The goal of this short chapter, aimed at philosophers, is to provide an overview and brief explanation of some central concepts involved in predictive processing (PP). Even those who consider themselves experts on the topic may find it helpful to see how the central terms are used in this collection. To keep things simple, we will first informally define a set of features important to predictive processing, supplemented by some short explanations and an alphabetic glossary. -/- The features described here (...) are not shared in all PP accounts. Some may not be necessary for an individual model; others may be contested. Indeed, not even all authors of this collection will accept all of them. To make this transparent, we have encouraged contributors to indicate briefly which of the features are necessary to support the arguments they provide, and which (if any) are incompatible with their account. For the sake of clarity, we provide the complete list here, very roughly ordered by how central we take them to be for “Vanilla PP” (i.e., a formulation of predictive processing that will probably be accepted by most researchers working on this topic). More detailed explanations will be given below. Note that these features do not specify individually necessary and jointly sufficient conditions for the application of the concept of “predictive processing”. All we currently have is a semantic cluster, with perhaps some overlapping sets of jointly sufficient criteria. The framework is still developing, and it is difficult, maybe impossible, to provide theory-neutral explanations of all PP ideas without already introducing strong background assumptions. (shrink)

​Imagination will remain a mystery—we will not be able to explain imagination—until we can break it into parts we already understand. Explaining Imagination is a guidebook for doing just that, where the parts are other ordinary mental states like beliefs, desires, judgments, and decisions. In different combinations and contexts, these states constitute cases of imagining. This reductive approach to imagination is at direct odds with the current orthodoxy, according to which imagination is a sui generis mental state or process—one with (...) its own inscrutable principles of operation. Explaining Imagination upends that view, showing how, on closer inspection, the imaginings at work in hypothetical reasoning, pretense, the enjoyment of fiction, and creativity are reducible to other familiar mental states—judgments, beliefs, desires, and decisions among them. Crisscrossing contemporary philosophy of mind, cognitive science, and aesthetics, Explaining Imagination argues that a clearer understanding of imagination is already well within reach. (shrink)

Predictive processing (PP) is now a prominent theoretical framework in the philosophy of mind and cognitive science. This review focuses on PP research with a relatively philosophical focus, taking stock of the framework and discussing new directions. The review contains an introduction that describes the full PP toolbox; an exploration of areas where PP has advanced understanding of perceptual and cognitive phenomena; a discussion of PP's impact on foundational issues in cognitive science; and a consideration of the philosophy of science (...) of PP. The overall picture is that PP is a fruitful framework, with exciting new directions awaiting exploration. (shrink)

In this paper, we argue for a theoretical separation of the free-energy principle from Helmholtzian accounts of the predictive brain. The free-energy principle is a theoretical framework capturing the imperative for biological self-organization in information-theoretic terms. The free-energy principle has typically been connected with a Bayesian theory of predictive coding, and the latter is often taken to support a Helmholtzian theory of perception as unconscious inference. If our interpretation is right, however, a Helmholtzian view of perception is incompatible with Bayesian (...) predictive coding under the free-energy principle. We argue that the free energy principle and the ecological and enactive approach to mind and life make for a much happier marriage of ideas. We make our argument based on three points. First we argue that the free energy principle applies to the whole animal–environment system, and not only to the brain. Second, we show that active inference, as understood by the free-energy principle, is incompatible with unconscious inference understood as analagous to scientific hypothesis-testing, the main tenet of a Helmholtzian view of perception. Third, we argue that the notion of inference at work in Bayesian predictive coding under the free-energy principle is too weak to support a Helmholtzian theory of perception. Taken together these points imply that the free energy principle is best understood in ecological and enactive terms set out in this paper. (shrink)

In this paper, we consider how certain longstanding philosophical questions about mental representation may be answered on the assumption that cognitive and perceptual systems implement hierarchical generative models, such as those discussed within the prediction error minimization framework. We build on existing treatments of representation via structural resemblance, such as those in Gładziejewski :559–582, 2016) and Gładziejewski and Miłkowski, to argue for a representationalist interpretation of the PEM framework. We further motivate the proposed approach to content by arguing that it (...) is consistent with approaches implicit in theories of unsupervised learning in neural networks. In the course of this discussion, we argue that the structural representation proposal, properly understood, has more in common with functional-role than with causal/informational or teleosemantic theories. In the remainder of the paper, we describe the PEM framework for approximate Bayesian inference in some detail, and discuss how structural representations might arise within the proposed Bayesian hierarchies. After explicating the notion of variational inference, we define a subjectively accessible measure of misrepresentation for hierarchical Bayesian networks by appeal to the Kullbach–Leibler divergence between posterior generative and approximate recognition densities, and discuss a related measure of objective misrepresentation in terms of correspondence with the facts. (shrink)

Four different accounts of the relationship between third-person mindreading and first-person metacognition are compared and evaluated. While three of them endorse the existence of introspection for propositional attitudes, the fourth (defended here) claims that our knowledge of our own attitudes results from turning our mindreading capacities upon ourselves. Section 1 of this target article introduces the four accounts. Section 2 develops the “mindreading is prior” model in more detail, showing how it predicts introspection for perceptual and quasi-perceptual (e.g., imagistic) mental (...) events while claiming that metacognitive access to our own attitudes always results from swift unconscious self-interpretation. This section also considers the model's relationship to the expression of attitudes in speech. Section 3 argues that the commonsense belief in the existence of introspection should be given no weight. Section 4 argues briefly that data from childhood development are of no help in resolving this debate. Section 5 considers the evolutionary claims to which the different accounts are committed, and argues that the three introspective views make predictions that are not borne out by the data. Section 6 examines the extensive evidence that people often confabulate when self-attributing attitudes. Section 7 considers “two systems” accounts of human thinking and reasoning, arguing that although there are introspectableeventswithin System 2, there are no introspectableattitudes. Section 8 examines alleged evidence of “unsymbolized thinking”. Section 9 considers the claim that schizophrenia exhibits a dissociation between mindreading and metacognition. Finally, section 10 evaluates the claim that autism presents a dissociation in the opposite direction, of metacognition without mindreading. (shrink)

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume (...) that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation. We show how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, how they interweave production and comprehension processes, and how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal. (shrink)

What is the function of cognition? On one influential account, cognition evolved to co-ordinate behaviour with environmental change or complexity. Liberal interpretations of this view ascribe cognition to an extraordinarily broad set of biological systems—even bacteria, which modulate their activity in response to salient external cues, would seem to qualify as cognitive agents. However, equating cognition with adaptive flexibility per se glosses over important distinctions in the way biological organisms deal with environmental complexity. Drawing on contemporary advances in theoretical biology (...) and computational neuroscience, we cash these distinctions out in terms of different kinds of generative models, and the representational and uncertainty-resolving capacities they afford. This analysis leads us to propose a formal criterion for delineating cognition from other, more pervasive forms of adaptive plasticity. On this view, biological cognition is rooted in a particular kind of functional organisation; namely, that which enables the agent to detach from the present and engage in counterfactual inference. (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)

Recently, various philosophers have argued that we can obtain knowledge via the imagination. In particular, it has been suggested that we can come to know concrete, empirical matters of everyday significance by appropriately imagining relevant scenarios. Arguments for this thesis come in two main varieties: black box reliability arguments and constraints-based arguments. We suggest that both strategies are unsuccessful. Against black-box arguments, we point to evidence from empirical psychology, question a central case-study, and raise concerns about a (claimed) evolutionary rationale (...) for the imagination's reliability. Against the constraints-based account, we argue that to the extent that it works, this does not give rise to knowledge that is distinctively from the imagination. We conclude by suggesting that the imagination's role in raising possibilities, traditionally seen as part of the context of discovery, can in fact play a role in justification, including as a bulwark against certain sorts of skepticism. (shrink)

Currie’s (2010) argument that “i-desires” must be posited to explain our responses to fiction is critically discussed. It is argued that beliefs and desires featuring ‘in the fiction’ operators—and not sui generis imaginings (or "i-beliefs" or "i-desires")—are the crucial states involved in generating fiction-directed affect. A defense of the “Operator Claim” is mounted, according to which ‘in the fiction’ operators would be also be required within fiction-directed sui generis imaginings (or "i-beliefs" and "i-desires"), were there such. Once we appreciate that (...) even fiction-directed sui generis imaginings would need to incorporate ‘in the fiction’ operators, the main appeal of the idea that sui generis imaginings (or "i-beliefs" or "i-desires") are at work in fiction-appreciation dissipates. [This is Chapter 10 of Explaining Imagination (OUP, 2020)]. (shrink)

This paper centers around the notion that internal, mental representations are grounded in structural similarity, i.e., that they are so-called S-representations. We show how S-representations may be causally relevant and argue that they are distinct from mere detectors. First, using the neomechanist theory of explanation and the interventionist account of causal relevance, we provide a precise interpretation of the claim that in S-representations, structural similarity serves as a “fuel of success”, i.e., a relation that is exploitable for the representation using (...) system. Then, we discuss crucial differences between S-representations and indicators or detectors, showing that—contrary to claims made in the literature—there is an important theoretical distinction to be drawn between the two. (shrink)

Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the “representation wars” of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing’s account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based (...) representational architecture with organism-relative contents that functions in the service of pragmatic success, not veridical representation. Finally, I argue that internal representation so understood is either impervious to the three anti-representationalist challenges I outline or can actively embrace them. (shrink)

The problem of amodal perception is the problem of how we represent features of perceived objects that are occluded or otherwise hidden from us. Bence Nanay (2010) has recently proposed that we amodally perceive an object's occluded features by imaginatively projecting them into the relevant regions of visual egocentric space. In this paper, I argue that amodal perception is not a single, unitary capacity. Drawing appropriate distinctions reveals amodal perception to be characterized not only by mental imagery, as Nanay suggests, (...) but also by genuinely visual representations as well as beliefs. I conclude with some brief remarks on the role of object-directed bodily action in conferring a sense of unseen presence on an object's occluded features. (shrink)

We advance an account that grounds cognition, specifically decision-making, in an activity all organisms as autonomous systems must perform to keep themselves viable—controlling their production mechanisms. Production mechanisms, as we characterize them, perform activities such as procuring resources from their environment, putting these resources to use to construct and repair the organism's body and moving through the environment. Given the variable nature of the environment and the continual degradation of the organism, these production mechanisms must be regulated by control mechanisms (...) that select when a production is required and how it should be carried out. To operate on production mechanisms, control mechanisms need to procure information through measurement processes and evaluate possible actions. They are making decisions. In all organisms, these decisions are made by multiple different control mechanisms that are organized not hierarchically but heterarchically. In many cases, they employ internal models of features of the environment with which the organism must deal. Cognition, in the form of decision-making, is thus fundamental to living systems which must control their production mechanisms. (shrink)

If imagination is subject to the will, in the sense that people choose the content of their own imaginings, how is it that one nevertheless can learn from what one imagines? This chapter argues for a way forward in addressing this perennial puzzle, both with respect to propositional imagination and sensory imagination. Making progress requires looking carefully at the interplay between one’s intentions and various kinds of constraints that may be operative in the generation of imaginings. Lessons are drawn from (...) the existing literature on propositional imagination and from the control theory literature concerning the prediction and comparison mechanisms (or “forward models”) involved in ordinary perception. A more general conclusion is reached that, once we have the tools to understand how some imaginings are both under willful control and helpfully guide action and inference, we will have what we need to understand the cognitive basis of imagination in general. (shrink)

We begin by introducing our readers to the Extended Mind Thesis and briefly discuss a series of arguments in its favour. We continue by showing of such a theory can be resisted and go on to demonstrate that a more conservative account of cognition can be developed. We acknowledge a stalemate between these two different accounts of cognition and notice a couple of issues that we argue have prevented further progress in the field. To overcome the stalemate, we propose to (...) focus on the ethical implications of these theories. We link work conducted on the Extended Mind Thesis with contemporary transhumanist research and claim that extended may be ethically preferred over embedded because it is a more progressive and inclusive theory. (shrink)

Colloquially, episodic memory is described as “the memory of personally experienced events”. Even though episodic memory has been studied in psychology and neuroscience for about six decades, there is still great uncertainty as to what episodic memory is. Here we ask how episodic memory should be characterized in order to be validated as a natural kind. We propose to conceive of episodic memory as a knowledge-like state that is identified with an experientially based mnemonic representation of an episode that allows (...) for a mnemonic simulation thereof. We call our analysis the Sequence Analysis of Episodic Memory since episodes will be analyzed in terms of sequences of events. Our philosophical analysis of episodic memory is driven and supported by experimental results from psychology and neuroscience. We discuss selected experimental results that provide exemplary evidence for uniform causal mechanisms underlying the properties of episodic memory and argue that episodic memory is a natural kind. The argumentation proceeds along three cornerstones: First, psychological evidence suggests that a violation of any of the proposed conditions for episodic memory amounts to a deficiency of episodic memory and no form of memory or cognitive process but episodic memory fulfills them. Second, empirical results support a claim that the principal anatomical substrate of episodic memory is the hippocampus. Finally, we can pin down causal mechanisms onto neural activities in the hippocampus to explain the psychological states and processes constituting episodic memory. (shrink)

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...) recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (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)

I offer an explanation of how subjects are able to perceive the intrinsic spatial properties of objects, given that subjects always perceive from a particular location. The argument proceeds in two steps. First, I argue that a conception of space is necessary to perceive the intrinsic spatial properties of objects. This conception of space is spelled out by showing that perceiving intrinsic properties requires perceiving objects as the kind of things that are perceivable from other locations. Second, I show that (...) having such a conception of space presupposes that a subject represent her location in relation to perceived objects. More precisely the thesis is that a subject represents her location as the location from which she both perceives objects and would act in relation to objects were she to act. So I argue that perception depends on the capacity to know what it would be to act in relation to objects. (shrink)

Fodor advocates a view of cognitive processes as computations defined over the language of thought (or Mentalese). Even among those who endorse Mentalese, considerable controversy surrounds its representational format. What semantically relevant structure should scientific psychology attribute to Mentalese symbols? Researchers commonly emphasize logical structure, akin to that displayed by predicate calculus sentences. To counteract this tendency, I discuss computational models of navigation drawn from probabilistic robotics. These models involve computations defined over cognitive maps, which have geometric rather than logical (...) structure. They thereby demonstrate the possibility of rational cognitive processes in an exclusively non-logical representational medium. Furthermore, they offer much promise for the empirical study of animal navigation. (shrink)

Biogenic approaches investigate cognition from the standpoint of evolutionary function, asking what cognition does for a living system and then looking for common principles and exhibitions of cognitive strategies in a vast array of living systems—non-neural to neural. One worry which arises for the biogenic approach is that it is overly permissive in terms of what it construes as cognition. In this paper I critically engage with a recent instance of this way of criticising biogenic approaches in order to clarify (...) their theoretical commitments and prospects. In his critique of the biogenic approach, Fred Adams uses the presence of intentional states with conceptual content as a criterion to demarcate cognition-driven behaviour from mere sensory response. In this paper I agree with Adams that intentionality is the mark of the cognitive, but simultaneously reject his overly restrictive conception of intentionality. I argue that understanding intentionality simpliciter as the mark of the mental is compatible with endorsing the biogenic approach. I argue that because cognitive science is not exclusively interested in behaviour driven by intentional states with the kind of content Adams demands, the biogenic approach’s status as an approach to cognition is not called into question. I then go on to propose a novel view of intentionality whereby it is seen to exist along a continuum which increases in the degree of representational complexity: how far into the future representational content can be directed and drive anticipatory behaviour. Understanding intentionality as existing along a continuum allows biogenic approaches and anthropogenic approaches to investigate the same overarching capacity of cognition as expressed in its different forms positioned along the continuum of intentionality. Even if all organisms engage in some behaviour that is driven by weak intentional dynamics, this does not suggest that every behaviour of all organisms is so driven. As such, the worry that the biogenic approach is overly permissive can be avoided. (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.

We use the hierarchical nature of Bayesian perceptual inference to explain a fundamental aspect of the temporality of experience, namely the phenomenology of temporal flow. The explanation says that the sense of temporal flow in conscious perception stems from probabilistic inference that the present cannot be trusted. The account begins by describing hierarchical inference under the notion of prediction error minimization, and exemplifies distrust of the present within bistable visual perception and action initiation. Distrust of the present is then discussed (...) in relation to previous research on temporal phenomenology. Finally, we discuss how there may be individual differences in the experience of temporal flow, in particular along the autism spectrum. The resulting view is that the sense of temporal flow in conscious perception results from an internal, inferential process. (shrink)

In this paper, I critically assess the enactive account of visual perception recently defended by AlvaNoë (2004). I argueinter aliathat the enactive account falsely identifies an object’s apparent shape with its 2D perspectival shape; that it mistakenly assimilates visual shape perception and volumetric object recognition; and that it seriously misrepresents the constitutive role of bodily action in visual awareness. I argue further that noticing an object’s perspectival shape involves a hybrid experience combining both perceptual and imaginative elements—an act of what (...) I call ‘make‐perceive’. (shrink)

Imitation, deliberation, and mindreading are characteristically human sociocognitive skills. Research on imitation and its role in social cognition is flourishing across various disciplines. Imitation is surveyed in this target article under headings of behavior, subpersonal mechanisms, and functions of imitation. A model is then advanced within which many of the developments surveyed can be located and explained. The shared circuits model (SCM) explains how imitation, deliberation, and mindreading can be enabled by subpersonal mechanisms of control, mirroring, and simulation. It is (...) cast at a middle, functional level of description, that is, between the level of neural implementation and the level of conscious perceptions and intentional actions. The SCM connects shared informational dynamics for perception and action with shared informational dynamics for self and other, while also showing how the action/perception, self/other, and actual/possible distinctions can be overlaid on these shared informational dynamics. It avoids the common conception of perception and action as separate and peripheral to central cognition. Rather, it contributes to the situated cognition movement by showing how mechanisms for perceiving action can be built on those for active perception.;>;>The SCM is developed heuristically, in five layers that can be combined in various ways to frame specific ontogenetic or phylogenetic hypotheses. The starting point is dynamic online motor control, whereby an organism is closely attuned to its embedding environment through sensorimotor feedback. Onto this are layered functions of prediction and simulation of feedback, mirroring, simulation of mirroring, monitored inhibition of motor output, and monitored simulation of input. Finally, monitored simulation of input specifying possible actions plus inhibited mirroring of such possible actions can generate information about the possible as opposed to actual instrumental actions of others, and the possible causes and effects of such possible actions, thereby enabling strategic social deliberation. Multiple instances of such shared circuits structures could be linked into a network permitting decomposition and recombination of elements, enabling flexible control, imitative learning, understanding of other agents, and instrumental and strategic deliberation. While more advanced forms of social cognition, which require tracking multiple others and their multiple possible actions, may depend on interpretative theorizing or language, the SCM shows how layered mechanisms of control, mirroring, and simulation can enable distinctively human cognitive capacities for imitation, deliberation, and mindreading. (shrink)

The aim of teleosemantics is to give a scientifically respectable, or ‘naturalistic’ theory of mental content. In the debates surrounding the scope and merits of teleosemantics a lot has been said about the concept of indication (or carrying information). The aim of this paper is to focus on the other key concept of teleosemantics: biological function. It has been universally accepted in the teleosemantics literature that the account of biological function one should use to flesh out teleosemantics is that of (...) etiological function. My claim is that if we replace this concept of function with an alternative one (that we have independent reasons to accept) and if we also restrict the scope of teleosemantics, we can arrive at an account of biologizing mental content that is much less problematic than the previous attempts. (shrink)

Recent research in cognitive and computational neuroscience portrays the neocortex as a hierarchically structured prediction machine. Several theorists have drawn on this research to challenge the traditional distinction between perception and cognition – specifically, to challenge the very idea that perception and cognition constitute useful kinds from the perspective of cognitive neuroscience. In place of this traditional taxonomy, such theorists advocate a unified inferential hierarchy subject to substantial bi-directional message passing. I outline the nature of this challenge and then raise (...) two objections to the cognitive architecture it proposes as a replacement: first, standard ways of characterising this inferential hierarchy are in tension with the representational reach of conceptual thought; second, there is compelling evidence that commonsense reasoning is structured around highly domain-specific intuitive theories that are difficult to situate within a single hierarchy. (shrink)

Does the material basis of conscious experience extend beyond the boundaries of the brain and central nervous system? In Clark 2009 I reviewed a number of ‘enactivist’ arguments for such a view and found none of them compelling. Ward (2012) rejects my analysis on the grounds that the enactivist deploys an essentially world-involving concept of experience that transforms the argumentative landscape in a way that makes the enactivist conclusion inescapable. I present an alternative (prediction-and-generative-model-based) account that neatly accommodates all the (...) positive evidence that Ward cites on behalf of this enactivist conception, and that (I argue) makes richer and more satisfying contact with the full sweep of human experience. (shrink)

Philosophical proponents of predictive processing cast the novelty of predictive models of perception in terms of differences in the functional role and information content of neural signals. However, they fail to provide constraints on how the crucial semantic mapping from signals to their informational contents is determined. Beyond a novel interpretative gloss on neural signals, they have little new to say about the causal structure of the system, or even what statistical information is carried by the signals. That means that (...) the predictive framework for perception can be relabeled in traditional, non-predictive terms, with no empirical consequences relevant to existing or future data. To the extent that neuroscientific research based on predictive processing is both innovative and productive, it will be due to the framework’s suggestive heuristic effects, or perhaps auxiliary empirical claims about implementation, rather than a difference in the information-processing structure that it describes. (shrink)

The phenomenology of agency and perception is probably underpinned by a common cognitive system based on generative models and predictive coding. I defend the hypothesis that this cognitive system explains core aspects of the sense of having a self in agency and perception. In particular, this cognitive model explains the phenomenological notion of a minimal self as well as a notion of the narrative self. The proposal is related to some influential studies of overall brain function, and to psychopathology. These (...) elusive notions of the self are shown to be the natural upshots of general cognitive mechanisms whose fundamental purpose is to enable agents to represent the world and act in it. (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)

Research on concepts has concentrated on the way people apply concepts online, when presented with a stimulus. Just as important, however, is the use of concepts offline, when planning what to do or thinking about what is the case. There is strong evidence that inferences driven by conceptual thought draw heavily on special-purpose resources: sensory, motoric, affective, and evaluative. At the same time, concepts afford general-purpose recombination and support domain-general reasoning processes—phenomena that have long been the focus of philosophers. There (...) is a growing consensus that a theory of concepts must encompass both kinds of process. This book shows how concepts are able to act as an interface between general-purpose reasoning and special-purpose systems. Concept-driven thinking can take advantage of the complementary costs and benefits of each. The book lays out an empirically-based account of the different ways in which thinking with concepts takes us to new conclusions and underpins planning, decision-making, and action. It also spells out three useful implications of the account. First, it allows us to reconstruct the commonplace idea that thinking draws on the meaning of a concept. Second, it offers an insight into how human cognition avoids the frame problem and the complementary, less discussed, ‘if-then problem’ for nested processing dispositions. Third, it shows that metacognition can apply to concepts and concept-driven thinking in various ways. The framework developed in the book elucidates what it is that makes concept-driven thinking an especially powerful cognitive resource. (shrink)

The paper proposes a minimal definition of dreaming in terms of immersive spatiotemporal hallucination (ISTH) occurring in sleep or during sleep–wake transitions and under the assumption of reportability. I take these conditions to be both necessary and sufficient for dreaming to arise. While empirical research results may, in the future, allow for an extension of the concept of dreaming beyond sleep and possibly even independently of reportability, ISTH is part of any possible extension of this definition and thus is a (...) constitutive condition of dreaming. I also argue that the proposed ISTH model of dreaming, in conjunction with considerations on the epistemic relationship between dreaming and dream reports, raises important questions about the extent to which dreams typically involve a detailed body representation—an assumption that plays an important role in philosophical work on dreaming. As a commonly accepted definition of dreaming is lacking in current dream research, the ISTH model, which integrates conceptual analysis and epistemological considerations with results from empirical research, is an important contribution to this field. By linking dreaming to felt presence, full-body illusions, and autoscopic phenomena such as out-of-body experiences in wakefulness and in the hypnagogic state, the ISTH model of dreaming also helps integrate dream research, both theoretically and experimentally, with the study of other altered states of consciousness involving hallucinations. It makes straightforward and investigable predictions by claiming that all of these experiences have amodal spatiotemporal hallucinations as their common denominator. Finally, it is theoretically relevant for the philosophical discussion on minimal phenomenal selfhood. (shrink)

Human beings have the ability to ‘augment’ reality by superimposing mental imagery on the visually perceived scene. For example, when deciding how to arrange furniture in a new home, one might project the image of an armchair into an empty corner or the image of a painting onto a wall. The experience of noticing a constellation in the sky at night is also perceptual-imaginative amalgam: it involves both seeing the stars in the constellation and imagining the lines that connect them (...) at the same time. I here refer to such hybrid experiences – involving both a bottom-up, externally generated component and a top-down, internally generated component – as make-perceive (Briscoe 2008, 2011). My discussion in this paper has two parts. In the first part, I show that make-perceive enables human beings to solve certain problems and pursue certain projects more effectively than bottom-up perceiving or top-down visualization alone. To this end, the skillful use of projected mental imagery is surveyed in a variety of contexts, including action planning, the interpretation of static mechanical diagrams, and non-instrumental navigation. In the second part, I address the question of whether make-perceive may help to account for the “phenomenal presence” of occluded or otherwise hidden features of perceived objects. I argue that phenomenal presence is not well explained by the hypothesis that hidden features are represented using projected mental images. In defending this position, I point to important phenomenological and functional differences between the way hidden object features are represented respectively in mental imagery and amodal completion. (shrink)

In Representation Reconsidered , William Ramsey suggests that the notion of structural representation is posited by classical theories of cognition, but not by the ‘newer accounts’ (e.g. connectionist modeling). I challenge the assertion about the newer accounts. I argue that the newer accounts also posit structural representations; in fact, the notion plays a key theoretical role in the current computational approaches in cognitive neuroscience. The argument rests on a close examination of computational work on the oculomotor system.

Theory theory and simulation theory share the assumption that mental states are unobservable, such that mental state attribution requires an extra psychological step beyond perception. Phenomenologists deny this, contending that we can directly perceive people's mental states. Here I evaluate objections to theory theory and simulation theory as accounts of everyday social perception offered by Dan Zahavi and Shaun Gallagher. I agree that their phenomenological claims have bite at the personal level, distinguishing direct social perception from conscious theorizing and simulation. (...) Their appeals to phenomenology and other arguments do not, however, rule out theory theory or simulation theory as accounts of the sub-personal processes underlying social perception. While I here remain uncommitted about the plausibility of sub-personal theorizing and simulation, I argue that phenomenologists must do more in order to reject these accounts. (shrink)

The target article sketched and explored a mechanism (action-oriented predictive processing) most plausibly associated with core forms of cortical processing. In assessing the attractions and pitfalls of the proposal we should keep that element distinct from larger, though interlocking, issues concerning the nature of adaptive organization in general.

What is the relationship between perception and mental imagery? I aim to eliminate an answer that I call perceptualism about mental imagery. Strong perceptualism, defended by Bence Nanay, predictive processing theorists, and several others, claims that imagery is a kind of perceptual state. Weak perceptualism, defended by M. G. F. Martin and Matthew Soteriou, claims that mental imagery is a representation of a perceptual state, a view sometimes called The Dependency Thesis. Strong perceptualism is to be rejected since it misclassifies (...) imagery disorders and abnormalities as perceptual disorders and abnormalities. Weak Perceptualism is to be rejected since it gets wrong the aim and accuracy conditions of a whole class of mental imagery–projected mental imagery–and relies on an impoverished concept of perceptual states, ignoring certain of their structural features. Whatever the relationship between perception and imagery, the perceptualist has it wrong. (shrink)

Ordinary human perceivers know that visual objects are perceivable from standpoints other than their own. The aim of this paper is to provide an explanation of how perceptual experience equips perceivers with this knowledge. I approach the task by discussing a variety of action-based theories of perception. Some of these theories maintain that standpoint transcendence is required for shape perception. I argue that this standpoint transcendence must take place in the phenomenal present and that it can be explained in terms (...) of the experience of perceivers who jointly attend to an object. Joint perceivers experience objects as being perceived from standpoints other than their own. They operate in what I call “social space”, in which they single out objects by triangulating targets’ locations relative to their co-perceivers’ standpoints on these targets. It is then possible to explain the public character of the objects of individual experience by appeal to what I call “public space”. This is a spatial framework whose locations are presented as standpoints whence joint attention to the target would ensue, were they occupied by co-perceivers. If shape perception requires standpoint transcendence, then shape perceivers operate in public space and are thus capable of singling out targets by triangulating their locations from standpoints other than their own. If it doesn’t, then the introduction of a public spatial framework is an additional step whose introduction explains how perceivers come to experience objects as perceivable from standpoints other than their own. (shrink)

A certain philosophical frame of mind holds that contentless imaginings are unimaginable, “inconceivable” (Shapiro, p. 214) ‐ that it is simply not possible to imagine acts of imagining in the absence of representational content. Against this, this paper argues that there is no naturalistically respectable way to rule out the possibility of contentless imaginings on purely analytic or conceptual grounds. Moreover, agreeing with Langland‐Hassan (2015), it defends the view that the best way to understand the content and correctness conditions of (...) non‐basic, hybrid imaginative attitudes is to assume that basic sensory imaginings are enlisted to play many different kinds of cognitive roles depending on the surrounding contentful attitudes that imaginers adopt toward them. Finally, it argues that when it comes to understanding how pure, basic sensory imaginings do their explanatorily important work there is every reason to focus on the properties of such imaginings that enable appropriate interactions and exactly no reason for thinking that representational contents are amongst those properties. (shrink)

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that (...) are being developed by a number of authors. (shrink)

Paweł Gładziejewski has recently argued that the framework of predictive processing postulates genuine representations. His focus is on establishing that certain structures posited by PP actually play a representational role. The goal of this paper is to promote this discussion by exploring the contents of representations posited by PP. Gładziejewski already points out that structural theories of representational content can successfully be applied to PP. Here, I propose to make the treatment slightly more rigorous by invoking Francis Egan’s distinction between (...) mathematical and cognitive contents. Applying this distinction to representational contents in PP, I first show that cognitive contents in PP are determined by mathematical contents, at least in the sense that computational descriptions in PP put constraints on ascriptions of cognitive contents. After that, I explore to what extent these constraints are specific. I argue that the general mathematical contents posited by PP do not constrain ascriptions of cognitive content in a specific way. However, there are at least three aspects of PP that constrain ascriptions of cognitive contents in more specific ways: formal PP models posit specific mathematical contents that define more specific constraints; PP entails claims about how computational mechanisms underpin cognitive phenomena ; the processing hierarchy posited by PP goes along with more specific constraints. (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)