Multiple realization was once taken to be a challenge to reductionist visions, especially within cognitive science, and a foundation of the “antireductionist consensus.” More recently, multiple realization has come to be challenged on naturalistic grounds, as well as on more “metaphysical” grounds. Within cognitive science, one focal issue concerns the role of neural plasticity for addressing these issues. If reorganization maintains the same cognitive functions, that supports claims for multiple realization. I take up the reorganization involved in language dysfunctions to (...) deal with questions concerned with multiple realization and neural plasticity. Beginning with Broca’s case for localization and the nineteenth century discussion of “reorganization,” and returning to more recent evidence for neural plasticity, I argue that, in the end, there is substantial support for multiple realization in cognitive systems; I further argue that this is wholly consistent with a recognition of methodological pluralism in cognitive science. (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.

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.

I argue that examining the explanatory power of the hypothesis of extended cognition (HEC) offers a fruitful approach to the problem of cognitive system demarcation. Although in the discussions on HEC it has become common to refer to considerations of explanatory power as a means for assessing the plausibility of the extended cognition approach, to date no satisfying account of explanatory power has been presented in the literature. I suggest that the currently most prominent theory of explanation in the special (...) sciences, James Woodward’s contrastive-counterfactual theory, and an account of explanatory virtues building on that theory can be used to develop a systematic picture of cognitive system demarcation in the psychological sciences. A major difference between my differential influence (DI) account and most other theories of cognitive extension is the cognitive systems pluralism implied by my approach. By examining the explanatory power of competing traditions in psychological memory research, I conclude that internalist and externalist classificatory strategies are characterized by different profiles of explanatory virtues and should often be considered as complementary rather than competing approaches. This suggests a deflationary interpretation of HEC. (shrink)

In this article, I develop an account of the use of intentional predicates in cognitive neuroscience explanations. As pointed out by Maxwell Bennett and Peter Hacker, intentional language abounds in neuroscience theories. According to Bennett and Hacker, the subpersonal use of intentional predicates results in conceptual confusion. I argue against this overly strong conclusion by evaluating the contested language use in light of its explanatory function. By employing conceptual resources from the contemporary philosophy of science, I show that although the (...) use of intentional predicates in mechanistic explanations sometimes leads to explanatorily inert claims, intentional predicates can also successfully feature in mechanistic explanations as tools for the functional analysis of the explanandum phenomenon. Despite the similarities between my account and Daniel Dennett's intentional-stance approach, I argue that intentional stance should not be understood as a theory of subpersonal causal explanation, and therefore cannot be used to assess the explanatory role of intentional predicates in neuroscience. Finally, I outline a general strategy for answering the question of what kind of language can be employed in mechanistic explanations. (shrink)

How can we best understand human cognitive architectural variability? We believe that the relationships between theories in neurobiology, cognitive science and evolutionary biology posited by evolutionary psychology’s Integrated Causal Model has unduly supported various essentialist conceptions of the human cognitive architecture, monomorphic minds, that mask HCA variability, and we propose a different set of relationships between theories in the same domains to support a different, non-essentialist, understanding of HCA variability. To set our case against essentialist theories of HCA variability, we (...) detail the general notion of an ICM and the specific ICM at the heart of evolutionary psychology. We briefly illustrate the type of essentialism fostered by evolutionary psychology’s ICM by showing how it grounds essentialist theories of cognitive gender. We shall not criticize these theories here since the literature is replete with compelling objections to them, but shall instead focus on motivating a replacement ICM to destabilize evolutionary psychology’s ICM wholesale. ICMs usually span larger than the models they support, hence larger than arguments against these models, and one reason the essentialist theories addressed here have the kind of staying power they do is that they are partly supported by the ICM in which they are grounded. In short, we offer “A New Hope” against the essentialist empire. True to the Hollywood trope, this new hope rests on an alliance between a young theory, cognitive network neuroscience, and two older, but still quite young, epistemic rebels: enactive cognitive science and developmental systems theory. Accordingly, we detail and discuss the proposed emerging ICM and test-drive it by sketching the multimorphic view of gender it grounds. (shrink)

This article examines some recent work by Berwick and Chomsky as presented in their book Why Only Us? Language and Evolution. As I understand them, Berwick and Chomsky’s overarching purpose is to explain how human language could have arisen in so short an evolutionary period. After articulating their strategy, I argue that they fall far short of reaching this goal. A co-evolutionary scenario linking the mechanisms that realize the language system, both with one other and with cognitive mechanisms capable of (...) exploiting linguistic expressions, is surely unavoidable. And yet this is precisely what Berwick and Chomsky in effect rule out. (shrink)

A common view is that ceteris paribus clauses render lawlike statements vacuous, unless such clauses can be explicitly reformulated as antecedents of ?real? laws that face no counterinstances. But such reformulations are rare; and they are not, we argue, to be expected in general. So we defend an alternative sufficient condition for the non-vacuity of ceteris paribus laws: roughly, any counterinstance of the law must be independently explicable, in a sense we make explicit. Ceteris paribus laws will carry a plethora (...) of explanatory commitments; and claims that such commitments are satisfied will be as (dis) confirmable as other empirical claims. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...) signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.

The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...) states are individuated within computability theory and computer science. A secondary purpose is to show that existing arguments for the semantic view are defective. (shrink)

This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...) justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.

Philosophy invariably starts with the attempt to spell out ideas and beliefs that we already hold, whether on topics like time or causality, colour or value, consciousness or free will, democracy or justice or freedom. It may go well beyond such pre-philosophical assumptions in its further developments, regimenting them in unexpected ways, revising them on novel lines, even discarding them entirely in favour of other views. But philosophy always begins with the articulation of ordinary ideas and beliefs. This is where (...) its ladder starts. As the name suggests, articulation requires that the ideas and beliefs articulated were already there waiting to be spelled out, and that identifying them is a matter of analysing.. (shrink)

This chapter contains sections titled: The Decision ‐ Theoretic Picture The Decision ‐ plus ‐ Deliberation Picture A Common Mistake References.

Sarah Patterson; III*—The Anomalism of Psychology, Proceedings of the Aristotelian Society, Volume 96, Issue 1, 1 June 1996, Pages 37–52, https://doi.org/10.109.

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we focus on views that attempt to render such ascriptions naturalistic by construing them in a deflationary or merely pragmatic way. We then contrast these views with staunchly realist views that attempt to naturalize intentionality by developing theories of content for representations in terms of information and biological function. (...) We echo several other philosophers by arguing that these theories over-generalize unless they are constrained by a theory of the functional role of representational vehicles. This leads to a discussion of the functional roles of representations, and how representations might be realized in the brain. We argue that there’s work to be done to identify a distinctively mental kind of representation. We close by sketching a way forward for the project of naturalizing intentionality. This will not be achieved simply by ascribing the content of mental states to generic neural representations, but by identifying specific neural representations that explain the puzzling intentional properties of mental states. (shrink)

I offer support for the view that physicalist theories of cognition don't reduce to neurophysiological theories. On my view, the mind-brain relationship is to be explained in terms of evolutionary forces, some of which tug in the direction of a reductionistic mind-brain relationship, and some of which which tug in the opposite direction. This theory of forces makes possible an anti-reductionist account of the cognitive mind-brain relationship which avoids psychophysical anomalism. This theory thus also responds to the complaint which arguably (...) lies behind the Churchlands' strongest criticisms of anti-reductionism — namely the complaint that anti-reductionists fail to supply principled explanations for the character of the mind-brain relationship. While lending support to anti-reductionism, the view defended here also insures a permanent place for mind-brain reduction as an explanatory ideal analogous to Newtonian inertial motion or Aristotelian natural motion. (shrink)

The debate between the defenders of explanatory unification and explanatory pluralism has been ongoing from the beginning of cognitive science and is one of the central themes of its philosophy. Does cognitive science need a grand unifying theory? Should explanatory pluralism be embraced instead? Or maybe local integrative efforts are needed? What are the advantages of explanatory unification as compared to the benefits of explanatory pluralism? These questions, among others, are addressed in this Synthese’s special issue. In the introductory paper, (...) we discuss the background of the questions, distinguishing integrative theorizing from building unified theories. On the one hand, integrative efforts involve collaboration between various disciplines, fields, approaches, or theories. These efforts could even be quite temporary, without establishing any long-term institutionalized fields or disciplines, but could also contribute to developing new interfield theories. On the other hand, unification can rely on developing complete theories of mechanisms and representations underlying all cognition, as Newell’s “unified theories of cognition”, or may appeal to grand principles, as predictive coding. Here, we also show that unification in contemporary cognitive science goes beyond reductive unity, and may involve various forms of joint efforts and division of explanatory labor. This conclusion is one of the themes present in the content of contributions constituting the special issue. (shrink)

Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation ofmodels (...) does not depend on whether they target real biological agents or not; instead, the standards of evaluation depend on the use of models rather than on the reality of their targets. I discuss how models are validated depending on their use and argue that all-encompassing benchmarks for models may be well beyond reach. (shrink)

Smolensky's (1995) proposal for a connectionist explanation of systematicity doesn't work.

Husserl has finally begun to be recognized as the precursor of current interest in intentionality — the first to have a general theory of the role of mental representations in the philosophy of language and mind. As the first thinker to put directedness of mental representations at the center of his philosophy, he is also beginning to emerge as the father of current research in cognitive psychology and artificial intelligence.

Fodor and Pylyshyn (1988), Fodor and McLaughlin (1990) and McLaughlin (1993) challenge connectionists to explain systematicity without simply implementing a classical architecture. In this paper I argue that what makes the challenge difficult for connectionists to meet has less to do with what is to be explained than with what is to count as an explanation. Fodor et al. are prepared to admit as explanatory, accounts of a sort that only classical models can provide. If connectionists are to meet the (...) challenge, they are going to have to insist on the propriety of changing what counts as an explanation of systematicity. Once that is done, there would seem to be as yet no reason to suppose that connectionists are unable to explain systematicity. (shrink)

The specialization of visual function within biological function is reason for introducing “homology thinking” into explanations of the visual system. It is argued that such specialization arises when organisms evolve by differentiation from their predecessors. Thus, it is essentially historical, and visual function should be regarded as a lineage property. The colour vision of birds and mammals do not function the same way as one another, on this account, because each is an adaptation to special needs of the visual functions (...) of predecessors—very different kinds of predecessors in each case. Thus, history underlies function. We also see how homology thinking figures in the hierarchical classification of visual systems, and how it supports the explanation of visual function by functional role analysis. (shrink)

Classicists and connectionists alike claim to be able to explain systematicity. The proposed classicist explanation, I argue, is little more than a promissory note, one that classicists have no idea how to redeem. Smolensky's (1995) proposed connectionist explanation fares little better: it is not vulnerable to recent classicist objections, but it nonetheless fails, particularly if one requires, as some classicists do, that explanations of systematicity take the form of a‘functional analysis’. Nonetheless, there are, I argue, reasons for cautious optimism about (...) the prospects of a connectionist explanation. (shrink)

Classicists and connectionists alike claim to be able to explain systematicity. The proposed classicist explanation, I argue, is little more than a promissory note, one that classicists have no idea how to redeem. Smolensky's (1995) proposed connectionist explanation fares little better: it is not vulnerable to recent classicist objections, but it nonetheless fails, particularly if one requires, as some classicists do, that explanations of systematicity take the form of a‘functional analysis’. Nonetheless, there are, I argue, reasons for cautious optimism about (...) the prospects of a connectionist explanation. (shrink)

If we are to understand why psychoanalysis extends ordinary psychology in the precise ways that it does, we must take account of the existence of, and the interplay between, two distinct kinds of explanatory concern: functional and idiographic. The form and content of psychoanalytic explanation and its unusual methodology can, at least in part, be viewed as emerging out of Freud's attempt to reconcile these two types of explanatory concern. We must also acknowledge the role of the background theoretical context (...) that shapes Freud's functional thinking about the mind. A neglect of the role of the background theory in shaping the extension of ordinary psychology leaves us with puzzles about the nature and direction of the psychoanalytic extension and gives rise to an unbelievable history of psychoanalysis. (shrink)