In this paper, we propose that an increasingly regarded theoretical framework in neuroscience—the predictive processing framework—can help to advance an understanding of the foundations of critical thinking as well as provide a mechanistic hypothesis for how education may increase a learner’s subsequent use of critical thinking outside of an educational context. We begin by identifying a lacuna in the understanding of critical thinking: a causal account of the internal triggers to think critically. We then introduce the predictive processing framework to (...) address this lacuna, and unpack the implications of this framework for understanding the deployment of critical thinking skills in situ, in the real world. (shrink)

There has been much criticism of the idea that Friston's free-energy principle can unite the life and mind sciences. Here, we argue that perhaps the greatest problem for the totalizing ambitions of its proponents is a failure to recognize the importance of evolutionary dynamics and to provide a convincing adaptive story relating free-energy minimization to organismal fitness.

I discuss Clark’s predictive processing/extended mind hybrid, diagnosing a problem: Clark’s hybrid suggests that, when we use them, we pay attention to mind-extending external resources. This clashes with a commonly accepted necessary condition of cognitive extension; namely, that mind-extending resources must be phenomenally transparent when used. I then propose a solution to this problem claiming that the phenomenal transparency condition should be rejected. To do so, I put forth a parity argument to the effect that phenomenal transparency cannot be a (...) necessary condition on cognitive extension: roughly, since internal cognitive resources can fail to be transparent when used, by parity, external resources can fail to be phenomenally transparent too. Further, I argue that phenomenal transparency is not even a reliable indicator of cognitive extension; hence its absence should not be considered a problem for Clark’s extended mind-predictive processing hybrid. Lastly, I consider and allay a number of worries my proposal might raise, and conclude the paper. (shrink)

In order to meet the explanatory challenge levelled against non-representationalist views on cognition, radical enactivists claim that cognition about potentially absent targets involves the socioculturally scaffolded capacity to manipulate public symbols. At a developmental scale, this suggests that higher cognition gradually emerges as humans begin to master language use, which takes place around the third year of life. If, however, it is possible to show that pre-linguistic infants represent their surroundings, then the radical enactivists’ explanation for the emergence of higher (...) cognition is defeated. In this paper, I critically assess experiments designed to show that pre-linguistic infants inherit representational abilities. I begin by outlining these experiments in Sect. 2. In Sect. 3, I argue that these experiments only succeed in supporting widespread representationalism by committing a particular kind of circular reasoning, which I call conjunctivist reasoning due to its origins in the debates about the nature of perception. I conclude by developing two independent yet congruent enactivist lines of interpretation for the experiments discussed in 2. I explain the infants’ responses to atypical experimental conditions based on agent-environment codetermination and then I argue that surprise behavior can be explained in terms of embodied habits and unfulfilled anticipation. (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)

4Es approaches to cognition draw an unconventional picture of cognitive processes and of the mind. Instead of conceiving of cognition as a process that always takes place within the boundaries of the skull and the skin, these approaches hold that cognition is a situated process that often extends beyond human agents’ physical boundaries. In particular, supporters of the extended mind theory and of the enactive approach claim that embodied action in a perceptually complex environment is constitutive of cognitive processes, and (...) thus of the mind. (Chapter 1). Although both draw an extended picture of cognition and of the mind, supporters of the extended mind and supporters of the enactive approach disagree on the value of internal representations in perceptually-guided action. The extended mind theory holds that we need to posit internal action-oriented representations (AORs). AORs are valuable -the argument goes- because they account for action-selection, action-control, and for the prediction of incoming perceptual information. Advocates of the enactive approach to cognition, instead, argue against AORs. Firstly, they argue that AORs do not fulfill the necessary conditions for the identification of representational entities. Therefore, that of AOR is an ill-conceived epistemic construct. Secondly, they argue that AORs are expressive of an internalist prejudice, which makes the extended mind theory weaker than it should be from an explanatory and metaphysical point of view. I endorse both these arguments advanced by supporters of the enactive approach. Moreover, through a semiotic analysis of the construct and of the workings of AORs, I show that AORs are not active at all. Hence, I argue that AORs do not do the job they are supposed to do: extending the mind’s boundaries by explaining our perceptual relation with the world as an active, embodied, and world-involving process. Therefore, I suggest that the construct of AOR ought to be dismissed - at least in current projects in 4Es cognition (Chapter 2). I argue that similar arguments apply to recent attempts to make predictive processing accounts of perceptually-guided action more aligned with 4Es approaches to cognitive science by appealing to predictive internal models of our perceptual world. I thus propose an alternative explanation of the key features of perceptually-guided action that AORs and these internal models are supposed to be grasp. Action-control, action-selection, and the anticipatory aspects of action-perception loops can be explained by appealing to embodied actions in a field of relevant affordances, which are perceived as such based on the agent’s motor skills and motives. Furthermore, I suggest that, by combining the enactive approach to cognition with an analysis of the indexical features of our perceptual environment, we can explain perceptually-guided action in a way that truly accounts for our minds as entities that often extend beyond our skulls and skin. And we can do so without holding onto spooking entities like AORs and internal predictive models. (Chapter 3). (shrink)

Much of our everyday, embodied action comes in the form of smooth coping. Smooth coping is skillful action that has become habituated and ingrained, generally placing less stress on cognitive load than considered and deliberative thought and action. When performed with skill and expertise, walking, driving, skiing, musical performances, and short-order cooking are all examples of the phenomenon. Smooth coping is characterized by its rapidity and relative lack of reflection, both being hallmarks of automatization. Deliberative and reflective actions provide the (...) contrast case. In Dreyfus’ classic view, smooth coping is “mindless” absorption into action, being in the flow, and any reflective thought will only interrupt this flow. Building on the pragmatist account of Dewey, others, such as Sutton, Montero, and Gallagher, insist on the intelligent flexibility built into smooth coping, suggesting that it is not equivalent to automatization. We seek to answer two complementary challenges in this article. First, how might we model smooth coping in autonomous agents at fine granularity? Second, we use this model of smooth coping to show how we might implement smooth coping in artificial intelligent agents. We develop a conceptual model of smooth coping in LIDA. LIDA is an embodied cognitive architecture implementing the global workspace theory of consciousness, among other psychological theories. LIDA’s implementation of consciousness enables us to account for the phenomenology of smooth coping, something that few cognitive architectures would be able to do. Through the fine granular analysis of LIDA, we argue that smooth coping is a sequence of automatized actions intermittently interspersed with consciously mediated action selection, supplemented by dorsal stream processes. In other words, non-conscious, automatized actions often require occasional bursts of conscious cognition to achieve the skillful and flexible adjustments of smooth coping. In addition, never-conscious dorsal stream information and associated sensorimotor processes provide further online adjustments during smooth coping. To achieve smooth coping in LIDA we introduce a new module to the LIDA cognitive architecture the Automatized Action Selection sub-module. Our complex model of smooth coping borrows notions of “embodied intelligence” from enactivism and augments these by allowing representations and more detailed mechanisms of conscious control. We explore several extended examples of smooth coping, starting from basic activities like walking and scaling up to more complex tasks like driving and short-order cooking. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising levels (...) of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (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)

On an ‘internalist’ picture, knowledge isn’t necessary for understanding the nature of perception and perceptual experience. This contrasts with the ‘knowledge first’ picture, according to which it’s essential to the nature of successful perceiving as a mental state that it’s a way of knowing. It’s often thought that naturalistic theorizing about the mind should adopt the internalist picture. However, I argue that a powerful, recently prominent framework for scientific study of the mind, ‘predictive processing,’ instead supports the knowledge first picture. (...) Under predictive processing, it’s intrinsic to successful perceiving that it’s a state with the kind of modal robustness that’s distinctive of knowledge, which gives us reason to think of successful perceiving along knowledge first lines. Furthermore, I argue that the predictive processing framework encourages us to conceptualize experiences which don’t amount to knowledge along knowledge first lines, as states which by their nature fall short of knowledge. (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)

Structural representations are increasingly popular in philosophy of cognitive science. A key virtue they seemingly boast is that of meeting Ramsey's job description challenge. For this reason, structural representations appear tailored to play a clear representational role within cognitive architectures. Here, however, I claim that structural representations do not meet the job description challenge. This is because even our most demanding account of their functional profile is satisfied by at least some receptors, which paradigmatically fail the job description challenge. Hence, (...) the functional profile typically associated with structural representations does not identify representational posits. After a brief introduction, I present, in the second section of the paper, the job description challenge. I clarify why receptors fail to meet it and highlight why, as a result, they should not be considered representations. In the third section I introduce what I take to be the most demanding account of structural representations at our disposal, namely Gładziejewski's account. Provided the necessary background, I turn from exposition to criticism. In the first half of the fourth section, I equate the functional profile of structural representations and receptors. To do so, I show that some receptors boast, as a matter of fact, all the functional features associated with structural representations. Since receptors function merely as causal mediators, I conclude structural representations are mere causal mediators too. In the second half of the fourth section I make this conclusion intuitive with a toy example. I then conclude the paper, anticipating some objections my argument invites. (shrink)

What is the content of a mental state? This question poses the problem of intentionality: to explain how mental states can be about other things, where being about them is understood as representing them. A framework that integrates predictive coding and signaling systems theories of cognitive processing offers a new perspective on intentionality. On this view, at least some mental states are evaluations, which differ in function, operation, and normativity from representations. A complete naturalistic theory of intentionality must account for (...) both types of intentional state. (shrink)

Predictive processing (PP) has been repeatedly presented as a unificatory account of perception, action, and cognition. In this paper, we argue that this is premature: As a unifying theory, PP fails to deliver general, simple, homogeneous, and systematic explanations. By examining its current trajectory of development, we conclude that PP remains only loosely connected both to its computational framework and to its hypothetical biological underpinnings, which makes its fundamentals unclear. Instead of offering explanations that refer to the same set of (...) principles, we observe systematic equivocations in PP‐based models, or outright contradictions with its avowed principles. To make matters worse, PP‐based models are seldom empirically validated, and they are frequently offered as mere just‐so stories. The large number of PP‐based models is thus not evidence of theoretical progress in unifying perception, action, and cognition. On the contrary, we maintain that the gap between theory and its biological and computational bases contributes to the arrested development of PP as a unificatory theory. Thus, we urge the defenders of PP to focus on its critical problems instead of offering mere re‐descriptions of known phenomena, and to validate their models against possible alternative explanations that stem from different theoretical assumptions. Otherwise, PP will ultimately fail as a unified theory of cognition. (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)

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)

We present a multiscale integrationist interpretation of the boundaries of cognitive systems, using the Markov blanket formalism of the variational free energy principle. This interpretation is intended as a corrective for the philosophical debate over internalist and externalist interpretations of cognitive boundaries; we stake out a compromise position. We first survey key principles of new radical views of cognition. We then describe an internalist interpretation premised on the Markov blanket formalism. Having reviewed these accounts, we develop our positive multiscale account. (...) We argue that the statistical seclusion of internal from external states of the system—entailed by the existence of a Markov boundary—can coexist happily with the multiscale integration of the system through its dynamics. Our approach does not privilege any given boundary, nor does it argue that all boundaries are equally prescient. We argue that the relevant boundaries of cognition depend on the level being characterised and the explanatory interests that guide investigation. We approach the issue of how and where to draw the boundaries of cognitive systems through a multiscale ontology of cognitive systems, which offers a multidisciplinary research heuristic for cognitive science. (shrink)

A leading theoretical framework for naturalistic explanation of mind holds that we explain the mind by positing progressively "stupider" capacities ("homunculi") until the mind is "discharged" by means of capacities that are not intelligent at all. The so-called homuncular fallacy involves violating this procedure by positing the same capacities at subpersonal levels. I argue that the homuncular fallacy is not a fallacy, and that modern-day homunculi are idle posits. I propose an alternative view of what naturalism requires that reflects how (...) the cognitive sciences are actually integrating mind and matter. (shrink)

I argue that Sellars’s distinction between signifying and picturing should be taken seriously by philosophers of mind, language, and cognition. I begin with interpretations of key Sellarsian texts in order to show that picturing is best understood as a theory of non-linguistic cognitive representations through which animals navigate their environments. This is distinct from the kind of discursive cognition that Sellars called ‘signifying’ and which is best understood in terms of socio-linguistic inferences. I argue that picturing is required because reflection (...) on signifying cannot adequately explain our need for cognitive friction. I then show how the idea of picturing is further developed by Paul Churchland, Ruth Garrett Millikan, and Huw Price. I finally turn to predictive processing as a theory of cognitive representation, and in particular Andy Clark’s ‘radical predictive processing’, to further characterize picturing. However, doing so has the cost of pushing picturing and signifying further apart than Sellars intended. (shrink)

This paper starts by considering an argument for thinking that predictive processing (PP) is representational. This argument suggests that the Kullback–Leibler (KL)-divergence provides an accessible measure of misrepresentation, and therefore, a measure of representational content in hierarchical Bayesian inference. The paper then argues that while the KL-divergence is a measure of information, it does not establish a sufficient measure of representational content. We argue that this follows from the fact that the KL-divergence is a measure of relative entropy, which can (...) be shown to be the same as covariance (through a set of additional steps). It is well known that facts about covariance do not entail facts about representational content. So there is no reason to think that the KL-divergence is a measure of (mis-)representational content. This paper thus provides an enactive, non-representational account of Bayesian belief optimisation in hierarchical PP. (shrink)

We evaluate a growing trend towards anti-representationalism in cognitive science in the context of recent research into the development and maintenance of anorexia nervosa in cognitive neuropsychiatry. We argue two things: first, that this research relies on an explanatorily robust concept of representation—the concept of a long-term body schema; second, that this body representation underlies our most basic environmental interactions and affordance perception—the psychological phenomena supposed to be most hospitable to a non-representationalist treatment.

Predictive Processing (PP) framework construes perception and action (and perhaps other cognitive phenomena) as a matter of minimizing prediction error, i.e. the mismatch between the sensory input and sensory predictions generated by a hierarchically organized statistical model. There is a question of how PP fits into the debate between traditional, neurocentric and representation-heavy approaches in cognitive science and those approaches that see cognition as embodied, environmentally embedded, extended and (largely) representation-free. In the present paper, I aim to investigate and clarify (...) the cognitivist or ‘conservative’ reading of PP. I argue that the conservative commitments of PP can be divided into three distinct categories: (1) representationalism, (2) inferentialism, and (3) internalism. I show how these commitments and their relations should be understood and argue for an interpretation of each that is both non-trivial and largely ecumenical towards the 4E literature. Conservative PP is as progressive as conservatism gets. (shrink)

O presente artigo objetiva fornecer uma apresentação crítica, compreensiva e inédita na língua portuguesa do Processamento Preditivo (PP) – um esquema teórico para a compreensão da cognição que propõe uma inversão de nosso entendimento padrão da ação, percepção, sensação e sua relação. Aqui, nosso objetivo primário será introduzir os principais conceitos e ideias do PP, tratando-o como um modelo moderadamente corporificado de cognição e analisando suas credenciais como uma proposta teórica unificadora. Para tanto, partiremos de uma contextualização histórica de algumas (...) correntes de pensamento que teriam fomentado seu desenvolvimento inicial, passando por uma descrição não-matemática do Princípio da Energia Livre, que fundamenta e subentende a atuação de suas especificidades para, então, esclarecermos o papel que, segundo o PP, a inferência bayesiana, a minimização dos erros de predição e a chamada Inferência Ativa possuiriam na manutenção homeostática de nossos cérebros e corpos preditivos. Por fim, forneceremos uma síntese de algumas consequências daquilo que o PP poderia trazer à compreensão contemporânea do cérebro e comportamento humanos, concluindo que, embora sua descrição da cognição como um processo preditivo único e contínuo prometa eventualmente unificar paradigmas explicativos e níveis de análise distintos, por ora, talvez seja melhor concebê-lo de forma mais modesta, como uma ferramenta ou heurística para nos auxiliar a repensar vários dos tópicos centrais ao estudo científico e filosófico da mente. (shrink)

In this paper I return to Hubert Dreyfus’ old but influential critique of artificial intelligence, redirecting it towards contemporary predictive processing models of the mind (PP). I focus on Dreyfus’ arguments about the “frame problem” for artificial cognitive systems, and his contrasting account of embodied human skills and expertise. The frame problem presents as a prima facie problem for practical work in AI and robotics, but also for computational views of the mind in general, including for PP. Indeed, some of (...) the issues it presents seem more acute for PP, insofar as it seeks to unify all cognition and intelligence, and aims to do so without admitting any cognitive processes or mechanisms outside of the scope of the theory. I contend, however, that there is an unresolved problem for PP concerning whether it can both explain all cognition and intelligent behavior as minimizing prediction error with just the core formal elements of the PP toolbox, and also adequately comprehend (or explain away) some of the apparent cognitive differences between biological and prediction-based artificial intelligence, notably in regard to establishing relevance and flexible context-switching, precisely the features of interest to Dreyfus’ work on embodied indexicality, habits/skills, and abductive inference. I address several influential philosophical versions of PP, including the work of Jakob Hohwy and Andy Clark, as well as more enactive-oriented interpretations of active inference coming from a broadly Fristonian perspective. (shrink)

Neural structural representations are cerebral map- or model-like structures that structurally resemble what they represent. These representations are absolutely central to the “cognitive neuroscience revolution”, as they are the only type of representation compatible with the revolutionaries’ mechanistic commitments. Crucially, however, these very same commitments entail that structural representations can be observed in the swirl of neuronal activity. Here, I argue that no structural representations have been observed being present in our neuronal activity, no matter the spatiotemporal scale of observation. (...) My argument begins by introducing the “cognitive neuroscience revolution” (Sect. 1 ) and sketching a prominent, widely adopted account of structural representations (Sect. 2 ). Then, I will consult various reports that describe our neuronal activity at various spatiotemporal scales, arguing that none of them reports the presence of structural representations (Sect. 3 ). After having deflected certain intuitive objections to my analysis (Sect. 4 ), I will conclude that, in the absence of neural structural representations, representationalism and mechanism can’t go together, and so the “cognitive neuroscience revolution” is forced to abandon one of its commitments (Sect. 5 ). (shrink)

Debunking arguments aim to undermine common sense beliefs by showing that they are not explanatorily or causally linked to the entities they are purportedly about. Rarely are facts about the aetiology of common sense beliefs invoked for the opposite aim, that is, to support the reality of entities that furnish our manifest image of the world. Here I undertake this sort of un-debunking project. My focus is on the metaphysics of ordinary physical objects. I use the view of perception as (...) approximate Bayesian inference to show how representations of ordinary objects can be extracted from sensory input in a rational and truth-tracking manner. Drawing an analogy between perception construed as Bayesian hypothesis testing and scientific inquiry, I sketch out how some of the intuitions that traditionally inspired arguments for scientific realism also find application with regards to proverbial tables and chairs. (shrink)

Predictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle —a normative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., representational versus non-representational. Here we argue that these different interpretations depend on implicit assumptions about what qualifies as representational. We deploy the Free Energy Principle instrumentally to distinguish four main notions of representation, which focus on organizational, (...) structural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that traditionally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demonstrates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what representations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate. (shrink)

Ecological psychologists and enactivists agree that the best explanation for a large share of cognition is nonrepresentational in kind. In both ecological psychology and enactivist philosophy, then, the task is to offer an explanans that does not rely on representations. Different theorists within these camps have contrasting notions of what the best kind of nonrepresentational explanation will look like, yet they agree on one central point: instead of focusing solely on factors interior to an agent, an important aspect of cognition (...) is found in the link or coupling between an agent and the external world. This link is fluid, dynamic, and active in a variety of ways, and we do not need to add any internal extra something in the perception-action-cognition process. At the same time, even devout defenders of ecological psychology and enactivism recognize that plenty happens inside an agent during cognition. In particular, no one denies that the brain plays an important role. What, then, is the role of the brain if it’s not in the game of representing the environment? One possible option is to describe the brain as a resonant organ instead of a representational organ. In this paper we consider the history of resonance in more detail. Particular focus will be placed on two different sets of approaches that have developed the concept of resonance: a representational reading of resonance and a nonrepresentational, dynamic account of resonance. We then apply these accounts to a case study on music performance, specifically in the context of standard tonal jazz. From this application, we propose that a nonrepresentational resonance account consistent with both enactivism and ecological psychology is a viable way of explaining jazz performance. We conclude with future considerations on research regarding the brain as a resonant organ. (shrink)

It has been pointed out that Sensorimotor Enactivism, a theory that claims that perception is enacted and brought about by movement, says very little about the neural mechanisms that enable perception. For the proponents of the predictive approach to Sensorimotor Enactivism, this is a challenge that can be met by introducing predictive processing into the picture. However, the compatibility between these theories is not straightforward. Firstly, because they seem to differ in their stand towards representations: while Sensorimotor Enactivism is said (...) to belong to the non-representational wing of cognitive science, predictive processing has a representational profile. And secondly, because they exhibit different explanatory strategies: while Sensorimotor Enactivism prioritizes the interactions of the embodied agent, predictive processing has internalist commitments. The aim of this paper is to address these concerns and show that a predictive approach to Sensorimotor Enactivism is viable. More specifically, I focus on the Free-Energy approach, a theory that falls within the ballpark of predictive processing. In this paper I argue for the following claims. I argue that both Sensorimotor Enactivism and the Free-Energy approach may be understood for some systems in representational terms. The non-representational reading of Sensorimotor Enactivism is not mandatory and neither is the representational reading of the Free-Energy approach. Sensorimotor Enactivism is, in this respect, compatible with both representational and non-representational interpretations of the FEA. So, the position towards representations of these frameworks should not stand in the way of a predictive approach to Sensorimotor Enactivism. I also show that the Free-Energy approach allows for an account that prioritizes the interaction of the embodied agent with the environment. This is the explanatory strategy followed by Sensorimotor Enactivism. To justify this strategy and following other proponents of Sensorimotor Enactivism, I argue that by referring to the interactions of the embodied agent a better account of the phenomena in question is provided. On this basis, I claim that Sensorimotor Enactivism and the Free-Energy approach are compatible in what concerns their explanatory strategy as well. Thus, making the case for the viability of the predictive approach to Sensorimotor Enactivism. (shrink)

Predictive processing has recently been advanced as a global cognitive architecture for the brain. I argue that its commitments concerning the nature and format of cognitive representation are inadequate to account for two basic characteristics of conceptual thought: first, its generality—the fact that we can think and flexibly reason about phenomena at any level of spatial and temporal scale and abstraction; second, its rich compositionality—the specific way in which concepts productively combine to yield our thoughts. I consider two strategies for (...) avoiding these objections and I argue that both confront formidable challenges. (shrink)

Predictive processing and its apparent commitment to explaining cognition in terms of Bayesian inference over hierarchical generative models seems to flatly contradict the pragmatist conception of mind and experience. Against this, I argue that this appearance results from philosophical overlays at odd with the science itself, and that the two frameworks are in fact well-poised for mutually beneficial theoretical exchange. Specifically, I argue: first, that predictive processing illuminates pragmatism’s commitment to both the primacy of pragmatic coping in accounts of the (...) mind and the profound organism-relativity of experience; second, that this pragmatic, “narcissistic” character of prediction error minimization undermines its ability to explain the distinctive normativity of intentionality; and third, that predictive processing therefore mandates an extra-neural account of intentional content of exactly the sort that pragmatism’s communitarian vision of human thought can provide. (shrink)

A weak version of the life-mind continuity thesis entails that every living system also has a basic mind (with a non-representational form of intentionality). The strong version entails that the same concepts that are sufficient to explain basic minds (with non-representational states) are also central to understanding non-basic minds (with representational states). We argue that recent work on the free energy principle supports the following claims with respect to the life-mind continuity thesis: (i) there is a strong continuity between life (...) and mind; (ii) all living systems can be described as if they had representational states; (iii) the ’as-if representationality’ entailed by the free energy principle is central to understanding both basic forms of intentionality and intentionality in non-basic minds. In addition to this, we argue that the free energy principle also renders realism about computation and representation compatible with a strong life-mind continuity thesis (although the free energy principle does not entail computational and representational realism). In particular, we show how representationality proper can be grounded in ’as-if representationality’. (shrink)

It has been pointed out that Sensorimotor Enactivism, a theory that claims that perception is enacted and brought about by movement, says very little about the neural mechanisms that enable perception. For the proponents of the predictive approach to Sensorimotor Enactivism, this is a challenge that can be met by introducing predictive processing into the picture. However, the compatibility between these theories is not straightforward. Firstly, because they seem to differ in their stand towards representations: while Sensorimotor Enactivism is said (...) to belong to the non-representational wing of cognitive science, predictive processing has a representational profile. And secondly, because they exhibit different explanatory strategies: while Sensorimotor Enactivism prioritizes the interactions of the embodied agent, predictive processing has internalist commitments. The aim of this paper is to address these concerns and show that a predictive approach to Sensorimotor Enactivism is viable. More specifically, I focus on the Free-Energy approach, a theory that falls within the ballpark of predictive processing. In this paper I argue for the following claims. I argue that both Sensorimotor Enactivism and the Free-Energy approach may be understood for some systems in representational terms. The non-representational reading of Sensorimotor Enactivism is not mandatory and neither is the representational reading of the Free-Energy approach. Sensorimotor Enactivism is, in this respect, compatible with both representational and non-representational interpretations of the FEA. So, the position towards representations of these frameworks should not stand in the way of a predictive approach to Sensorimotor Enactivism. I also show that the Free-Energy approach allows for an account that prioritizes the interaction of the embodied agent with the environment. This is the explanatory strategy followed by Sensorimotor Enactivism. To justify this strategy and following other proponents of Sensorimotor Enactivism, I argue that by referring to the interactions of the embodied agent a better account of the phenomena in question is provided. On this basis, I claim that Sensorimotor Enactivism and the Free-Energy approach are compatible in what concerns their explanatory strategy as well. Thus, making the case for the viability of the predictive approach to Sensorimotor Enactivism. (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)

We seem to learn and use concepts in a variety of heterogenous “formats”, including exemplars, prototypes, and theories. Different strategies have been proposed to account for this diversity. Hybridists consider instances in different formats to be instances of a single concept. Pluralists think that each instance in a different format is a different concept. Eliminativists deny that the different instances in different formats pertain to a scientifically fruitful kind and recommend eliminating the notion of a “concept” entirely. In recent years, (...) hybridism has received the most attention and support. However, we are still lacking a cognitive-computational model for concept representation and processing that would underpin hybridism. The aim of this paper is to advance the understanding of concepts by grounding hybridism in a neuroscientific model within the Predictive Processing framework. In the suggested view, the different formats are not distinct parts of a concept but arise from different ways of processing a functionally unified representational structure. (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.

Although pragmatism and phenomenology have both contributed significantly to the genealogy of so-called “4E” – embodied, embedded, enactive and extended – cognition, there is benefit to be had from a systematic comparative study of these roots. As existing 4E cognition literature has tended to emphasise one or the other tradition, issues remain to be addressed concerning their commonalities – and possible incompatibilities. We begin by exploring pragmatism and phenomenology’s shared focus on contesting intellectualism, and its key assumption of mindedness as (...) representation. We then outline distinctive insights from both traditions regarding the nature and role of habits, in order to put forward a habit-based epistemology as an alternative to the Cartesian idea-based epistemology that has dominated modern philosophy. We pay particular attention to the work of classical pragmatist C.S. Peirce, arguing that his semiotics, which analyses sign-use as habit, shows how theorists of embodied cognition can break a certain false dichotomy between embodiment and logical or intellectual structure which has prevented them from fully theorising propositional knowledge. In this way, our work both augments and challenges the Dewey/Merleau-Ponty connection that has been much more extensively explored by the field. (shrink)

In this paper, I develop an account of linguistic content based on the active inference framework. While ecological and enactive theorists have rightly rejected the notion of content as a basis for cognitive processes, they must recognize the important role that it plays in the social regulation of linguistic interaction. According to an influential theory in philosophy of language, normative inferentialism, an utterance has the content that it has in virtue of its normative status, that is, in virtue of the (...) set of commitments and entitlements that the speaker undertakes by producing this utterance. This normative status is determined by the normative attitudes shared by members of the utterer’s linguistic community. I propose here an account of such normative attitudes based on the ecological interpretation of the active inference framework. I explain how social normativity can be understood in that framework as the way in which members of a group shape their social niche to make it more predictable. Finally, I apply this account of social normativity to basic communicative practices, thereby explaining how social normative expectations can emerge to regulate these communicative practices, eventually leading to the institution of the sort of normative statuses constitutive of linguistic content. (shrink)

In this paper, I develop an empirically-driven approach to the relationship between conceptual and non-conceptual representations. I begin by clarifying Wilfrid Sellars's distinction between a non-conceptual capacity to picture significant aspects of our world, and a capacity to stabilize semantic content in the form of conceptual representations that signify those aspects of the world that are relevant to our shared practices. I argue that this distinction helps to clarify the reason why cognition must be understood as embodied and situated. Drawing (...) on recent models of attention and valuation, I then argue that the human brain constructs a dynamic model of the world that it has encountered, encoding higher-level regularities in the form of linguistically structured representations. And I conclude by arguing that this approach to cognition provides a set of critical resources for understanding the situated nature of social cognition. (shrink)

Two striking claims are advanced on behalf of the free energy principle in cognitive science and philosophy: that it identifies a condition of the possibility of existence for self-organising systems; and that it has important implications for our understanding of how the brain works, defining a set of process theories—roughly, theories of the structure and functions of neural mechanisms—consistent with the free energy minimising imperative that it derives as a necessary feature of all self-organising systems. I argue that the conjunction (...) of claims and rests on a fallacy of equivocation. The FEP can be interpreted in two ways: as a claim about how it is possible to redescribe the existence of self-organising systems, and as a claim about how such systems maintain their existence. Although the Descriptive FEP plausibly does identify a condition of the possibility of existence for self-organising systems, it has no important implications for our understanding of how the brain works. Although the Explanatory FEP would have such implications if it were true, it does not identify a condition of the possibility of existence for self-organising systems. I consider various ways of responding to this conclusion, and I explore its implications for the role and importance of the FEP in cognitive science and philosophy. (shrink)

Radical views on cognition are generally defined by a cluster of features including non-representationalism and vehicle-externalism. In this paper, I concentrate on the way radical views on cognition define themselves as revolutionary theories in cognitive science. These theories often use the Kuhnian concepts of “paradigm” and “paradigm shift” for describing their ambitions and the current situation in cognitive science. I examine whether the use of Kuhn’s theory of science is appropriate here. There might be good reasons to think that cognitive (...) science is in a situation of foundational crisis, but that does not entail that the classical paradigm is currently displaced to the benefit of a new paradigm. Larry Laudan’s theory of research traditions is more enlightening than Kuhn’s theory for describing the scope and ambitions of radical views on cognition, and their relations with an anti-intellectualist tradition in philosophy. (shrink)

James (1890) distinguished two understandings of the self, the self as “Me” and the self as “I”. This distinction has recently regained popularity in cognitive science, especially in the context of experimental studies on the underpinnings of the phenomenal self. The goal of this paper is to take a step back from cognitive science and attempt to precisely distinguish between “Me” and “I” in the context of consciousness. This distinction was originally based on the idea that the former (“Me”) corresponds (...) to the self as an object of experience (self as object), while the latter (“I”) reflects the self as a subject of experience (self as subject). I will argue that in most of the cases (arguably all) this distinction maps onto the distinction between the phenomenal self (reflecting self-related content of consciousness) and the metaphysical self (representing the problem of subjectivity of all conscious experience), and as such these two issues should be investigated separately using fundamentally different methodologies. Moreover, by referring to Metzinger’s (2018) theory of phenomenal self-models, I will argue that what is usually investigated as the phenomenal-“I” [following understanding of self-as-subject introduced by Wittgenstein (1958) ] can be interpreted as object, rather than subject of experience, and as such can be understood as an element of the hierarchical structure of the phenomenal self-model. This understanding relates to recent predictive coding and free energy theories of the self and bodily self discussed in cognitive neuroscience and philosophy. (shrink)

The free energy principle, an influential framework in computational neuroscience and theoretical neurobiology, starts from the assumption that living systems ensure adaptive exchanges with their environment by minimizing the objective function of variational free energy. Following this premise, it claims to deliver a promising integration of the life sciences. In recent work, Markov blankets, one of the central constructs of the free energy principle, have been applied to resolve debates central to philosophy (such as demarcating the boundaries of the mind). (...) The aim of this paper is twofold. First, we trace the development of Markov blankets starting from their standard application in Bayesian networks, via variational inference, to their use in the literature on active inference. We then identify a persistent confusion in the literature between the formal use of Markov blankets as an epistemic tool for Bayesian inference, and their novel metaphysical use in the free energy framework to demarcate the physical boundary between an agent and its environment. Consequently, we propose to distinguish between “Pearl blankets” to refer to the original epistemic use of Markov blankets and “Friston blankets” to refer to the new metaphysical construct. Second, we use this distinction to critically assess claims resting on the application of Markov blankets to philosophical problems. We suggest that this literature would do well in differentiating between two different research programmes: “inference with a model” and “inference within a model.” Only the latter is capable of doing metaphysical work with Markov blankets, but requires additional philosophical premises and cannot be justified by an appeal to the success of the mathematical framework alone. (shrink)

I identify three lessons from Kenneth Craik’s landmark book “The Nature of Explanation” for contemporary debates surrounding the existence, extent, and nature of mental representation: first, an account of mental representations as neural structures that function analogously to public models; second, an appreciation of prediction as the central component of intelligence in demand of such models; and third, a metaphor for understanding the brain as an engineer, not a scientist. I then relate these insights to discussions surrounding the representational status (...) of predictive processing – which, I argue, provides a contemporary vindication of Craik’s extremely prescient “hypothesis on the nature of thought.”. (shrink)

In ‘Computing Machinery and Intelligence’, Turing, sceptical of the question ‘Can machines think?’, quickly replaces it with an experimentally verifiable test: the imitation game. I suggest that for such a move to be successful the test needs to be relevant, expansive, solvable by exemplars, unpredictable, and lead to actionable research. The Imitation Game is only partially successful in this regard and its reliance on language, whilst insightful for partially solving the problem, has put AI progress on the wrong foot, prescribing (...) a top-down approach for building thinking machines. I argue that to fix shortcomings with modern AI systems a nonverbal operationalisation is required. This is provided by the recent Animal-AI Testbed, which translates animal cognition tests for AI and provides a bottom-up research pathway for building thinking machines that create predictive models of their environment from sensory input. (shrink)

Predictive processing is an increasingly popular approach to cognition, perception and action. It says that the brain is essentially a hierarchical prediction machine. It is typically construed in a representationalist and inferentialist fashion so that the brain makes contentful inferences on the basis of representational models. In this paper, I argue that the predictive processing framework is inconsistent with this epistemic position. In particular, I argue that the combination of hierarchical modeling, contentful inferentialism and representationalism entail an internal inconsistency. Specifically, (...) for a particular set of states, there will be both a representation requirement and not. Yet a system cannot both be required to represent a certain set of states and not be required to represent those states. Due to this contradiction, I propose to reject the standard view. I suggest that predictive processing is best interpreted in terms of reliable covariation instead, entailing an instrumentalist approach to the statistical machinery. (shrink)

Much of contemporary philosophy assumes a close connection between thought and language. It is widely assumed, for example, that the structural units, semantic properties, and forms of reasoning as...