Neurobiological models of language need a level of analysis that can account for the typical range of language phenomena. Because linguistically motivated models have been successful in explaining numerous language properties, it is premature to dismiss them as biologically irrelevant. Models attempting to unify neurobiology and linguistics need to be sensitive to both sources of evidence.

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.

Müller argues that general cognitive skills and linguistic skills are not necessarily independent. However, cross-linguistic evidence from an inherited specific language disorder affecting productive rules suggests significant degrees of modularity, innateness, and universality of language. Confident claims about the overall nature of such a complex system still await more interdisciplinary research.

The relevance of Wolfgang K hler's psychoneural isomorphism principle to contemporary cognitive neuroscience is explored. K hler's approach to the mind—body problem is interpreted as a response to the foundational crisis of psychology at the beginning of the twentieth century. Some aspects of his isomorphism doctrine are discussed, with a view to reaching an interpretation that is both historically accurate and pertinent to issues currently debated in the philosophy of psychology. The principle was meant to be empirically verifiable. Accordingly, some (...) similarities between K hler's approach and current neural network modeling are pointed out, and it is shown that some recent trends in the neurosciences are broadly compatible with K hler's views on cortical functioning. Isomorphism is interpreted as a form of neuroreductionism constrained by bridging laws relating mental phenomena to macrosocopic parameters of neural function. While isomorphism is probably valid for perceptual phenomena, its applicability to higher mental processes remains doubtful. (shrink)

The nominalistic ontology of Kotarbinski, Slupecki and Tarski does not provide any direct interpretations of the sets of higher types which play important roles in type theory and in set theory. For this and other reasons I will interpret those theories as descriptions of some finite structures which are actually constructed in human imaginations and stored in their memories. Those structures will be described in this lecture. They are hinted by the idea of Skolem functions and Hilbert's -symbols, and they (...) constitute a finitistic modification of Tarski's concept of a model. They suggest also a form of the evolutionary process which leads to the development of human intelligence and language. (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.

Evidence is presented from a polyglot savant to suggest that double dissociations between linguistic and nonverbal abilities are more important than Müller's target article implies. It is also argued that the special nature of syntax makes its assimilation to other aspects of language or to nonhuman communication systems radically implausible.

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.

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)

This paper examines whether a classical model could be translated into a PDP network using a standard connectionist training technique called extra output learning. In Study 1, standard machine learning techniques were used to create a decision tree that could be used to classify 8124 different mushrooms as being edible or poisonous on the basis of 21 different Features (Schlimmer, 1987). In Study 2, extra output learning was used to insert this decision tree into a PDP network being trained on (...) the identical problem. An interpretation of the trained network revealed a perfect mapping from its internal structure to the decision tree, representing a precise translation of the classical theory to the connectionist model. In Study 3, a second network was trained on the mushroom problem without using extra output learning. An interpretation of this second network revealed a different algorithm for solving the mushroom problem, demonstrating that the Study 2 network was indeed a proper theory translation. (shrink)

To begin, I introduce an analysis of interlevel relations that allows us to offer an initial characterization of the debate about the way classical and connectionist models relate. Subsequently, I examine a compatibility thesis and a conditional claim on this issue.With respect to the compatibility thesis, I argue that, even if classical and connectionist models are not necessarily incompatible, the emergence of the latter seems to undermine the best arguments for the Language of Thought Hypothesis, which is essential to the (...) former. (shrink)

The distinction between analog and digital representation is reexamined; it emerges that a more fundamental distinction is that between symbolic and analog simulation. Analog simulation is analyzed in terms of a (near) isomorphism of causal structures between a simulating and a simulated process. It is then argued that a core concept, naturalistic analog simulation, may play a role in a bottom-up theory of adaptive behavior which provides an alternative to representational analyses. The appendix discusses some formal conditions for naturalistic analog (...) simulation. (shrink)

In this paper I assess the explanatory role of internal representations in connectionist models of cognition. Focusing on both the internal‘hidden’units and the connection weights between units, I argue that the standard reasons for viewing these components as representations are inadequate to bestow an explanatorily useful notion of representation. Hence, nothing would be lost from connectionist accounts of cognitive processes if we were to stop viewing the weights and hidden units as internal representations.

One can disagree with Müller that it is neurobiologically questionable to suppose that human language is innate, specialized, and species-specific, yet agree that the precise brain mechanisms controlling language in any individual will be influenced by epigenesis and genetic variability, and that the interplay between inherited and acquired aspects of linguistic capacity deserves to be investigated.

Müller provides a valuable synthesis of neurobiological evidence on the epigenetic development of neural structures involved in language acquisition. The pluripotentiality of developing neural tissue crucially constrains linguistic/cognitive theorizing about supposedly innate neural mechanisms and contributes significantly to our understanding of experience–dependent processes involved in language acquisition. Without this understanding, any proposed explanation of language acquisition is suspect.

In this paper I describe basic features of traditional (British) emergentism and Popper’s emergentist theory of consciousness and compare them to the contemporary versions of emergentism present in connectionist approach in cognitive sciences. I argue that despite their similarities, the traditional form, as well as Popper’s theory belong to strong causal emergentism and yield radically different ontological consequences compared to the weaker, contemporary version present in cognitive science. Strong causal emergentism denies the causal closure of the physical domain and introduces (...) genuine new mental causal powers and genuine downward causation, while weak emergentism provides new insights in understanding the mechanisms and explanation that is compatible with physicalism. (shrink)

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.

The synthetic position adopted by Müller is weakened by a large number of overinterpretations and misrepresentations, together with a caricatured view of innateness and modularity.

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.

Müller's review of the neuroscientific evidence undermines nativist claims for autonomous syntax and the argument from the poverty of the stimulus. Generativists will appeal to data from language acquisition, but here too there is growing evidence against the nativist position. Epigenetic naturalism, the developmental alternative to nativism, can be extended to epigenetic socionaturalism, acknowledging the importance of sociocultural processes in language and cognitive development.

Both autonomy and local specificity are compatible with observed interconnectivity at the cell level when considering two different levels: cell assemblies and brain systems. Early syntactic structuring processes in particular are likely to representan autonomous module in the language/brain system.

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.

There is widespread belief that connectionist networks are dramatically different from classical or symbolic models. However, connectionists rarely test this belief by interpreting the internal structure of their nets. A new approach to interpreting networks was recently introduced by Berkeley et al. (1995). The current paper examines two implications of applying this method: (1) that the internal structure of a connectionist network can have a very classical appearance, and (2) that this interpretation can provide a cognitive theory that cannot be (...) dismissed as a mere implementation. (shrink)

The conclusion that language is not really innate or modular is based on several fallacies. I show that the target article confuses communicative skills with linguistic abilities, and that its discussion of brain/language relations is replete with factual errors. I also criticize its attempt to contrast biological and linguistic principles. Finally, I argue that no case is made for the “alternative” approach proposed here.

Müller attempts to downplay cases of dissociation between language and cognition as evidence against the modularity of language. We review cases of associations between verbal and nonverbal abilities as further evidence against the notion of language as an autonomous subsystem. We also point out a discrepancy between his proposal of homologies between nonhuman primates' communication and human language and recent proposals on the evolution of language.

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)

Müller's goal of bringing neuroscience to bear on controversies in linguistics is laudable. However, some of his specific proposals about innateness and autonomy are misguided. Recent studies on the neurobiology of regular and irregular inflectional morphology indicate that these two linguistic processes are subserved by anatomically and physiologically distinct neural subsystems, whose functional organization is likely to be under direct genetic control rather than assembled by strictly epigenetic factors.

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. (shrink)

The claims that learning systems must build causal models and provide explanations of their inferences are not new, and advocate a cognitive functionalism for artificial intelligence. This view conflates the relationships between implicit and explicit knowledge representation. We present recent evidence that neural networks do engage in model building, which is implicit, and cannot be dissociated from the learning process.

Segregated neural circuits that effect particular domain-specific behaviors can be differentiated from neuroanatomical structures implicated in many different aspects of behavior. The basal ganglionic components of circuits regulating nonlinguistic motor behavior, speech, and syntax all function in a similar manner. Hence, it is unlikely that special properties and evolutionary mechanisms are associated with the neural bases of human language.