According to a standard representationalist view cognitive capacities depend on internal content-carrying states. Recent alternatives to this view have been met with the reaction that they have, at best, limited scope, because a large range of cognitive phenomena—those involving absent and abstract features—require representational explanations. Here we challenge the idea that the consideration of cognition regarding the absent and the abstract can move the debate about representationalism along. Whether or not cognition involving the absent and the abstract requires the positing (...) of representations depends upon whether more basic forms of cognition require the positing of representations. (shrink)

Where does the mind stop and the rest of the world begin? The question invites two standard replies. Some accept the demarcations of skin and skull, and say that what is outside the body is outside the mind. Others are impressed by arguments suggesting that the meaning of our words "just ain't in the head", and hold that this externalism about meaning carries over into an externalism about mind. We propose to pursue a third position. We advocate a very different (...) sort of externalism: an _active externalism_, based on the active role of the environment in driving cognitive processes. (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)

Arguments in favor of anti-representationalism in cognitive science often suffer from a lack of attention to detail. The purpose of this paper is to fill in the gaps in these arguments, and in so doing show that at least one form of anti- representationalism is potentially viable. After giving a teleological definition of representation and applying it to a few models that have inspired anti- representationalist claims, I argue that anti-representationalism must be divided into two distinct theses, one ontological, one (...) epistemological. Given the assumptions that define the debate, I give reason to think that the ontological thesis is false. I then argue that the epistemological thesis might, in the end, turn out to be true, despite a potentially serious difficulty. Along the way, there will be a brief detour to discuss a controversy from early twentieth century physics. (shrink)

We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization in order to explain (...) cognition. To a large extent, practicing cognitive neuroscientists have already accepted this shift, but philosophical theory has not fully acknowledged and appreciated its significance. As a result, the explanatory framework underlying cognitive neuroscience has remained largely implicit. We explicate this framework and demonstrate its contrast with previous approaches. (shrink)

The theory put forward by Cohen Kadosh & Walsh (CK&W) proposing that semantic representations of numerical magnitude in the parietal cortex are format-specific, does not specify how these representations might be constructed over the course of learning and development. The developmental predictions of the non-abstract theory are discussed and the need for a developmental perspective on the abstract versus non-abstract question highlighted.

An alarming number of philosophers and cognitive scientists have argued that mind extends beyond the brain and body. This book evaluates these arguments and suggests that, typically, it does not. A timely and relevant study that exposes the need to develop a more sophisticated theory of cognition, while pointing to a bold new direction in exploring the nature of cognition Articulates and defends the “mark of the cognitive”, a common sense theory used to distinguish between cognitive and non-cognitive processes Challenges (...) the current popularity of extended cognition theory through critical analysis and by pointing out fallacies and shortcoming in the literature Stimulates discussions that will advance debate about the nature of cognition in the cognitive sciences. (shrink)

I examine one of the conceptual cornerstones of the field known as computational neuroscience, especially as articulated in Churchland et al. (1990), an article that is arguably the locus classicus of this term and its meaning. The authors of that article try, but I claim ultimately fail, to mark off the enterprise of computational neuroscience as an interdisciplinary approach to understanding the cognitive, information-processing functions of the brain. The failure is a result of the fact that the authors provide no (...) principled means to distinguish the study of neural systems as genuinely computational/information-processing from the study of any complex causal process. I then argue for two things. First, that in order to appropriately mark off computational neuroscience, one must be able to assign a semantics to the states over which an attempt to provide a computational explanation is made. Second, I show that neither of the two most popular ways of trying to effect such content assignation -- informational semantics and 'biosemantics' -- can make the required distinction, at least not in a way that a computational neuroscientist should be happy about. The moral of the story as I take it is not a negative one to the effect that computational neuroscience is in principle incapable of doing what it wants to do. Rather, it is to point out some work that remains to be done. (shrink)

Optimising the 4E revolution in cognitive science arguably requires the rejection of two guiding commitments made by orthodox thinking in the field, namely that the material realisers of cognitive states and processes are located entirely inside the head, and that intelligent thought and action are to be explained in terms of the building and manipulation of content-bearing representations. In other words, the full-strength 4E revolution would be secured only by a position that delivered externalism plus antirepresentationalism. I argue that one (...) view in 4E space—extended functionalism—is appropriately poised to deliver externalism but not antirepresentationalism. By contrast, in the case of a competing 4E view—radical enactivism—even if that view can deliver antirepresentationalism, its pivotal notion of extensiveness falls short of establishing externalism. These conclusions are justified via an examination of, and by responding critically to, certain key arguments offered in support of their view by the radical enactivists. (shrink)

Some recent cognitive-scientific research suggests that a considerable amount of intelligent action is generated not by the systematic activity of internal representations, but by complex interactions involving neural, bodily, and environmental factors. Following an analysis of this threat to representational explanation, we pursue an analogy between the role of genes in the production of biological form and the role of neural states in the production of behaviour, in order to develop a notion of genic representation. In both cases an appeal (...) to normal ecological context is used to balance multi-factoral, interactive causal determination against the intuition that certain aspects of the causal nexus play a special role in promoting adaptive success. Certain worries abut this vision help us to get a better grip on the concept of genic representation itself. We end with a puzzle concerning the relation between cognition and representation. (shrink)

I argue that, on plausible assumptions, anomalous entails monism epiphenomenalism of the mental. The plausible assumptions are (1) events are particulars; (2) causal relations are extensional; (3) mental properties are epiphrastic. A principle defender of anomalous monism, Donald Davidson, acknowledges that anomalous monism is committed to (1) and (2). I argue that it is committed to (3) as well. Given (1), (2), and (3), epiphenomenalism of the mental falls out immediately. Three attempts to salvage anomalous monism from epiphenomenalism of the (...) mental are examined and rejected. I conclude with reflections on the status of non-reductive physicalism. (shrink)

This introduction to a special issue of Topoi introduces and summarises the relationship between three main varieties of 'enactivist' theorising about the mind: 'autopoietic', 'sensorimotor', and 'radical' enactivism. It includes a brief discussion of the philosophical and cognitive scientific precursors to enactivist theories, and the relationship of enactivism to other trends in embodied cognitive science and philosophy of mind.

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

The historical debate on representation in cognitive science and neuroscience construes representations as theoretical posits and discusses the degree to which we have reason to posit them. We reject the premise of that debate. We argue that experimental neuroscientists routinely observe and manipulate neural representations in their laboratory. Therefore, neural representations are as real as neurons, action potentials, or any other well-established entities in our ontology.

An underlying assumption in computational approaches in cognitive and brain sciences is that the nervous system is an input–output model of the world: Its input–output functions mirror certain relations in the target domains. I argue that the input–output modelling assumption plays distinct methodological and explanatory roles. Methodologically, input–output modelling serves to discover the computed function from environmental cues. Explanatorily, input–output modelling serves to account for the appropriateness of the computed function to the explanandum information-processing task. I compare very briefly the (...) modelling explanation to mechanistic and optimality explanations, noting that in both cases the explanations can be seen as complementary rather than contrastive or competing. (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)

Since the cognitive revolution, it has become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theorists of cognition be explicit and careful (...) in choosing notions of computation and information and connecting them together.Keywords: Computation; Information processing; Computationalism; Computational theory of mind; Cognitivism. (shrink)

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)

Human cognition is extended and enacted. Drawing the boundaries of cognition to include the resources and attributes of the body and materiality allows an examination of how these components interact with the brain as a system, especially over cultural and evolutionary spans of time. Literacy and numeracy provide examples of multigenerational, incremental change in both psychological functioning and material forms. Though we think materiality, its central role in human cognition is often unappreciated, for reasons that include conceptual distribution over multiple (...) material forms, the unconscious transparency of cognitive activity in general, and the different temporalities of metaplastic change in neurons and cultural forms. (shrink)

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of (...) acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The out- side world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the gov- erning laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Sev- eral lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual “filling in,” visual stability despite eye movements, change blindness, sensory substitution, and color perception. (shrink)

We address some frequently encountered criticisms of Radical Embodied/Enactive Cognition. Contrary to the claims that the position is too radical, or not sufficiently so, we claim REC is just radical enough.

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)

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)

In this paper, I argue that even if the Hard Problem of Content, as identified by Hutto and Myin, is important, it was already solved in natu- ralized semantics, and satisfactory solutions to the problem do not rely merely on the notion of information as covariance. I point out that Hutto and Myin have double standards for linguistic and mental representation, which leads to a peculiar inconsistency. Were they to apply the same standards to basic and linguistic minds, they would (...) either have to embrace representationalism or turn to semantic nihilism, which is, as I argue, an unstable and unattractive position. Hence, I conclude, their book does not offer an alternative to representation- alism. At the same time, it reminds us that representational talk in cognitive science cannot be taken for granted and that information is different from men- tal representation. Although this claim is not new, Hutto and Myin defend it forcefully and elegantly. (shrink)

In this review of Hutto and Myin's Radicalizing Enactivism, I question the adequacy of a non-representational theory of mind. I argue first that such a theory cannot differentiate cognition from other bodily engagements such as wrestling with an opponent. Second, I question whether the simple robots constructed by Rodney Brooks are adequate as models of multimodal organisms. Last, I argue that Hutto and Myin pay very little attention to how semantically interacting representations are needed to give an account of choice (...) and action. (shrink)

This paper shows how a radical approach to enactivism provides a way of clarifying and unifying different varieties of enactivism and enactivist-friendly approaches so as to provide a genuine alternative to classical cognitivism. Section 1 reminds readers of the broad church character of the enactivism framework. Section 2 explicates how radical enactivism is best understood not as a kind of enactivism per se but as a programme for radicalizing and consolidating the many different enactivist offerings. The main work of radical (...) enactivism is to RECtify, existing varieties of enactivism and other cognate approaches so as to strengthen and unify them into a single collective that can rival classical ways of thinking about mind and cognition. Section 3 shows how even seemingly non-enactivist explanatory offerings—such as predictive processing accounts of cognition—might be RECtified and brought within the enactivist explanatory fold. Section 4 reveals why, once RECtified, enactivist offerings, broadly conceived, qualify as genuine and revolutionary alternatives to classical ways of understanding cognition. (shrink)

Colombo (Phenomenology and the Cognitive Sciences, 2012) argues that we have compelling reasons to posit neural representations because doing so yields unique explanatory purchase in central cases of social norm compliance. We aim to show that there is no positive substance to Colombo’s plea—nothing that ought to move us to endorse representationalism in this domain, on any level. We point out that exposing the vices of the phenomenological arguments against representationalism does not, on its own, advance the case for representationalism (...) one inch—beyond establishing its mere possibility. We criticize the continual confounding of constitutive and explanatory claims and the lack of recognition of a Hard Problem of having to provide a naturalistic account of content, coupled with an inability to face up to it. We point at the inadequacy of various deflationary moves that end up driving representationalists towards the idea of neural representations with non-standard contents or without content altogether, both of which either render neural representationalism unfit for purpose or vacuous. Referring to possibilities for neural manipulation and control, or to established scientific practice does not help representationalism either. (shrink)

In a recent series of publications, dynamicist researchers have proposed a new conception of cognitive functioning. This conception is intended to replace the currently dominant theories of connectionism and symbolicism. The dynamicist approach to cognitive modeling employs concepts developed in the mathematical field of dynamical systems theory. They claim that cognitive models should be embedded, low-dimensional, complex, described by coupled differential equations, and non-representational. In this paper I begin with a short description of the dynamicist project and its role as (...) a cognitive theory. Subsequently, I determine the theoretical commitments of dynamicists, critically examine those commitments and discuss current examples of dynamicist models. In conclusion, I determine dynamicism's relation to symbolicism and connectionism and find that the dynamicist goal to establish a new paradigm has yet to be realized. (shrink)

The complex systems approach (CSA) to characterizing cognitive function is purported to underlie a conceptual and methodological revolution by its proponents. I examine one central claim from each of the contributed papers and argue that the provided examples do not justify calls for radical change in how we do cognitive science. Instead, I note how currently available approaches in ‘‘standard’’ cognitive science are adequate (or even more appropriate) for understanding the CSA provided examples.

I argue that of the four kinds of quantitative description relevant for understanding brain function, a control theoretic approach is most appealing. This argument proceeds by comparing computational, dynamical, statistical and control theoretic approaches, and identifying criteria for a good description of brain function. These criteria include providing useful decompositions, simple state mappings, and the ability to account for variability. The criteria are justified by their importance in providing unified accounts of multi-level mechanisms that support intervention. Evaluation of the four (...) kinds of description with respect to these criteria supports the claim that control theoretic characterizations of brain function are the kind of quantitative description we ought to provide.Keywords: Neural computation; Control theory; Neural representation; Cognitive architecture; Cognitive models; Theoretical neuroscience. (shrink)

I argue that dynamicism does not provide a convincing alternative to currently available cognitive theories. First, I show that the attractor dynamics of dynamicist models are inadequate for accounting for high-level cognition. Second, I argue that dynamicist arguments for the rejection of computation and representation are unsound in light of recent empirical findings. This new evidence provides a basis for questioning the importance of continuity to cognitive function, challenging a central commitment of dynamicism. Coupled with a defense of current connectionist (...) theory, these two critiques lead to the conclusion that dynamicists have failed to achieve their goal of providing a new paradigm for understanding cognition. (shrink)

This chapter examines the relations between psychology and neuroscience. There is a strong philosophical intuition that direct study of the brain can and will constrain the development of psychological theory. When this intuition is tested against case studies from the psychology of perception and memory, it turns out that psychology has led the way toward knowledge of neurophysiology. The chapter presents an abstract argument to show that psychology can and must lead the way in neuroscientific study of mental function. The (...) opposing intuition is based on mainly weak arguments about the fundamentality or objectivity of physics or physiology in relation to psychology. The chapter argues that psychological phenomena are methodologically prior to neurophysiological concepts and descriptions, that psychology provides the functional descriptions that guide the behavioral brain sciences, that psychological concepts are not reducible, but that neurophysiological data and concepts are nonetheless evidentially and explanatorily relevant for psychology. (shrink)