The foundations of biology have been a topic of debate for the past few decades. The traditional perspective of the Modern Synthesis, which portrays organisms as passive entities with limited role in evolutionary theory, is giving way to a new paradigm where organisms are recognized as active agents, actively shaping their own phenotypic traits for adaptive purposes. Within this context, this article raises the question of whether contemporary biological theory is undergoing a cognitive revolution. This inquiry can be approached in (...) two ways: from a theoretical standpoint, exploring the centrality of the cognitive sciences in current theoretical biology; and from a historical perspective, examining the resemblance between the current state of theoretical biology and the Cognitive Revolution of the mid-20th century. Both inquiries yield affirmative answers, though important nuances will be emphasized. The cognitive sciences' explanatory framework is employed to elucidate the agentic characteristics of organisms, establishing a clear parallelism between the Cognitive Revolution and the present state of theoretical biology. (shrink)

Among the cognitive capacities of evolved creatures is the capacity to represent. Theories in cognitive neuroscience typically explain our manifest representational capacities by positing internal representations, but there is little agreement about how these representations function, especially with the relatively recent proliferation of connectionist, dynamical, embodied, and enactive approaches to cognition. In this talk I sketch an account of the nature and function of representation in cognitive neuroscience that couples a realist construal of representational vehicles with a pragmatic account of (...) mental content. I call the resulting package a deflationary account of mental representation and I argue that it avoids the problems that afflict competing accounts. (shrink)

The sensorimotor theory of vision and visual consciousness is often described as a radical alternative to the computational and connectionist orthodoxy in the study of visual perception. However, it is far from clear whether the theory represents a significant departure from orthodox approaches or whether it is an enrichment of it. In this study, I tackle this issue by focusing on the explanatory structure of the sensorimotor theory. I argue that the standard formulation of the theory subscribes to the same (...) theses of the dynamical hypothesis and that it affords covering-law explanations. This however exposes the theory to the mere description worry and generates a puzzle about the role of representations. I then argue that the sensorimotor theory is compatible with a mechanistic framework, and show how this can overcome the mere description worry and solve the problem of the explanatory role of representations. By doing so, it will be shown that the theory should be understood as an enrichment of the orthodoxy, rather than an alternative. (shrink)

The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. Therefore, contemporary dynamicist (...) research reveals the need for a more sophisticated account of mechanistic explanation. (shrink)

Despite the growing popularity of nonrepresentationalist approaches to cognition, and especially of those coming from the enactivist corner, positing internal representations is still the order of the day in mainstream cognitive science. Indeed, the idea that we have to invoke internal content-carrying, thing-like entities to account for the workings of mind and cognition proves to be particularly resilient. In this paper, my aim is to explain at least partially where this resilience of the reified notion of representation comes from. What (...) I want to show is that, crucially, positing inner representations isn’t so much warranted by the scientific practice itself – as is commonly held – but much more motivated by nonscientific and pre-theoretical elements that largely stem from, what I will call, linguistic contingencies. Otherwise put, much of what makes the reified notion of representation an attractive posit can be explained, not by the science, but by the way we, including cognitive scientists, speak. What I want to do here, then, is first, rehearse what reification means in the context of representationalism and, second, specify which linguistic contingencies can account for why the idea of positing representations remains for many not only a viable option, but an indispensability for anyone interested in explanations of mind and cognition. (shrink)

According to situated cognition theory, cognitive accomplishments rely in part on structures and processes outside the individual. This article argues that interactional structures—particularly those created through language use—can make essential contributions to situated cognition in rational academic discourse. Most cognitive accomplishments rely in part on language, and language in use always has both representational and interactional functions. The article analyzes one classroom conversation, in order to illustrate how the interactional functions of speech can facilitate the cognitive accomplishments speakers make through (...) that speech. By showing how closely cognition and interaction can interrelate, the article both supports theories of situated cognition and shows how cognition in at least some educational contexts cannot be extricated from enduring social structures and the construction of social identity. (shrink)

We argue that one important aspect of the “cognitive neuroscience revolution” identified by Boone and Piccinini :1509–1534. doi: 10.1007/s11229-015-0783-4, 2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both “from below” and “from above”—that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves, and from a greater appreciation of the problems (...) solved by bio-cognitive systems, chiefly regulation and prediction. We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of dynamical models as a central postulate in neurocognitive research. (shrink)

models of cognition are essentially incomplete because they fail to capture the temporal properties of mental processing. I present two possible interpretations of the dynamicists' argument from time and show that neither one is successful. The disagreement between dynamicists and symbolic theorists rests not on temporal considerations per se, but on differences over the multiple realizability of cognitive states and the proper explanatory goals of psychology. The negative arguments of dynamicists against symbolic models fail, and it is doubtful whether pursuing (...) dynamicists' explanatory goals will lead to a robust psychological theory. Introduction Elements of the symbolic theory Elements of dynamical systems theory The argument from time 4.1 First interpretation of the argument from time 4.2 Second interpretation of the argument from time Limits of dynamical systems theory. (shrink)

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system.

In this paper, I outline two strands of evidence for the conclusion that the dynamical approach to cognitive science both seeks and provides covering law explanations. Two of the most successful dynamical models—Kelso’s model of rhythmic finger movement and Thelen et al.’s model of infant perseverative reaching—can be seen to provide explanations which conform to the famous explanatory scheme first put forward by Hempel and Oppenheim. In addition, many prominent advocates of the dynamical approach also express the provision of this (...) kind of explanation as a goal of dynamical cognitive science. I conclude by briefly outlining two consequences. First, dynamical cognitive science’s explanatory style may strengthen its links to the so-called “situated” approach to cognition, but, secondly, it may also undermine the widespread intuition that dynamics is related to emergentism in the philosophy of mind. (shrink)

After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then (...) consider a case of insect sensorimotor systematic behavior: communicating behavior in honey bees. I conclude that anti-representational dynamicism fails to capture the fundamental trait of systematic behaviors qua systematic, i.e., their involving exercises of the same behavioral capacities. I suggest, finally, a collaborative strategy in pursuit of a rich and powerful account of this central phenomenon of high cognition at all levels of explanation, including the representational level. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

ABSTRACTIn this paper I offer an interventionist perspective on the explanatory structure and explanatory power of dynamical models in cognitive science: I argue that some “pure” dynamical models – ones that do not refer to mechanisms at all – in cognitive science are “contextualized causal models” and that this explanatory structure gives such models genuine explanatory power. I contrast this view with several other perspectives on the explanatory power of “pure” dynamical models. One of the main results is that dynamical (...) models need not refer to underlying mechanisms in order to be explanatory. I defend and illustrate this position in terms of dynamical models of the A-not-B error in developmental psychology as elaborated by Thelen and colleagues, and dynamical models of unintentional interpersonal coordination developed by Richardson and colleagues. (shrink)

This study addresses the dynamical nature of a “representation‐hungry” cognitive task involving an imagined action. In our experiment, participants were handed rods that systematically increased or decreased in length on subsequent trials. Participants were asked to judge whether or not they thought they could reach for a distant object with the hand‐held rod. The results are in agreement with a dynamical model, extended from Tuller, Case, Ding, and Kelso (1994). The dynamical effects observed in this study suggest that predictive judgments (...) regarding the possibility or impossibility of a certain action can be understood in terms of dynamically evolving basins of attraction instead of as depending on representational structures. (shrink)

Some philosophers argue that we should eschew cross-explanatory integrations of mechanistic, dynamicist, and psychological explanations in cognitive science, because, unlike integrations of mechanistic explanations, they do not deliver genuine, cognitive scientific explanations. Here I challenge this claim by comparing the theoretical virtues of both kinds of explanatory integrations. I first identify two theoretical virtues of integrations of mechanistic explanations—unification and greater qualitative parsimony—and argue that no cross-explanatory integration could have such virtues. However, I go on to argue that this is (...) only a problem for those who think that cognitive science aims to specify one fundamental structure responsible for cognition. For those who do not, cross-explanatory integration will have at least two theoretical virtues to a greater extent than integrations of mechanistic explanations: explanatory depth and applicability. I conclude that one’s views about explanatory integration in cognitive science cannot be segregated from one’s views about the explanatory task of cognitive science. (shrink)

Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel’s (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). We then propose a philosophy of science appropriate to nonrepresentational, dynamical (...) cognitive science. (shrink)

Robert Cummins [(1996) Representations, targets and attitudes, Cambridge, MA: Bradford/MIT, p. 1] has characterized the vexed problem of mental representation as "the topic in the philosophy of mind for some time now." This remark is something of an understatement. The same topic was central to the famous controversy between Nicolas Malebranche and Antoine Arnauld in the 17th century and remained central to the entire philosophical tradition of "ideas" in the writings of Locke, Berkeley, Hume, Reid and Kant. However, the scholarly, (...) exegetical literature has almost no overlap with that of contemporary cognitive science. I show that the recurrence of certain deep perplexities about the mind is a systematic and pervasive pattern arising not only throughout history, but also in a number of independent domains today such as debates over visual imagery, symbolic systems and others. Such historical and contemporary convergences suggest that the fundamental issues cannot arise essentially from the theoretical guise they take in any particular case. (shrink)

In response to widespread doubts among professional philosophers (Russell, Horwich, Dietrich, McGinn, Chalmers), Stoljar argues for a ‘reasonable optimism’ about progress in philosophy. He defends the large and surprising claim that ‘there is progress on all or reasonably many of the big questions.’ However, Stoljar’s caveats and admitted avoidance of historical evidence permits overlooking persistent controversies in philosophy of mind and cognitive science that are essentially unchanged since the 17th Century. Stoljar suggests that his claims are commonplace in philosophy departments (...) and, indeed, the evidence I adduce constitutes an indictment of the widely shared view among professional analytic philosophers. (shrink)

Many who advocate dynamical systems approaches to cognitive science believe themselves committed to the thesis of extended cognition and to the rejection of representation. I argue that this belief is false. In part, this misapprehension rests on a warrantless re-conception of cognition as intelligent behavior. In part also, it rests on thinking that conceptual issues can be resolved empirically. Once these issues are sorted out, the way is cleared for a dynamical systems approach to cognition that is free to retain (...) the standard conception of cognition as taking place in the head, and over representations. (shrink)

Despite its internal divisions and the uncertainty surrounding many of its foundations, there is a growing consensus that the on‐going search for an alternative model of the mind finds a minimal theoretical identity in the pursuit of an anti‐Cartesian conception of mental phenomena. Nevertheless, this anti‐Cartesianism remains more or less explicitly committed to the neo‐Brentanian idea that intentionality is an essential feature of the mental—an idea that has prevailed since the advent of modern cognitive science in the 1950s. An issue (...) of compatibility is thereby raised, as neo‐Brentanism arguably sides with cognitive Cartesianism. The main goal of the paper is to put into full light one specific aspect of this largely unperceived problem of compatibility by arguing that the neo‐Brentanian property of intentionality is an essentially representational one that runs counter to the salient anti‐representationalism of anti‐Cartesianism. And, that this representational essence confronts the search for alternative models of the mind of an anti‐Cartesian kind with the following theoretical issue: To what extent is it possible to devise a non‐Brentanian property of intentionality, particularly one that is fully dissociated from the property of representation? This issue is shown to be much deeper and more difficult than it looks once the nature of representation is properly apprehended; it seems to be still waiting for an answer in the current search for an alternative model of the mind, if only because it has not yet be set in fully adequate terms. (shrink)

In this article I elaborate a scientifically based moral realism that I call affordance moral realism, and I offer a promissory note that affordance moral realism is the best current explanation of morality. Affordance moral realism maintains that morality is constituted by the interaction of moral agents and moral affordances. The latter are the natural and social environments in which moral agents’ activities take place and contain the objects of moral agents’ activities whose actualizations are the manifestation of substantive moral (...) goods. In making this argument, I take a scientific naturalistic approach that includes both the natural and social sciences, aiming to make my account both methodologically and substantively naturalistic. On the subject side of my affordance view, I offer a scientific account of moral agency, one based on an extension of social cognitive theories of agency to the realm of morality. And I argue that affordance moral realism explains the nature of moral agency, its acquisition, maintenance, and successful performance. To explain its origin and maintenance, I make use of a general theory of selection that embraces biological, social, cultural, and intentional selection. On the object side, I offer a theory of moral affordances and their actualizations, employing the findings and theories of moral developmental psychology and moral psychology to understand their actualizations through the successful operations of moral agents. I conclude that a scientifically based naturalistic affordance moral realism promises to provide the best current account of morality. It is not only affordable; it’s a bargain. (shrink)

This study addresses the dynamical nature of a “representation‐hungry” cognitive task involving an imagined action. In our experiment, participants were handed rods that systematically increased or decreased in length on subsequent trials. Participants were asked to judge whether or not they thought they could reach for a distant object with the hand‐held rod. The results are in agreement with a dynamical model, extended from Tuller, Case, Ding, and Kelso (1994). The dynamical effects observed in this study suggest that predictive judgments (...) regarding the possibility or impossibility of a certain action can be understood in terms of dynamically evolving basins of attraction instead of as depending on representational structures. (shrink)

I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar (...) equivalencies between organic dynamic systems and other cognitive functions. This type of research could help us discover how (and/or if) it is possible to use Dynamic Systems Theory to more accurately model the cognitive functions that are now being modeled by subroutines in Symbolic AI computer models. If such a reduction of subroutines to basins of attraction is possible, it could free AI from the limitations that prompted Fodor to say that it was impossible to model certain higher level cognitive functions. (shrink)

ABSTRACTThe seminal work of David Marr, popularized in his classic work Vision, continues to exert a major influence on both cognitive science and philosophy. The interpretation of his work also co...

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...) a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. (shrink)

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...) a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction 2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis? 2.2The informational benefits of multivariate pattern analysis 3Why the Decoder’s Dictum Is False 3.1We don’t know what information is decoded 3.2The theoretical basis for the dictum 3.3Undermining the theoretical basis 4Objections and Replies 4.1Does anyone really believe the dictum? 4.2Good decoding is not enough 4.3Predicting behaviour is not enough 5Moving beyond the Dictum 6Conclusion. (shrink)

Some philosophers have offered structural representations as an alternative to indicator-based representations. Motivating these philosophers is the belief that an indication-based analysis of representation exhibits two fatal inadequacies from which structural representations are spared: such an analysis cannot account for the causal role of representational content and cannot explain how representational content can be made determinate. In fact, we argue, indicator and structural representations are on a par with respect to these two problems. This should not be surprising, we contend, (...) given that the distinction between indicator and structural representations is better conceived as one involving degree rather than kind. (shrink)

In the last decade several prominent critics have charged that invocation of representations is not only not essential for cognitive science, but should be avoided. These claims have been followed by counterarguments demonstrating that the notion certainly is important in explanations of cognitive phenomena. Analyzing some important contributions to the debate, Anthony Chemero has argued that representationalists still need to explain the significance of the notion once there is an available formal account of a system and has, accordingly, challenged representationalists (...) to provide such an explanation. This paper's first part explains why the representationalist should take an interest in Chemero's challenge. It discusses William Bechtel 's account of the representational structure of the Watt Governor, which, among other things, was motivating Chemero to question the relevance of a representational account once a dynamical one is available. The second part contains the answer to Chemero's challenge. It is motivated by the thought that only a representational account of the Watt Governor with a comparable level of detail could possibly add explanatory value to a dynamical account. However, accepting the account also means that it becomes difficult to understand dynamical and representational accounts as rivals. Instead, it would be more adequate to speak of a dynamical account of the representational structure. (shrink)

Applying the concepts of dynamical systems theory to explain cognitive phenomena is still a fairly recent trend in cognitive science and its potential and consequences are not nearly mapped out. A decade ago, dynamical approaches were introduced as a paradigm shift in cognitive science and in this paper I concentrate on how to substantiate this claim. After having considered and rejected the possibility that continuous time is the crucial factor, I present Kelso’s model of a near-cognitive phenomenon which invokes self-organization (...) as the guiding principle. Then, the explanatory strategy implicit in this approach is explicated and its underlying assumption presented. Finally, I discuss how we should characterize this explanatory framework using the notion of emergence. (shrink)

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)

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of (...) mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation. (shrink)

Understanding the role of ‘‘representations’’ in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as ‘‘standing in,’’ and I look for representations in embodied agents involved in simple categorization tasks. In a (...) first experiment, no representation can be found, but the relevance of the task is undermined by the fact that agents with no internal states can reach high performance. A simple modification makes the task more “representationally hungry,” and in this case, agents’ internal states are found to qualify as representations. I conclude by discussing the benefits of reconciling the embodied-dynamical approach with the notion of representation. (shrink)

Correctly understood, teleosemantics is the claim that “representation” is a function term. Things are called “representations” if they have a certain kind of function or telos and perform it in a certain kind of way. This claim is supported with a discussion and proposals about the function of a representation and of how representations perform that function. These proposals have been retrieved by putting together current descriptions from the literature on neural representations with earlier explorations of the features common to (...) most things we are inclined to call representations as these were assessed in Millikan. Of interest is the degree to which these independent sources converge. I conclude that there is no need to employ any new or technical sense of the term “representation” for it to play an important role in neuroscience. (shrink)

The purpose of this paper is to present a general mechanistic framework for analyzing causal representational claims, and offer a way to distinguish genuinely representational explanations from those that invoke representations for honorific purposes. It is usually agreed that rats are capable of navigation because they maintain a cognitive map of their environment. Exactly how and why their neural states give rise to mental representations is a matter of an ongoing debate. I will show that anticipatory mechanisms involved in rats’ (...) evaluation of possible routes give rise to satisfaction conditions of contents, and this is why they are representationally relevant for explaining and predicting rats’ behavior. I argue that a naturalistic account of satisfaction conditions of contents answers the most important objections of antirepresentationalists. (shrink)

Concept contextualism is the view that the information associated with a concept is dependent on the context in which it is tokened. This view is gaining support in recent years. The received and c...

This article demonstrates that non-mechanistic, dynamical explanations are a viable approach to explanation in the special sciences. The claim that dynamical models can be explanatory without reference to mechanisms has previously been met with three lines of criticism from mechanists: the causal relevance concern, the genuine laws concern, and the charge of predictivism. I argue, however, that these mechanist criticisms fail to defeat non-mechanistic, dynamical explanation. Using the examples of Haken et al.’s model of bimanual coordination, and Thelen et al.’s (...) dynamical field model of infant perseverative reaching, I show how each mechanist criticism fails once the standards of Woodward’s interventionist framework are applied to dynamical models. An even-handed application of Woodwardian interventionism reveals that dynamical models are capable of producing genuine explanations without appealing to underlying mechanistic details. 1Introduction2Interventionism and Mechanistic Explanation 2.1Causal relevance and ideal interventions2.2Invariance2.3Explanation3Covering-Laws and Dynamical Explanation 3.1Dynamical models3.2Covering-law explanation3.3Prediction4Causal Relevance 4.1The causal relevance concern4.2Intervening on dynamical models4.3Test case I: The Haken–Kelso–Bunz model4.4Test case II: Dynamical field model5Genuine Laws 5.1The genuine laws concern5.2Using invariance in place of laws5.3Test case I: The Haken–Kelso–Bunz model5.4Test case II: Dynamical field model6Prediction 6.1Predictivism6.2Crude and invariant prediction7Interventionist Criticism of the Haken–Kelso–Bunz Model8Dynamical Explanation8Conclusion. (shrink)

The paper presents and discusses the “which-is-which content of handedness,” the meaning of left as left and right as right, as a possible candidate for the idea of a genuine embodied cognitive content. After showing that the Ozma barrier, the non-transferability of the meaning of left and right, provides a kind of proof of the non-descriptive, indexical nature of the which-is-which content of handedness, arguments are presented which suggest that the classical representationalist account of cognition faces a perplexing problem of (...) underdetermination of reference of left and right in the which-is-which sense. By way of contrast, no such problems occur in a framework were embodied contents are not mediated by some extra body model which carries the representational power, but are instead directly represented. (shrink)

The battle over the proper place of mental representation in cognitive science is often portrayed as a clash between realism and eliminativism. But this simple dichotomy belies the variety of different ontological positions available. This article investigates the various stances that one can adopt toward the ontology of mental representation, and in so doing, shows that eliminativism is in fact best understood as two distinct positions: a posteriori eliminativism and a priori eliminativism. Furthermore, I show that a priori eliminativism faces (...) two crippling challenges. I argue that once we put a priori eliminativism aside, determining the ultimate ontological status of representation can be postponed while we assess its utility across different domains of cognitive science—something all remaining positions can agree on. (shrink)

Enactivism advances an understanding of cognition rooted in the dynamic interaction between an embodied agent and their environment, whilst new mechanism suggests that cognition is explained by uncovering the organised components underlying cognitive capacities. On the face of it, the mechanistic model’s emphasis on localisable and decomposable mechanisms, often neural in nature, runs contrary to the enactivist ethos. Despite appearances, this paper argues that mechanistic explanations of cognition, being neither narrow nor reductive, and compatible with plausible iterations of ideas like (...) emergence and downward causation, are congruent with enactivism. Attention to enactivist ideas, moreover, may serve as a heuristic for mechanistic investigations of cognition. Nevertheless, I show how enactivism and approaches that prioritise mechanistic modelling may diverge in starting assumptions about the nature of cognitive phenomena, such as where the constitutive boundaries of cognition lie. (shrink)

The predominance of machine learning based techniques in cognitive neuroscience raises a host of philosophical and methodological concerns. Given the messiness of neural activity, modellers must make choices about how to structure their raw data to make inferences about encoded representations. This leads to a set of standard methodological assumptions about when abstraction is appropriate in neuroscientific practice. Yet, when made uncritically these choices threaten to bias conclusions about phenomena drawn from data. Contact between the practices of multivariate pattern analysis (...) and philosophy of science can help to illuminate the conditions under which we can use artificial neural networks to better understand neural mechanisms. This paper considers a specific technique for MVPA called representational similarity analysis. I develop a theoretically-informed account of RSA that draws on early connectionist research and work on idealization in the philosophy of science. By bringing a philosophical account of cognitive modelling in conversation with RSA, this paper clarifies the practices of neuroscientists and provides a generalizable framework for using artificial neural networks to study neural mechanisms in the brain. (shrink)

This paper aims to do three things: First, to provide a review of John Staddon's book Adaptive dynamics: The theoretical analysis of behavior. Second, to compare Staddon's behaviorist view with current ideas on embodied cognition. Third, to use this comparison to explicate some outlines for a theoretical analysis of behavior that could be useful as a behavioral foundation for cognitive phenomena. Staddon earlier defended a theoretical behaviorism, which allows internal states in its models but keeps these to a minimum while (...) remaining critical of any cognitive interpretation. In his latest book, Adaptive dynamics, he provides an overview and analysis of an extensive number of these current, behaviorist models. Theoretical behaviorism comes close to the view of embodied cognition, which also stresses the importance of behavior in contrast to high-level cognition. A detailed picture of the overlaps and differences between the two approaches will be sketched by comparing the two on four separate issues: the conceptualization of behavior, loopy structures, parsimonious explanations, and cognitive behavior. The paper will stress the need for a structural analysis of behavior to gain a better understanding of both behavior and cognition. However, for this purpose, we will need behavioral science rather than behaviorism. (shrink)

Recently, it has been provocatively claimed that dynamical modeling approaches signal the emergence of a new explanatory framework distinct from that of mechanistic explanation. This paper rejects this proposal and argues that dynamical explanations are fully compatible with, even naturally construed as, instances of mechanistic explanations. Specifically, it is argued that the mathematical framework of dynamics provides a powerful descriptive scheme for revealing temporal features of activities in mechanisms and plays an explanatory role to the extent it is deployed for (...) this purpose. It is also suggested that more attention should be paid to the distinctive methodological contributions of the dynamical framework including its usefulness as a heuristic for mechanism discovery and hypothesis generation in contemporary neuroscience and biology. (shrink)

This paper challenges arguments that systematic patterns of intelligent behavior license the claim that representations must play a role in the cognitive system analogous to that played by syntactical structures in a computer program. In place of traditional computational models, I argue that research inspired by Dynamical Systems theory can support an alternative view of representations. My suggestion is that we treat linguistic and representational structures as providing complex multi-dimensional targets for the development of individual brains. This approach acknowledges the (...) indispensability of the intentional or representational idiom in psychological explanation without locating representations in the brains of intelligent agents. (shrink)

This article addresses the problem of the nature of mental imagery from a new perspective. It suggests that sign-theoretical approach as elaborated by C. S. Peirce can give a better and more comprehensive explanation of mental imagery. Our empirical findings follow the methodology of cognitive semiotics and they show that (i) properties of mental images are heterogeneous in nature; (ii) properties of mental images are dependent on the characteristics of object-stimulus; (iii) properties of mental images are dependent on individual differences (...) in imaginary capacities. This suggests that, contrary to representational accounts, mental imagery is not based on one dominant representational format. Imagery constitutes a complex system of signs consisting of several sign elements and dynamic relations. A sign-theoretical account may give a better explanation of the nature of mental imagery, as it accommodates heterogenous evidence from this experiment. (shrink)

Traditionally it is taken for granted that mental imagery (MI) is a mental representation (MR) of some kind or format. This yields that theory of MR can give an adequate and exhaustive explanation of MI. Such co-relation between the two is usually seen as unproblematic. But is it really so? This article aims at challenging the theoretical claim that the dominant ‘two-world’ account of MR can adequately explain MI. Contrary to the standard theory of MR, there are reasons to believe (...) that: (a) MI has different cognitive architecture, (b) the relations between elements of MI are dynamic, (c) relations between elements of MI are context-dependent. Consequently, it follows that dominant account of MR neglects important characteristics of MI and, thus, fails to give a comprehensive explanation of the latter. Alternatively, I will argue that a sign-theoretic approach, proposed by C. S. Peirce, can suggest a promising explanation of MI and fully account for the divergent empirical data on the matter. (shrink)

The debate over the explanatory nature of cognitive models has been waged mostly between two factions: the mechanists and the dynamical systems theorists. The former hold that cognitive models are explanatory only if they satisfy a set of mapping criteria, particularly the 3M/3m* requirement. The latter have argued, pace the mechanists, that some cognitive models are both dynamical and constitute covering-law explanations. In this paper, I provide a minimal model interpretation of dynamical cognitive models, arguing that this both provides needed (...) clarity to the mechanist versus dynamicist divide in cognitive science and also paves the way towards further insights about scientific explanation generally. (shrink)

This paper advances the view that some explanations in cognitive science are extra-mathematical explanations. Demonstrating the plausibility of this interpretation centers around certain efficient coding cases which ineliminably enlist information theoretic laws, facts and theorems to identify in-principle, mathematical constraints on neuronal information processing capacities. The explanatory structure in these cases is shown to parallel other putative instances of mathematical explanation. The upshot for cognitive mathematical explanations is thus two-fold: first, the view capably rebuts standard mechanistic objections to non-mechanistic explanation; (...) second, this view serves to importantly widen the possibility space for non-mechanistic forms of explanation in cognitive science. (shrink)