Goldstein reported multiple cases of failure to categorise colours in patients that he termed amnesic or anomic aphasics. These patients have a particular difficulty in producing perceptual categories in the absence of other aphasic impairments. We hold that neuropsychological evidence supports the view that the task of colour categorisation is logically impossible without labels.

The aim of this paper is to clarify and critically assess the methods of evolutionary psychology, and offer a sketch of an alternative methodology. My thesis is threefold. (1) The methods of inquiry unique to evolutionary psychology rest upon the claim that the discovery of theadaptive functions of ancestral psychological capacities leads to the discovery of thepsychological functions of those ancestral capacities. (2) But this claim is false; in fact, just the opposite is true. We first must discover the psychological (...) functions of our psychological capacities in order to discover their adaptive functions. Hence the methods distinctive of evolutionary psychology are idle in our search for the mechanisms of the mind. (3) There are good reasons for preferring an alternative to the methods of evolutionary psychology, an alternative that aims to discover the functions of our psychological capacities by appeal to the concept of awhole psychology. (shrink)

A critical discussion is provided of three central assumptions underlying Nunez's approach to modeling cortical activity. A plea is made for neurophysiologically realistic models involving nonlinearities, multiple time scales, and stochasticity.

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...) convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)

This paper uses the economic crisis of 2008 as a case study to examine the explanatory validity of collective mental representations. Distinguished economists such as Paul Krugman and Joseph Stiglitz attribute collective beliefs, desires, intentions, and emotions to organizations such as banks and governments. I argue that the most plausible interpretation of these attributions is that they are metaphorical pointers to a complex of multilevel social, psychological, and neural mechanisms. This interpretation also applies to collective knowledge in science: scientific communities (...) do not literally have collective representations, but social mechanisms do make important contributions to scientific knowledge. (shrink)

Network analysis is increasingly used to discover and represent the organization of complex systems. Focusing on examples from neuroscience in particular, I argue that whether network models explain, how they explain, and how much they explain cannot be answered for network models generally but must be answered by specifying an explanandum, by addressing how the model is applied to the system, and by specifying which kinds of relations count as explanatory.

We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...) causes can be translated into mechanistically mediated effects, the posited relationship is intelligible and should raise no special philosophical objections. When they cannot, they are suspect. (shrink)

It is common to defend the Homeostatic Property Cluster ( HPC ) view as a third way between conventionalism and essentialism about natural kinds ( Boyd , 1989, 1991, 1997, 1999; Griffiths , 1997, 1999; Keil , 2003; Kornblith , 1993; Wilson , 1999, 2005; Wilson , Barker , & Brigandt , forthcoming ). According to the HPC view, property clusters are not merely conventionally clustered together; the co-occurrence of properties in the cluster is sustained by a similarity generating ( (...) or homeostatic ) mechanism . I argue that conventional elements are involved partly but ineliminably in deciding which mechanisms define kinds , for deciding when two mechanisms are mechanisms of the same type, and for deciding where one particular mechanism ends and another begins. This intrusion of conventional perspective into the idea of a mechanism raises doubts as to whether the HPC view is sufficiently free of conventional elements to serve as an objective arbiter in scientific disputes about what the kinds of the special sciences should be. (shrink)

The study of signed languages has inspired scientific' speculation regarding foundations of human language. Relationships between the acquisition of sign language in apes and man are discounted on logical grounds. Evidence from the differential hreakdown of sign language and manual pantomime places limits on the degree of overlap between language and nonlanguage motor systems. Evidence from functional magnetic resonance imaging reveals neural areas of convergence and divergence underlying signed and spoken languages.

I enlarge on the theme that the brain mechanisms required for languageand other aspects of the human mind evolved through selective changes in the regulatory genes governing growth. Extension of the period of postnatal growth increases the role of the environment in structuring the brain, and spatiotemporal programming (heterochrony) ofgrowth might explain hierarchical representation, hemispheric specialization, and perhaps sex differences.

In this paper I put forward a reconstruction of the evolution of certain explanatory hypotheses on the neural basis of association and learning that are the premises of connectionism in the cybernetic age and of present-day connectionism. The main point of my reconstruction is based on two little-known case studies. The first is the project, published in 1913, of a hydraulic machine through which its author believed it was possible to simulate certain essential elements of the plasticity of nervous connections. (...) The author, S. Bent Russell, was an engineer deeply influenced by the neurological hypotheses on nervous conduction of Herbert Spencer, Max Meyer and Edward L. Thorndike. The second is the project, published in 1929, of an electromechanical machine in which the author, the psychologist J.M. Stephens, believed it was possible to embody Thorndike's law of effect. Thus both Bent Russell and Stephens referred to the principles of learning that Thorndike defined as connectionist . Their attempt was that of simulating by machines at least certain simple aspects of inhibition, association and habit formation that are typical of living organisms. I propose to situate their projects within the frame of thediscovery of a simulative (modelling) methodology which I believe might be considered an important topic of the Culture of the Artificial . Certain more recent steps toward such a methodology made by both connectionism of the 1950s and present-day connectionism are briefly pointed out in the paper. (shrink)

According to John Haugeland, the capacity for “authentic intentionality” depends on a commitment to constitutive standards of objectivity. One of the consequences of Haugeland’s view is that a neurocomputational explanation cannot be adequate to understand “authentic intentionality”. This paper gives grounds to resist such a consequence. It provides the beginning of an account of authentic intentionality in terms of neurocomputational enabling conditions. It argues that the standards, which constitute the domain of objects that can be represented, reflect the statistical structure (...) of the environments where brain sensory systems evolved and develop. The objection that I equivocate on what Haugeland means by “commitment to standards” is rebutted by introducing the notion of “florid, self-conscious representing”. Were the hypothesis presented plausible, computational neuroscience would offer a promising framework for a better understanding of the conditions for meaningful representation. (shrink)

How should we understand the claim that people comply with social norms because they possess the right kinds of beliefs and preferences? I answer this question by considering two approaches to what it is to believe (and prefer), namely: representationalism and dispositionalism. I argue for a variety of representationalism, viz. neural representationalism. Neural representationalism is the conjunction of two claims. First, what it is essential to have beliefs and preferences is to have certain neural representations. Second, neural representations are often (...) necessary to adequately explain behaviour. After having canvassed one promising way to understand what neural representations could be, I argue that the appeal to beliefs and preferences in explanations of paradigmatic cases of norm compliance should be understood as an appeal to neural representations. (shrink)

Can facts about subpersonal states and events be constitutively relevant to personal-level phenomena? And can knowledge of these facts inform explanations of personal-level phenomena? Some philosophers, like Jennifer Hornsby and John McDowell, argue for two negative answers whereby questions about persons and their behavior cannot be answered by using information from subpersonal psychology. Knowledge of subpersonal states and events cannot inform personal-level explanation such that they cast light on what constitutes persons’ behaviors. In this paper I argue against this position. (...) After having distinguished between enabling and constitutive relevance, I defend the claim that at least some facts about subpersonal states and events are constitutively relevant to some personal-level phenomenon, and therefore can, and sometimes should, inform personal-level explanations. I draw some of the possible consequences of my claim for our understanding of personal-level behavior by focusing on the phenomenon of addiction. (shrink)

Can facts about subpersonal states and events be constitutively relevant to personal-level phenomena? And can knowledge of these facts inform explanations of personal-level phenomena? Some philosophers, like Jennifer Hornsby and John McDowell, argue for two negative answers whereby questions about persons and their behavior cannot be answered by using information from subpersonal psychology. Knowledge of subpersonal states and events cannot inform personal-level explanation such that they cast light on what constitutes persons? behaviors. In this paper I argue against this position. (...) After having distinguished between enabling and constitutive relevance, I defend the claim that at least some facts about subpersonal states and events are constitutively relevant to some personal-level phenomenon, and therefore can, and sometimes should, inform personal-level explanations. I draw some of the possible consequences of my claim for our understanding of personal-level behavior by focusing on the phenomenon of addiction. (shrink)

Recent work in cognitive science highlights the importance of exem- plar-based know-how in supporting human expertise. Influenced by this model, certain accounts of moral knowledge now stress exemplar- based, non-sentential know-how at the expense of rule-and-principle based accounts. I shall argue, however, that moral thought and reason cannot be understood by reference to either of these roles alone. Moral cognition – like other forms of ‘advanced’ cognition – depends crucially on the subtle interplay and interaction of multiple factors and forces (...) and especially (or so I argue) between the use of linguistic tools and formulations and more biologically basic forms of thought and reason. (shrink)

Recent studies such as Thelen and Smith, Kelso, Van Gelder, Beer, and others have presented a forceful case for a dynamical systems approach to understanding cognition and adaptive behavior. These studies call into question some foundational assumptions concerning the nature of cognitive scientific explanation and the role of notions such as internal representation and computation. These are exciting and important challenges. But they must be handled with care. It is all to easy in this debate to lose sight of the (...) explanatorily important issues and to talk at cross purposes, courtesy of the various ways in which different theorists often concieve key terms. (shrink)

Marinov''s critique I argue, is vitiated by its failure to recognize the distinctive role of superposition within the distributed connectionist paradigm. The use of so-called subsymbolic distributed encodings alone is not, I agree, enough to justify treating distributed connectionism as a distinctive approach. It has always been clear that microfeatural decomposition is both possible and actual within the confines of recognizably classical approaches. When such approaches also involve statistically-driven learning algorithms — as in the case of ID3 — the fundamental (...) differences become even harder to spot. To see them, it is necessary to consider not just the nature of an acquired input-output function but the nature of the representational scheme underlying it. Differences between such schemes make themselves best felt outside the domain of immediate problem solving. It is in the more extended contexts of performance DURING learning and cognitive change as a result of SUBSEQUENT training on new tasks (or simultaneous training on several tasks) that the effects of superpositional storage techniques come to the fore. I conclude that subsymbols, distribution and statistically driven learning alone are indeed not of the essence. But connectionism is not just about subsymbols and distribution. It is about the generation of whole subsymbol SYSTEMS in which multiple distributed representations are created and superposed. (shrink)

Connectionism and classicism, it generally appears, have at least this much in common: both place some notion of internal representation at the heart of a scientific study of mind. In recent years, however, a much more radical view has gained increasing popularity. This view calls into question the commitment to internal representation itself. More strikingly still, this new wave of anti-representationalism is rooted not in armchair theorizing but in practical attempts to model and understand intelligent, adaptive behavior. In this paper (...) we first present, and then critically assess, a variety of recent anti-representationalist treatments. We suggest that so far, at least, the sceptical rhetoric outpaces both evidence and argument. Some probable causes of this premature scepticism are isolated. Nonetheless, the anti-representationalist challenge is shown to be both important and progressive insofar as it forces us to see beyond the bare representational/non-representational dichotomy and to recognize instead a rich continuum of degrees and types of representationality. (shrink)

Drawing on the findings of neuroscience, this text proposes and defends the hypothesis that the various modalities of sensation share a generic form that the author, Austen Clark, calls feature-placing.

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

Does the Wright & Liley model predict: (1) that subdural and hippocampal EEGs coherence tend to rise and fall in parallel for many frequencies, (2) that it is locally high or low within 10mm and falls steeply on average or, (3) that it is in constant flux, mostly rising and falling within 5–15 sec?

Müller argues that double dissociations do not imply underlying modularity of the cognitive system, citing neural networks as examples of fully distributed systems that can give rise to double dissociations. We challenge this claim, noting that suchdouble dissociations typically do not “scale-up,” and that even some singledissociations can be difficult to account for in a distributed system.

A fundamental claim associated with parallel distributed processing theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts, that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned (...) in connectionist models and neural coding in brain and often dismiss localist theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models. (shrink)

As opposed to the dismissive attitude toward reductionism that is popular in current philosophy of mind, a “ruthless reductionism” is alive and thriving in “molecular and cellular cognition”—a field of research within cellular and molecular neuroscience, the current mainstream of the discipline. Basic experimental practices and emerging results from this field imply that two common assertions by philosophers and cognitive scientists are false: (1) that we do not know much about how the brain works, and (2) that lower-level neuroscience cannot (...) explain cognition and complex behavior directly. These experimental practices involve intervening directly with molecular components of sub-cellular and gene expression pathways in neurons and then measuring specific behaviors. These behaviors are tracked using tests that are widely accepted by experimental psychologists to study the psychological phenomenon at issue (e.g., memory, attention, and perception). Here I illustrate these practices and their importance for explanation and reduction in current mainstream neuroscience by describing recent work on social recognition memory in mammals. (shrink)

Neurobiologists talk of linking mind to molecular dynamics in and between neurons. Such talk is dismissed by cognitive scientists, including many cognitive neuroscientists, due to the number of “levels” that separate behaviors from these molecular events. In this paper I explain what neurobiologists mean by such claims by describing the kinds of experiment tools that have forged these linkages, directly on lab benches. I here focus on one of these tools, gene targeting techniques, brought into behavioral neuroscience from developmental biology (...) more than a quarter-century ago. Discussion of this tool does more than illuminate these claims by neurobiologists, however. An account of its development shows the doubly dependent role that theory plays in neurobiology. Our best current theories about “how the brain works” depend entirely on the experiment tools neuroscientists have available. And these tools get developed via the solution of engineering problems, not the application of theory. Theory is thus of tertiary importance in neuroscience, not of the primary importance that many cognitive scientists assume it to occupy. (shrink)

Müller misconstrues autonomy to mean strict locality of brain function, something quite different from the functional autonomy that linguists claim. Similarly, he misperceives the interaction of learned and innate components hypothesized in current generative models. Evidence from sign languages, Creole languages, and neurological studies of rare forms of aphasia also argues against his conclusions.

Long‐term modification of synaptic strength is thought to be the basic mechanism underlying the activity‐dependent refinement of neural circuits and the formation of memories engrammed on them. Studies ranging from cell culture preparations to humans subjects indicate that the decision of whether a synapse will undergo strengthening or weakening critically depends on the temporal order of presynaptic and postsynaptic activity. At many synapses, potentiation will be induced only when the presynaptic neuron fires an action potential within milliseconds before the postsynaptic (...) neuron fires, whereas weakening will occur when it is the postsynaptic neuron that fires first. Such processes might be important for the remodeling of neural circuits by activity during development and for network functions such as sequence learning and prediction. Ultimately, this synaptic property might also be fundamental for the cognitive process by which we structure our experience through cause and effect relations. BioEssays 24:212–222, 2002. © 2002 Wiley Periodicals, Inc.; DOI 10.1002/bies.10060. (shrink)

The distinction between occurrent and non-occurrent mental states is frequently appealed to by contemporary philosophers, but it has never been explicated in any significant detail. In the literature, two accounts of the distinction are commonly presupposed. One is that occurrent states are conscious states. The other is that non-occurrent states are dispositional states, and thus that occurrent states are manifestations of dispositions. I argue that neither of these accounts is adequate, and therefore that another account is needed. I propose that (...) occurrent states are active states. (shrink)

Modern biology has not yet come to terms with the presence of many organic codes in Nature, despite the fact that we can prove their existence. As a result, it has not yet accepted the idea that the great events of macroevolution were associated with the origin of new organic codes, despite the fact that this is the most parsimonious and logical explanation of those events. This is probably due to the fact that the existence of organic codes in all (...) fundamental processes of life, and in all major transitions in the history of life, has enormous theoretical implications. It requires nothing less than a new theoretical framework, and that kind of change is inevitably slow. There are too many facts to reconsider, too many bits of history to weave together in a new mosaic. But this is what science is about, and the purpose of the present paper is to show that it can be done. More precisely, it is shown that the whole natural history of the brain can be revisited in the light of the organic codes. What is described here is only a bird’s-eye view of brain macroevolution, but it is hoped that the extraordinary potential of the organic codes can nevertheless come through. The paper contains also another message. The organic codes prove that life is based on semiosis, and are in fact the components of organic semiosis, the first and the most diffused form of semiosis on Earth, but not the only one. It will be shown that the evolution of the brain was accompanied by the development of two new types of sign processes. More precisely, it gave origin first to interpretive semiosis, mostly in vertebrates, and then to cultural semiosis, in our species. (shrink)

Sciences able to identify appropriate analytical units for their domain, their natural kinds, have tended to be more progressive. In the biological sciences, evolutionary natural kinds are adaptations that can be identified by their common history of selection for some function. Human brains are the product of an evolutionary history of selection for component systems which produced behaviours that gave adaptive advantage to their hosts. These structures, behaviour production systems, are the natural kinds that psychology seeks. We argue these can (...) be identified deductively by classing behaviour first according to its level of behavioural control. Early animals in our lineage used only reactive production, Vertebrates evolved motivation, and later Primates developed executive control. Behaviour can also be classified by the type of evolutionary benefit it bestows: it can deliver either immediate benefits (food, gametes), improvements in the individual’s position with respect to the world (resource access, social status), or improvements in the ability to secure future benefits (knowledge, skill). Combining history and function implies the existence of seven types of behaviour production systems in human brains responsible for reflexive, instinctual, exploratory, driven, emotional, playful and planned behaviour. Discovering scientifically valid categories of behaviour can provide a fundamental taxonomy and common language for understanding, predicting and changing behaviour, and a way of discovering the organs in the brain––its natural kinds––that are responsible for behaviour. (shrink)

Analyzing the outline of the endless literature on consciousness, the separation between science and philosophy rather than being overcome, seems to come back in different shapes. According to this point of view, the hard problem seems to be how to study consciousness while avoiding a slip back to the old dualism. This article outlines the advantages of the phenomenological method. This method, more than getting over the mind-body separation, anticipates it through an open gaze, able to bring back the human (...) presence as something structurally “ambiguous.” Reintroducing Husserl's scientific project in a complete way, Francisco Varela opened up a research area yet to be explored, which promises to be fertile for neuroscience, provided that we accept that radicalism essential to phenomenology. (shrink)

An argument is offered for this conditional: If our current concept conscious state is sharp rather than vague, and also correct , then common versions of familiar metaphysical theories of consciousness are false--?namely versions of the identity theory, functionalism, and dualism that appeal to complex physical or functional properties in identification, realization, or correlation. Reasons are also given for taking seriously the claim that our current concept conscious state is sharp. The paper ends by surveying the theoretical options left open (...) by the concept's sharpness and the truth of the conditional argued for in the paper. (shrink)

Some concepts relating to learned, structured functioning of local modules in neocortex are clarified in order to ensure that the integration from the small scale to the global attempted by Wright & Liley does not miss the target.

In this chapter, I critically examine two of the main approaches to colour categorization in cognitive science: the perceptual salience theory and linguistic relativism. I then turn to reviewing several decades of psychological research on colour categorical perception (CP). A careful assessment of relevant findings suggests that most of the experimental effects that have been understood in terms of CP actually fall on the cognition side of the perception-cognition divide: they are effects of colour language, for example, on memory or (...) decision-making. (shrink)

Chomskyian claims of a genetically hard-wired and cognitively autonomous “universal grammar” are being promoted by generative linguistics as facts about language to the present day. The related doctrine of an evolutionary discontinuity in language emergence, however, is based on misconceptions about the notions of homology and preadaptation. The obvious lack of equivalence between symbolic communicative capacities in existing nonhuman primates and human language does not preclude common roots. Normal and disordered language development is strongly influenced by the genome, but there (...) is no evidence for the existence of specific genes underlying “universal grammar.” In the mature brain, stages of language processing can be distinguished and “first-pass” syntactic analyses appear to precede semantic decoding. However, this partial seriality – as well as behavioral and clinical dissociations between lexical and functional categories – can be best described, not in terms of serially activated and discrete modules, but in terms of classes of cell assemblies that differ in their distributional properties. Whereas cell assemblies involved in semantic interpretation (“content word” assemblies) are widely distributed and are generally less vulnerable to focal lesion, those involved in structural decoding (functor assemblies) are primarily distributed within the left perisylvian cortices and are selectively vulnerable to left perisylvian lesion. These distributional differences are explained in terms of the perceptuomotor components involved in the acquisition of relevant representations. The emerging “motivated” or “toposemantic” brain regional specificity can only be accommodated with “soft” and maturational versions of modularity. The failure to reproduce double dissociations in current connectionist models is due to overly simple neuroscientific assumptions, notably that of overall equipotentiality. Linguistic models should not be expected to be “implemented” in the brain, but need to be constrained by neuroscientific evidence on how biological brains function. (shrink)

Contrary to Müller's claims, and in support of modular theories, genetic factors play a substantial and significant role in language. The finding that some children with specific language impairment (SLI) have nonlinguistic impairments may reflect improper diagnosis of SLI or impairments that are secondary to linguistic impairments. Thus, such findings do not argue against the modularity thesis. The lexical/functional distinction appears to be innate and specifically linguistic and could be instantiated in either symbolic or connectionist systems.

The belief that syntax is an innate, autonomous, species-specific module is highly questionable. Syntax demonstrates the mosaic nature of evolutionary change, in that it made use of (and led to the enhancement of) numerous preexisting neurocognitive features. It is best understood as an emergent characteristic of the explosion of semantic complexity that occurred during hominid evolution.

Müller's target article aims to summarize approaches to the question of how language elements (phonemes, morphemes, etc.) and rules are laid down in the brain. However, it suffers from being too vague about basic assumptions and empirical predictions of neurobiological models, and the empirical evidence available to test the models is not appropriately evaluated. (1) In a neuroscientific model of language, different cortical localizations of words can only be based on biological principles. These need to be made explicit. (2) Evidence (...) for and against word class differences could be evaluated more rigorously. (3) All (and only) humans are able to learn languages with complex syntactic structures; it is, therefore, not appropriate to deny innateness and universality of syntactic principles. The real question appears to be the following: Which neurobiological principles are the linguistic principles based on? (shrink)

The concepts of the innateness, universality, species-specificity, and autonomy of the human language capacity have had an extreme impact on the psycholinguistic debate for over thirty years. These concepts are evaluated from several neurobiological perspectives, with an emphasis on the emergence of language and its decay due to brain lesion and progressive brain disease.Evidence of perceptuomotor homologies and preadaptations for human language in nonhuman primates suggests a gradual emergence of language during hominid evolution. Regarding ontogeny, the innate component of language (...) capacity is likely to be polygenic and shared with other developmental domains. Dissociations between verbal and nonverbal development are probably rooted in the perceptuomotor specializations of neural substrates rather than the autonomy of a grammar module. Aphasiologicaldata often assumed to suggest modular linguistic subsystems can be accounted for in terms of a neurofunctional model incorporating perceptuomotor-based regional specializationsand distributivity of representations. Thus, dissociations between grammatical functors and content words are due to different conditions of acquisition and resulting differences in neural representation. Human brains are characterized by multifactorial interindividual variability, and strict universality of functional organization is biologically unrealistic.A theoretical alternative is proposed according to which (1) linguistic specialization of brain areas is due to epigenetic and probabilistic maturational events, not to genetic ”hard-wiring,” and (2) linguistic knowledge is neurally represented in distributed cell assemblies whose topography reflects the perceptuomotor modalities involved in the acquisition and use of a given item of knowledge. (shrink)

The philosophical innateness debate has long relied onpsychological evidence. For a century, however, a parallel debate hastaken place within neuroscience. In this paper, I consider theimplications of this neuroscience debate for the philosophicalinnateness debate. By combining the tools of theoretical neurobiologyand learning theory, I introduce the ``problem of development'' that alladaptive systems must solve, and suggest how responses to this problemcan demarcate a number of innateness proposals. From this perspective, Isuggest that the majority of natural systems are in fact innate. (...) Lastly,I consider the acquistion strategies implemented by the human brain andsuggest that there is a rigorous way of characterizing these ``neuralconstructivist'' strategies as not being strongly innate. Alternatives toinnateness are thus both rigorously definable and empirically supported. (shrink)

This chapter describes the conceptual foundations of cognitive science during its establishment as a science in the 20th century. It is organized around the core ideas of individual agency as its basic explanans and information-processing as its basic explanandum. The latter consists of a package of ideas that provide a mathematico-engineering framework for the philosophical theory of materialism.

The network model of EEG formation has revealed a unified mechanism for disparate EEG phenomena: for various reactions as well as for ontogenetic and phylogenetic differences. EEG rhythmicity was shown to be an external manifestation of the functioning of the intracortical stabilizing system which provides normal informational operations in the cerebral cortex.