with and without the locality assumption. The three dissociations are: selective impairments in knowledge of living things, disengagment of visual attention, and overt face recognition. In all three cases, the neuropsychological phenomena lead to more plausible inferences about the normal functional architecture when the locality assumption is abandoned. Also discussed are the relations between the locality assumption in neuropsychology and broader issues, including Fodor's modularity hypothesis and the choice between top-down and bottom-up research approaches.

Beyond modularity attempts a synthesis of Fodor's anticonstructivist nativism and Piaget's antinativist constructivism. Contra Fodor, I argue that: (1) the study of cognitive development is essential to cognitive science, (2) the module/central processing dichotomy is too rigid, and (3) the mind does not begin with prespecified modules; rather, development involves a gradual process of “modularization.” Contra Piaget, I argue that: (1) development rarely involves stagelike domain-general change and (2) domainspecific predispositions give development a small but significant kickstart by focusing the infant's attention on proprietary inputs. Development does not stop at efficient learning. A fundamental aspect of human development (“representational redescription”) is the hypothesized process by which information that is in a cognitive system becomes progressively explicit knowledge to that system. Development thus involves two complementary processes of progressive modularization and progressive “explicitation.” Empirical findings on the child as linguist, physicist, mathematician, psychologist, and notator are discussed in support of the theoretical framework. Each chapter concentrates first on the initial state of the infant mind/brain and on subsequent domain-specific learning in infancy and early childhood. It then goes on to explore data on older children's problem solving and theory building, with particular focus on evolving cognitive flexibility. Emphasis is placed throughout on the status of representations underlying different capacities and on the multiple levels at which knowledge is stored and accessible. Finally, consideration is given to the need for more formal developmental models, and a comparison is made between representational redescription and connectionist simulations of development. In conclusion, I consider what is special about human cognition by speculating on the status of representations underlying the structure of behavior in other species.

The human species is more reliant on cultural adaptation than any other species, but it is unclear how observational learning can give rise to the faithful transmission of cultural adaptations. One possibility is that teaching facilitates accurate social transmission by narrowing the range of inferences that learners make. However, there is wide disagreement about how to define teaching, and how to interpret the empirical evidence for teaching across cultures and species. In this article I argue that disputes about the nature and prevalence of teaching across human societies and nonhuman animals are based on a number of deep-rooted theoretical differences between fields, as well as on important differences in how teaching is defined. To reconcile these disparate bodies of research, I review the three major approaches to the study of teaching – mentalistic, culture-based, and functionalist – and outline the research questions about teaching that each addresses. I then argue for a new, integrated framework that differentiates between teaching types according to the specific adaptive problems that each type solves, and apply this framework to restructure current empirical evidence on teaching in humans and nonhuman animals. This integrative framework generates novel insights, with broad implications for the study of the evolution of teaching, including the roles of cognitive constraints and cooperative dilemmas in how and when teaching evolves. Finally, I propose an explanation for why some types of teaching are uniquely human, and discuss new directions for research motivated by this framework.

We provide a threefold taxonomy of models in neurolinguistics: faculty models, which embrace the work of classical connectionists and holists and of such modern workers as Geschwind; process models, which are exemplified by the work of Luria, and which fractionate psycholinguistic tasks and ascribe the components to particular brain regions; and representational models, which use specific linguistic representations to build a psycholinguistic analysis of aphasic performance. We argue that further progress requires that neurolinguistics become more computational, using techniques from Artificial Intelligence to model the cooperative computation underlying language processing at a level of detail consonant with linguistic representations. Finally, we note that current neurolinguistics makes virtually no contact with the synapse-cell-circuit level of analysis characteristic of twentieth-century neuroscience. We suggest that the cooperative computation models we envisage provide the necessary intermediary between current neurolinguistic analysis and the utilization of the fruits of modern neuroanatomy, neurochemistry, and neurophysiology.

This critical appraisal of contemporary interpretations in the area of infantile attachment begins with an outline of the principal features of the Bowlby-Ainsworth ethological theory, the instrumental/operant learning theory of Gewirtz, and Hoffman's classical conditioning model. Some attention is also given to Cairns's contiguity learning analysis and the Hoffman-Solomon opponentprocess model Discussion of these theories is followed by a review of representative data from infants at four phyletic levels (precocial birds, dogs, monkeys, and human beings), with an emphasis on three aspects of social bonding: (a) the formation and persistence of social ties in the infant under conditions of maltreatment, (b) the role of the attachment object in the adjustment of the infant to the broader environment (the so-called secure base effect), and (c) the infant's reaction to involuntary separation from the attachment object.

An attempt is made to judge how well each of the interpretations accounts for all or part of the data, with the conclusion that current theories do not accord completely with documented attachment phenomena. The following criticisms are highlighted: Ethological theory emphasizes that infants' behavior systems have been shaped by the ordinarily expectable environment and depend on that environment for their functioning, yet infants of many species form bonds to objects not typical in any species' environment, or even to sources of maltreatment. Learning theory is faulted for making predictions contradicted by the maltreatment data and for a lack of formal mechanisms to account for the secure base and separation effects. The contiguity analysis is criticized for its inability to account for the emergence of certain response patterns during separation, and the opponent-process model is called into question because of its failure to fit important affective dynamics of social separation (a central focus of this theory). Recommendations for future theories of attachment are offered.

Advanced perceptual systems are faced with the problem of securing a principled (ideally, veridical) relationship between the world and its internal representation. I propose a unified approach to visual representation, addressing the need for superordinate and basic-level categorization and for the identification of specific instances of familiar categories. According to the proposed theory, a shape is represented internally by the responses of a small number of tuned modules, each broadly selective for some reference shape, whose similarity to the stimulus it measures. This amounts to embedding the stimulus in a low-dimensional proximal shape space spanned by the outputs of the active modules. This shape space supports representations of distal shape similarities that are veridical as Shepard's (1968) second-order isomorphisms (i.e., correspondence between distal and proximal similarities among shapes, rather than between distal shapes and their proximal representations). Representation in terms of similarities to reference shapes supports processing (e.g., discrimination) of shapes that are radically different from the reference ones, without the need for the computationally problematic decomposition into parts required by other theories. Furthermore, a general expression for similarity between two stimuli, based on comparisons to reference shapes, can be used to derive models of perceived similarity ranging from continuous, symmetric, and hierarchical ones, as in multidimensional scaling (Shepard 1980), to discrete and nonhierarchical ones, as in the general contrast models (Shepard & Arabie 1979; Tversky 1977).

We present a general framework for analyzing the contribution to reproductive success of a behavioural action. An action may make a direct contribution to reproductive success, but even in the absence of a direct contribution it may make an indirect contribution by changing the animal's state. We consider actions over a period of time, and define a reward function that characterizes the relationship between the animal's state at the end of the period and its future reproductive success. Working back from the end of the period using dynamic programming, the optimal action as a function of state and time can be found. The procedure also yields a measure of the cost, in terms of future reproductive success, of a suboptimal action. These costs provide us with a common currency for comparing activities such as eating and drinking, or eating and hiding from predators. The costs also give an indication of the robustness of the conclusions that can be drawn from a model. We review how our framework can be used to analyze optimal foraging decisions in a stochastic environment. We also discuss the modelling of optimal daily routines and provide an illustration based on singing to attract a mate. We use the model to investigate the features that can produce a dawn song burst in birds. State is defined very broadly so that it includes the information an animal has about its environment. Thus, exploration and learning can be included within the framework.

Psychological adaptation underlies all human behavior. Thus, sexual coercion by men could either arise from a rape-specific psychological adaptation or it could be a side-effect of a more general psychological adaptation not directly related to rape. Determining the specific environmental cues that men's brains have been designed by selection to process may help us decide which these rival explanations is correct. We examine six testable predictions against existing data: (1) Both coercive and noncoercive will be associated with high levels of sexual arousal and performance in men. (2) Achieving physical control of a sexually unwilling woman will be sexually arousing to men. (3) Young men will be more sexually coercive than older men. (4) Men of low socioeconomic status will likewise be more sexually coercive. (5) A man's motivation to use sexual coercion will be influenced by its effects on social image. (6) Even in long-term relationships men will be motivated to use coercion when their mates show a lack of interest in resistance to sex because these are interpreted as signs of sexual infidelity. Current data support all six predictions and are hence consistent with the rape-specific hypothesis, but this does not eliminate the side-effect hypothesis, which is likewise compatible with the findings, as well as with the further evidence that forced matings increased the fitness of ancestral males during human evolution. We suggest some research that may help decide between the two hypotheses.

To what extent, if any, does Universal Grammar (UG) constrain second language (L2) acquisition? This is not only an empirical question, but one which is currently investigable. In this context, L2 acquisition is emerging as an important new domain of psycholinguistic research. Three logical possibilities have been articulated regarding the role of UG in L2 acquisition: The first is the “no access” hypothesis that claims that no aspect of UG is available to the L2 learner. The second is the “partial access” hypothesis that claims that only LI instantiated principles and LI instantiated parameter-values of UG are available to the learner. The third, called the “full access” hypothesis, asserts that UG in its entirety constrains L2 acquisition.

In this paper we argue that there is no compelling evidence to support either of the first two hypotheses. Moreover, we provide evidence concerning functional categories in L2 acquisition consistent with the claim that UG is fully available to the L2 learner (see also Flynn 1987; Li 1993; Martohardjono 1992; Schwartz & Sprouse 1991; Thomas 1991; White 1989). In addition, we will attempt to clarify some of currently unclear theoretical issues that arise with respect to positing UG as an explanatory theory of L2 acquisition. We will also investigate in some detail certain crucial methodological questions involved in experimentally testing the role of UG in L2 acquisition and finally, we will present a set of experimental results of our own supporting the “Full Access” hypothesis.

Effective conditioning requires a correlation between the experimenter's definition of a response and an organism's, but an animal's perception of its behavior differs from ours. These experiments explore various definitions of the response, using the slopes of learning curves to infer which comes closest to the organism's definition. The resulting exponentially weighted moving average provides a model of memory that is used to ground a quantitative theory of reinforcement. The theory assumes that: incentives excite behavior and focus the excitement on responses that are contemporaneous in memory. The correlation between the organism's memory and the behavior measured by the experimenter is given by coupling coefficients, which are derived for various schedules of reinforcement. The coupling coefficients for simple schedules may be concatenated to predict the effects of complex schedules. The coefficients are inserted into a generic model of arousal and temporal constraint to predict response rates under any scheduling arrangement. The theory posits a response-indexed decay of memory, not a time-indexed one. It requires that incentives displace memory for the responses that occur before them, and may truncate the representation of the response that brings them about. As a contiguity-weighted correlation model, it bridges opposing views of the reinforcement process. By placing the short-term memory of behavior in so central a role, it provides a behavioral account of a key cognitive process.

Most people who are regular consumers of psychoactive drugs are not drug addicts, nor will they ever become addicts. In neurobiological theories, non-addictive drug consumption is acknowledged only as a “necessary” prerequisite for addiction, but not as a stable and widespread behavior in its own right. This target article proposes a new neurobiological framework theory for non-addictive psychoactive drug consumption, introducing the concept of “drug instrumentalization.” Psychoactive drugs are consumed for their effects on mental states. Humans are able to learn that mental states can be changed on purpose by drugs, in order to facilitate other, non-drug-related behaviors. We discuss specific “instrumentalization goals” and outline neurobiological mechanisms of how major classes of psychoactive drugs change mental states and serve non-drug-related behaviors. We argue that drug instrumentalization behavior may provide a functional adaptation to modern environments based on a historical selection for learning mechanisms that allow the dynamic modification of consummatory behavior. It is assumed that in order to effectively instrumentalize psychoactive drugs, the establishment of and retrieval from a drug memory is required. Here, we propose a new classification of different drug memory subtypes and discuss how they interact during drug instrumentalization learning and retrieval. Understanding the everyday utility and the learning mechanisms of non-addictive psychotropic drug use may help to prevent abuse and the transition to drug addiction in the future.

Converging data from different disciplines indicate that central nervous system processes are capable of influencing immune responses. This paper concentrates on recent studies documenting behaviorally conditioned suppression and enhancement of immunity. Exposing rats or mice to a conditioned stimulus previously paired with an immunomodulating agent results in alterations in humoral and cell-mediated immune responses to antigenic stimuli, and unreinforced reexposures to the conditioned stimuli result in extinction of the conditioned response. Although the magnitude of such conditioning effects has not been large, the phenomenon has been independently verified under a variety of experimental conditions. The biological impact of conditioned alterations in immune function is illustrated by studies in which conditioning operations were applied in the pharmacotherapy of autoimmune disease in New Zealand mice. In conditioned animals, substituting conditioned stimuli for active drugs delays the onset of autoimmune disease relative to nonconditioned animals using a dose of immunosuppressive drug that, by itself, is ineffective in modifying the progression of disease. The hypothesis that such conditioning effects are mediated by elevations in adrenocortical steroid levels receives no support from available data. Despite its capacity for self-regulation, it appears that the immune system is integrated with other psychophysiological processes and subject to modulation by the brain.

Purely parallel neural networks can model object recognition in brief displays – the same conditions under which illusory conjunctions (the incorrect combination of features into perceived objects in a stimulus array) have been demonstrated empirically (Treisman 1986; Treisman & Gelade 1980). Correcting errors of illusory conjunction is the “tag-assignment” problem for a purely parallel processor: the problem of assigning a spatial tag to nonspatial features, feature combinations, and objects. This problem must be solved to model human object recognition over a longer time scale. Our model simulates both the parallel processes that may underlie illusory conjunctions and the serial processes that may solve the tag-assignment problem in normal perception. One component of the model extracts pooled features and another provides attentional tags that correct illusory conjunctions. Our approach addresses two questions: (i) How can objects be identified from simultaneously attended features in a parallel, distributed representation? (ii) How can the spatial selectional requirements of such an attentional process be met by a separation of pathways for spatial and nonspatial processing? Our analysis of these questions yields a neurally plausible simulation of tag assignment based on synchronizing feature processing activity in a spatial focus of attention.