Tenenbaum and Griffiths (2001) have proposed that their Bayesian model of generalisation unifies Shepard’s (1987) and Tversky’s (1977) similarity-based explanations of two distinct patterns of generalisation behaviours by reconciling them under a single coherent task analysis. I argue that this proposal needs refinement: instead of unifying the heterogeneous notion of psychological similarity, the Bayesian approach unifies generalisation by rendering the distinct patterns of behaviours informationally relevant. I suggest that generalisation as a Bayesian inference should be seen as a complement to, (...) instead of a replacement of, similarity-based explanations. Furthermore, I show that the unificatory powers of the Bayesian model of generalisation can contribute to the selection of one of these models of psychological similarity. (shrink)

Many philosophers claim that the neurocomputational framework of predictive processing entails a globally inferentialist and representationalist view of cognition. Here, I contend that this is not correct. I argue that, given the theoretical commitments these philosophers endorse, no structure within predictive processing systems can be rightfully identified as a representational vehicle. To do so, I first examine some of the theoretical commitments these philosophers share, and show that these commitments provide a set of necessary conditions the satisfaction of which allows (...) us to identify representational vehicles. Having done so, I introduce a predictive processing system capable of active inference, in the form of a simple robotic “brain”. I examine it thoroughly, and show that, given the necessary conditions highlighted above, none of its components qualifies as a representational vehicle. I then consider and allay some worries my claim could raise. I consider whether the anti-representationalist verdict thus obtained could be generalized, and provide some reasons favoring a positive answer. I further consider whether my arguments here could be blocked by allowing the same representational vehicle to possess multiple contents, and whether my arguments entail some extreme form of revisionism, answering in the negative in both cases. A quick conclusion follows. (shrink)

Despite the popularity that the embodied cognition thesis has gained in recent years, explicit memories of events personally experienced are still conceived as disembodied mental representations. It seems that we can consciously remember our personal past through sensory imagery, through concepts, propositions and language, but not through the body. In this article, I defend the idea that the body constitutes a genuine means of representing past personal experiences. For this purpose, I focus on the analysis of bodily movements associated with (...) the retrieval of a personal memory, which have certain features that make them different from procedural memories, pragmatic actions and common gestures, as well as other forms of embodied memories found in recent literature. I refer to these as “kinetic memories” and analyse their representative nature as well as their adaptive functions. Kinetic memories are bodily movements in which some event or action that took place in the past can be seen, because they are an externalisation of the subject’s inner intention of representing a past personal experience. Kinetic memories represent a past experience sometimes by imitation of a past movement, and other times through embodied symbols and metaphors. Furthermore, although sometimes they present direct pragmatic benefits, such as communicative benefits, they seem to enhance the whole reexperience of the past event and memory recall, which I argue is one important adaptive value. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine the only argument (...) offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

Representationalism (aka intentionalism) has been the most significant weapon in the late twentieth century defence of direct realism. However, although the representationalist objection to the Phenomenal Principle might provide an effective response to the arguments from illusion and hallucination, plausible representationalist theories of perception are, when fleshed-out, incompatible with metaphysical direct realism’s directness-claim. Indeed within cognitive science, direct perception is the avowedly-radical anti-representationalist heterodoxy. Drawing on both the philosophy and cognitive science, we develop a robust argument against representationalist direct realism (...) which does not rest on illusory cases or the notion of an object of immediate awareness. None of the representations so far posited, or in prospect, can supply the content required of a representation in a direct realist theory of veridical perception. (shrink)

Similarity-based cognition is commonplace. It occurs whenever an agent or system exploits the similarities that hold between two or more items—e.g., events, processes, objects, and so on—in order to perform some cognitive task. This kind of cognition is of special interest to cognitive neuroscientists. This paper explicates how similarity-based cognition can be understood through the lens of radical enactivism and why doing so has advantages over its representationalist rival, which posits the existence of structural representations or S-representations. Specifically, it is (...) argued that there are problems both with accounting for the content of S-representations and with understanding how neurally-based structural similarities can work as representations in guiding intelligent behavior. Finally, with these clarifications in place, it is revealed how radical enactivism can commit to an account of similarity-based cognition in its understanding of neurodynamics. (shrink)

We discuss various implications of some radical anti-representationalist views of cognition and what they have to offer with regard to the naturalization of intentionality and the explanation of cognitive phenomena. Our focus is on recent arguments from proponents of enactive views of cognition to the effect that basic cognition is intentional but not representational and that cognition is co-extensive with life. We focus on lower rather than higher forms of cognition, namely the question regarding the intentional and representational nature of (...) cognition found in organisms simpler than human beings, because enactivists do not deny that more sophisticated cognitive phenomena are representational and involve content. After introducing the debate on the naturalization of intentionality, we briefly review different varieties of enactivism and introduce their central claims. In Sect. 4 we turn to radical enactivism in order to focus on the arguments for a thoroughly non-representational, enactive account of perception and basic cognition. In particular, we discuss three major issues: First, what is supposed to replace the representational analysis of perception in a radical-enactive explanation of perception? How does the enactive explanation of perception compare to the best scientific work on the neuroscience of perception? Second, what is—on an enactive account—the function of neural processing in the brain for the generation of perception if not to produce representations? This question is especially pressing since one implication of autopoietic enactivism is that even the simplest organisms, i.e. single-celled organisms, have cognitive capacities. Since they lack brains and nervous systems, enactivists must specify the unique contribution of the brain and nervous system in those animals who have them. In Sect. 5, we evaluate the advantages of an autopoietic–enactive approach to the naturalization of intentionality and end with a suggestion how cognition may relate to intentionality and representation. (shrink)

How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

The papers in this special issue make important contributions to a longstanding debate about how we should conceive of and explain mental phenomena. In other words, they make a case about the best philosophical paradigm for cognitive science. The two main competing approaches, hotly debated for several decades, are representationalism and enactivism. However, recent developments in disciplines such as machine learning and computational neuroscience have fostered a proliferation of intermediate approaches, leading to the emergence of completely new positions, in particular (...) the Predictive Processing approach. Here, we will consider the different approaches discussed in this volume. (shrink)

This paper explores early Australasian philosophy in some detail. Two approaches have dominated Western philosophy in Australia: idealism and materialism. Idealism was prevalent between the 1880s and the 1930s, but dissipated thereafter. Idealism in Australia often reflected Kantian themes, but it also reflected the revival of interest in Hegel through the work of ‘absolute idealists’ such as T. H. Green, F. H. Bradley, and Henry Jones. A number of the early New Zealand philosophers were also educated in the idealist tradition (...) and were influential in their communities, but produced relatively little. In Australia, materialism gained prominence through the work of John Anderson, who arrived in Australia in 1927, and continues to be influential. John Anderson had been a student of Henry Jones, who might therefore be said to have influenced both main strands of Australian philosophical thought. (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)

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)

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)

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)

This thesis is intended to analyze a mental phenomenon widely neglected in current philosophical discussions: personal memories. The first part presents a general framework to better understand what personal memories are, how we access our personal past and what we access about our personal past. Chapter 1 introduces traditional theories of memory: direct realism and representationalism in their different versions, as well as some objections. I defend here a particular form of representationalism that is based on the distinction between content, (...) intentional object and ontological object. Chapter 2 explores the possible contents of our personal memories, which prove to be heterogeneous, whereas chapter 3 analyses their possible intentional objects, with a special focus on past events. The second part of the thesis explores an aspect of our personal memories that was omitted in the first part: the senses in which our personal past is apprehended as personal. Chapter 4 examines the way in which the “self” intervenes in the construction of our personal memories. Chapters 5 and 6 focus on the analysis of what seems to be the most subjective aspect of our memories, that is, the emotions and feelings of our past experiences. In these last two chapters, I analyze the different interactions that can take place between memories and emotions and defend the idea that there can be emotional memories that are reducible neither to a propositional memory nor an occurrent and present emotion. The overall intention of this thesis is twofold. First, I aim to show to the philosophical community that there is still a lot to be said and discussed about memory as a mental phenomenon. And second, I intend to emphasize the importance of bringing into the philosophical discussions about the mind ideas coming from different philosophical traditions as well as ideas and empirical data coming from scientific research. (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)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in (...) the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (shrink)

The aim of this article is to critically examine what I call Action-Centric Theories of Representation (ACToRs). I include in this category theories of representation that (1) reject construing representation in terms of a relation that holds between representation itself (the representational vehicle) and what is represented, and instead (2) try to bring the function that representations play for cognitive systems to the center stage. Roughly speaking, according to proponents of ACToRs, what makes a representation (that is, what is constitutive (...) of it being a representation) is its being functionally involved in preselecting or guiding the actions of cognitive systems. I intend to argue that while definitely valuable, ACToRs are underconstrained and thus not entirely satisfying, since there exist structures that would count as representations according to ACToRs, but which do not play functional roles that could be nontrivially or in an explanatorily valuable way classified as representing something for a cognitive system. I outline a remedy for this theoretical situation by postulating that a fully satisfying theory of representation in cognitive science should have two factors; i.e., it should combine the pragmatic, action-oriented aspect present in ACToRs with an element that emphasizes the importance of the relation holding between a representational vehicle and what is represented. (shrink)

An interesting feature of some sets of representations is that their structure mirrors the structure of the items they represent. Founding an account of representational content on isomorphism, homomorphism or structural resemblance has proven elusive, however, largely because these relations are too liberal when the candidate structure over representational vehicles is unconstrained. Furthermore, in many cases where there is a clear isomorphism, it is not relied on in the way the representations are used. That points to a potential resolution: that (...) an isomorphism must be used, hence usable, if it is to be an ingredient in a theory of content. This paper argues that the class of exploitable isomorphisms can indeed play a content-constituting role. (shrink)

It's often hypothesized that the structure of mental representation is map-like rather than language-like. The possibility arises as a counterexample to the argument from the best explanation of productivity and systematicity to the language of thought hypothesis—the hypothesis that mental structure is compositional and recursive. In this paper, I argue that the analogy with maps does not undermine the argument, because maps and language have the same kind of compositional and recursive structure.

We show how an epistemology informed by cognitive science promises to shed light on an ancient problem in the philosophy of mathematics: the problem of exactness. The problem of exactness arises because geometrical knowledge is thought to concern perfect geometrical forms, whereas the embodiment of such forms in the natural world may be imperfect. There thus arises an apparent mismatch between mathematical concepts and physical reality. We propose that the problem can be solved by emphasizing the ways in which the (...) brain can transform and organize its perceptual intake. It is not necessary for a geometrical form to be perfectly instantiated in order for perception of such a form to be the basis of a geometrical concept. (shrink)

I argue that maps do not feature predication, as analyzed by Frege and Tarski. I take as my foil (Casati and Varzi, Parts and places, 1999), which attributes predication to maps. I argue that the details of Casati and Varzi’s own semantics militate against this attribution. Casati and Varzi emphasize what I call the Absence Intuition: if a marker representing some property (such as mountainous terrain) appears on a map, then absence of that marker from a map coordinate signifies absence (...) of the corresponding property from the corresponding location. Predication elicits nothing like the Absence Intuition. “F(a)” does not, in general, signify that objects other than a lack property F. On the basis of this asymmetry, I argue that attaching a marker to map coordinates is a different mode of semantic composition than attaching a predicate to a singular term. (shrink)

As a topic in the philosophy of psychology, dreaming is a fascinating, diverse, and severely underdeveloped area of study. The topic excites intense public interest in its own right, while also challenging our confidence that we know what the words “conscious” and “consciousness” mean. So dreaming should be at the forefront of our interdisciplinary investigations: theories of mind which fail to address the topic are incomplete. This chapter illustrates the tight links between conceptual and empirical issues by highlighting surprisingly deep (...) disagreements among leading dream scientists over what might seem basic aspects of their topic. (shrink)

This paper exploits the fact that the variability in the inter-spike intervals, in the spike train issuing from a neuron, carries substantial information regarding the input to the neuron. A framework for neuronal information processing is proposed which utilizes the above fact to distinguish phenomenal from non-phenomenal mental representation. In the process, an explanation is offered as to what is it, in the nature of conscious mental states, that imparts them a subjective feeling – there is something it is like (...) to be in those mental states. To give empirical support, it is shown how the proposed framework can neatly explain, the delay in eliciting conscious awareness as observed by Libet and the related backwards referral in time. (shrink)

I defend a theory of mental representation that satisfies naturalistic constraints. Briefly, we begin by distinguishing (i) what makes something a representation from (ii) given that a thing is a representation, what determines what it represents. Representations are states of biological organisms, so we should expect a unified theoretical framework for explaining both what it is to be a representation as well as what it is to be a heart or a kidney. I follow Millikan in explaining (i) in terms (...) of teleofunction, explicated in terms of natural selection. -/- To explain (ii), we begin by recognizing that representational states do not have content, that is, they are neither true nor false except insofar as they both “point to” or “refer” to something, as well as “say” something regarding whatever it is they are about. To distinguish veridical from false representations, there must be a way for these separate aspects to come apart; hence, we explain (ii) by providing independent theories of what I call f-reference and f-predication (the ‘f’ simply connotes ‘fundamental’, to distinguish these things from their natural language counterparts). -/- Causal theories of representation typically founder on error, or on what Fodor has called the disjunction problem. Resemblance or isomorphism theories typically founder on what I’ve called the non-uniqueness problem, which is that isomorphisms and resemblance are practically unconstrained and so representational content cannot be uniquely determined. These traditional problems provide the motivation for my theory, the structural preservation theory, as follows. F-reference, like reference, is a specific, asymmetric relation, as is causation. F-predication, like predication, is a non-specific relation, as predicates typically apply to many things, just as many relational systems can be isomorphic to any given relational system. Putting these observations together, a promising strategy is to explain f-reference via causal history and f-predication via something like isomorphism between relational systems. -/- This dissertation should be conceptualized as having three parts. After motivating and characterizing the problem in chapter 1, the first part is the negative project, where I review and critique Dretske’s, Fodor’s, and Millikan’s theories in chapters 2-4. Second, I construct my theory about the nature of representation in chapter 5 and defend it from objections in chapter 6. In chapters 7-8, which constitute the third and final part, I address the question of how representation is implemented in biological systems. In chapter 7 I argue that single-cell intracortical recordings taken from awake Macaque monkeys performing a cognitive task provide empirical evidence for structural preservation theory, and in chapter 8 I use the empirical results to illustrate, clarify, and refine the theory. (shrink)

A representationalist analysis of strong first-person phenomena is developed (Baker 1998), and it is argued that conscious, cognitive self-reference can be naturalized under this representationalist analysis. According to this view, the phenomenal first-person perspective is a condition of possibility for the emergence of a cognitive first-person perspective. Cognitive self-reference always is reference to the phenomenal content of a transparent self-model. The concepts of phenomenal transparency and introspection are clarified. More generally, I suggest that the concepts of phenomenal opacity and phenomenal (...) transparency are interesting instruments for analyzing conscious, self-representational content, and that their relevance in understanding reflexive, i.e., cognitive subjectivity may have been overlooked in the past. (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.

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)

Despite the fact that the notion of internal representation has - at least according to some - a fundamental role to play in the sciences of the mind, not only has its explanatory utility been under attack for a while now, but it also remains unclear what criteria should an explanation of a given cognitive phenomenon meet to count as a representational explanation in the first place. The aim of this article is to propose a solution to this latter problem. (...) I will assume that representational explanations should be construed as a form of mechanistic explanations and proceed by proposing a general sketch of a functional architecture of a representational cognitive mechanism. According to the view on offer here, representational mechanisms are mechanisms that meet four conditions: the structural resemblance condition, the action-guidance condition, the decouplability condition, and the error-detection condition. (shrink)

Models of memory in cognitive science and philosophy have traditionally explained human remembering in terms of storage and retrieval. This tendency has been entrenched by reliance on computationalist explanations over the course of the twentieth century; even research programs that eschew computationalism in name, or attempt the revision of traditional models, demonstrate tacit commitment to computationalist assumptions. It is assumed that memory must be stored by means of an isomorphic trace, that memory processes must divide into conceptually distinct systems and (...) phases, and that human remembering consists in inner, cognitive processes that are implemented by distinct neural processes. This dissertation draws on recent empirical work, and on philosophical arguments from Ludwig Wittgenstein and others, to demonstrate that this latent computationalism in the study of memory is problematic, and that it can and should be eliminated. Cognitive psychologists studying memory have encountered numerous data in recent decades that belie archival models. In cognitive neuroscience, establishing the neural basis of storage and retrieval processes has proven elusive. A number of revised models on offer in memory science, that have taken these issues into account, fail to sufficiently extricate the archival framework. Several impasses in memory science are products of these underlying computationalist assumptions. Wittgenstein and other philosophers offer a number of arguments against the need for, and the efficacy of, the storage and retrieval of traces in human remembering. A study of these arguments clarifies the ways that these computationalist assumptions are presently impeding the science of memory, and provides ways forward in removing them. We can and should characterize and model human memory without invoking the storage and retrieval of traces. A range of work in connectionism, dynamical systems theory, and recent philosophical accounts of memory demonstrate how the science of memory can proceed without these assumptions, toward non-archival models of remembering. (shrink)

Does the existence of body representations undermine the explanatory role of the body? Or do certain types of representation depend so closely upon the body that their involvement in a cognitive task implicates the body itself? In the introduction of this special issue we explore lines of tension and complement that might hold between the notions of embodiment and body representations, which remain too often neglected or obscure. To do so, we distinguish two conceptions of embodiment that either put weight (...) on the explanatory role of the body itself or body representations. We further analyse how and to what extent body representations can be said to be embodied. Finally, we give an overview of the full volume articulated around foundational issues (How should we define the notion of embodiment? To what extent and in what sense is embodiment compatible with representationalism? To what extent and in what sense are sensorimotor approaches similar to behaviourism?) and their applications in several cognitive domains (perception, concepts, selfhood, social cognition). (shrink)

Current orthodoxy in the philosophy of perception views indirect realism as misguided, wrongheaded or simply outdated. The reasons for its pariah status are variegated. Although it is surely not unreasonable to speculate that philosophical fashion is one factor that contributes to this situation, there are also solid philosophical arguments which put pressure on the indirect realist position. In this paper, I will discuss one such main objection and show how the indirect realist can face it. The upshot will be a (...) defence of a new structural account of indirect realism which is immune to a number of objections that have been traditionally levelled at such theories of perceptual consciousness. (shrink)

Mirror neurons and systems are often appealed to as mechanisms enabling mindreading, i.e., understanding other people’s mental states. Such neural mirroring processes are often treated as instances of mental simulation rather than folk psychological theorizing. I will call into question this assumed connection between mirroring and simulation, arguing that mirroring does not necessarily constitute mental simulation as specified by the simulation theory of mindreading. I begin by more precisely characterizing “mirroring” (Sect. 2) and “simulation” (Sect. 3). Mirroring results in a (...) neural process in an observer that resembles a neural process of the same type in the observed agent. Although simulation is often characterized in terms of resemblance (Goldman, Simulating minds: The philosophy, psychology, and neuroscience of mindreading, 2006), I argue that simulation requires more than mere interpersonal mental resemblance: A simulation must have the purpose or function of resembling its target (Sect. 3.1). Given that mirroring processes are generated automatically, I focus on what is required for a simulation to possess the function of resembling its target. In Sect. 3.2 I argue that this resemblance function, at least in the case of simulation-based mindreading, requires that a simulation serve as a representation or stand-in of what it resembles. With this revised account of simulation in hand, in Sect. 4 I show that the mirroring processes do not necessarily possess the representational function required of simulation. To do so I describe an account of goal attribution involving a motor mirroring process that should not be characterized as interpersonal mental simulation. I end in Sect. 5 by defending the conceptual distinction between mirroring and simulation, and discussing the implications of this argument for the kind of neuroscientific evidence required by simulation theory. (shrink)

Some proponents of structural representations (henceforth, structuralists) claim that no other theory of representation can legitimatize the explanatory appeals that cognitive science makes to mental content. Because other naturalistic approaches to representation purportedly posit an arbitrary relation between representing vehicles and representational content, these approaches must appeal to the role played by a representation, i.e., how it is used by the system in which it is embedded, to ground its content. This is in supposed contrast to structural representations, in which (...) the relation of resemblance results in a non-arbitrary relationship between vehicles and content. Structuralists argue that, as a result, approaches that posit structural representations can, and alternative approaches cannot, explain how representational content can be causally relevant in the production of behavior. In this paper, I will argue that structural representations are susceptible to the very same critiques that proponents level against what they sometimes refer to as “use” theories. This, I contend, is not surprising given that a theory of structural representations is, in fact, just as much a use-theory as alternative approaches. (shrink)

Whilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual account of (...) two features of structural representations: structural similarity and decoupling. We argue that structural similarity can be analysed in terms of two dimensions: number of preserved relations and state space granularity. Both dimensions can take on different values and hence render structural similarity gradual. We further argue that decoupling is gradual in two ways. First, we show that different brain areas are involved in decoupled cognitive processes to a greater or lesser degree depending on the cause (internal or external) of their activity. Second, and more importantly, we show that the degree of decoupling can be further regulated in some brain areas through precision weighting of prediction error. We lastly argue that gradation of decoupling (via precision weighting) and gradation of structural similarity (via state space granularity) are conducive to behavioural success. (shrink)

This paper is concerned with representational explanations of how one experiences and acts with one’s body as an integrated whole. On the standard view, accounts of bodily experience and action must posit a corresponding representational structure: a representation of the body as an integrated whole. The aim of this paper is to show why we should instead favour the minimal view: given the nature of the body, and representation of its parts, accounts of the structure of bodily experience and action (...) need not appeal to a representation of the body as an integrated whole. The argument proceeds by distinguishing two kinds of explanatory roles for representations: standing-in for absent targets and structuring ambiguous sensory information concerning a target. Representations of body-parts are suited to fulfil both kinds of explanatory role, whereas a representation of the body as an integrated whole is only suited to fulfil the latter, as a means of coordinating representations of body-parts. It is then argued that the structure of the body can itself serve as a means of coordinating body-part representations, rendering representation of the body as an integrated whole explanatorily superfluous. (shrink)

Traditionally, intentionality is regarded as that feature of all and only mental states – paradigmatically beliefs and desires – in virtue of which they are directed at or are about something. The problem of intentionality is to explain how it fits into the natural order given the intuition that no physical entity can be intentionally directed in this sense. The basic assumption of this paper, proposed by enactivists, is that failure to naturalize intentionality and mental representation is partly due to (...) the fact that most participants in the debate take intentionality and mental representation to be equivalent. In contrast, it is proposed to treat intentionality as a feature of whole embodied agents (paradigmatically organisms) who can be directed at objects and states of affairs in various ways, while representation should be regarded as a feature of mental states (and their respective vehicles or underlying mechanisms). The present paper develops and motivates the distinction, applies it to Metzinger’s project of naturalizing phenomenal representation, and demonstrates the range of theoretical options with respect to a delineation of cognition given the enactive proposal. It is taken as problematic that enactivism takes the realm of cognition to be identical to the realm of biology. Instead, a constraint on a theory of intentionality and representation is that it should delineate the subject matter of cognitive science and distinguish it from other sciences, also to leave room for the possibility of artificial intelligence. One important implication of the present proposal is that there can be creatures which can be intentionally directed without having the capacity to represent. That is, their intentionality is restricted to being able to be directed at existent things. Only creatures in possession of the right kind of neurocognitive architecture can produce and sustain representations in order to be directed at non-existent things. It is sketched how this approach conceives of intentionality as a developmental and layered concept, allowing for a hierarchical model of varieties of intentionality, ranging from the basic pursuit of local environmental goals to thoughts about fictional objects. (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)

We offer to extend structural realism into the field of mind and brain studies. The naturalised metaphysics of structural realism has been defined in terms of unification of sciences. The unification program has been carried out nicely in fields of Quantum Mechanics and General Relativity. But for the structural realist metaphysics to receive a recommendation, the unification program needs to be extended to the fields of especial sciences. Our aim in the paper is twofold. On the one hand, we present (...) a structural realist theory of the brain that is well-supported by the best theories of computational neurosciences. On the other hand, and at the same time, we provide further reason for being optimistic about the structural realism metaphysical claim which is based on the idea of unification in sciences. (shrink)

A promising strategy for defending the role that representation plays in explanations of cognition frames the concept in terms of internal models or map‐like mechanisms. “Structural representation” offers an account of representation that is grounded in well‐specified, empirical criteria. However, anti‐representationalists continue to press the issue of how to account for the paradigmatic semantic properties of representation at the subpersonal level. In this paper, I offer an account of how the proponent of structural representation should think about content. There are (...) really two problems of content any account of representation must overcome: the “hard problem of content” and the “content determination problem.” I argue that the structural representation account has the resources to provide a naturalistically respectable notion of content that overcomes both problems. (shrink)

In this paper I am advocating a structuralist theory of mental representation. For a structuralist theory of mental representation to be defended satisfactorily, the naturalistic and causal constraints have to be satisfied first. The more intractable of the two, i.e., the naturalistic constraint, indicates that to account for the mental representation, we should not invoke “a full-blown interpreting mind”. So, the aim of the paper is to show how the naturalistic and causal constraints could be satisfied. It aims to offer (...) a strategy for grounding the structure of the mental representations in nature. The strategy that I offer is inspired by Marcello Barbieri’s code model of biosemiotics. (shrink)

Millikan [2000] has levelled a number of persuasive criticisms against Cummins's [1996] theory of mental representation. In this paper, I pave a middle path in the debate between Cummins [2000] and Millikan [2000] to answer two questions. How are representations applied to targets? How is the content of a representation determined? The result is a new theory of mental representation, which I call narrow structuralism.

This paper analyzes the rapid and unexpected rise of deep learning within Artificial Intelligence and its applications. It tackles the possible reasons for this remarkable success, providing candidate paths towards a satisfactory explanation of why it works so well, at least in some domains. A historical account is given for the ups and downs, which have characterized neural networks research and its evolution from “shallow” to “deep” learning architectures. A precise account of “success” is given, in order to sieve out (...) aspects pertaining to marketing or sociology of research, and the remaining aspects seem to certify a genuine value of deep learning, calling for explanation. The alleged two main propelling factors for deep learning, namely computing hardware performance and neuroscience findings, are scrutinized, and evaluated as relevant but insufficient for a comprehensive explanation. We review various attempts that have been made to provide mathematical foundations able to justify the efficiency of deep learning, and we deem this is the most promising road to follow, even if the current achievements are too scattered and relevant for very limited classes of deep neural models. The authors’ take is that most of what can explain the very nature of why deep learning works at all and even very well across so many domains of application is still to be understood and further research, which addresses the theoretical foundation of artificial learning, is still very much needed. (shrink)

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...) convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)