In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology (...) of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system “brain-body-landscape of affordances.” Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients. (shrink)

We review some of the main implications of the free-energy principle (FEP) for the study of the self-organization of living systems – and how the FEP can help us to understand (and model) biotic self-organization across the many temporal and spatial scales over which life exists. In order to maintain its integrity as a bounded system, any biological system - from single cells to complex organisms and societies - has to limit the disorder or dispersion (i.e., the long-run (...) entropy) of its constituent states. We review how this can be achieved by living systems that minimize their variational free energy. Variational free energy is an information theoretic construct, originally introduced into theoretical neuroscience and biology to explain perception, action, and learning. It has since been extended to explain the evolution, development, form, and function of entire organisms, providing a principled model of biotic self-organization and autopoiesis. It has provided insights into biological systems across spatiotemporal scales, ranging from microscales (e.g., sub- and multicellular dynamics), to intermediate scales (e.g., groups of interacting animals and culture), through to macroscale phenomena (the evolution of entire species). A crucial corollary of the FEP is that an organism just is (i.e., embodies or entails) an implicit model of its environment. As such, organisms come to embody causal relationships of their ecological niche, which, in turn, is influenced by their resulting behaviors. Crucially, free-energy minimization can be shown to be equivalent to the maximization of Bayesian model evidence. This allows us to cast natural selection in terms of Bayesian model selection, providing a robust theoretical account of how organisms come to match or accommodate the spatiotemporal complexity of their surrounding niche. In line with the theme of this volume; namely, biological complexity and self-organization, this chapter will examine a variational approach to self-organization across multiple dynamical scales. (shrink)

What can we hope to learn about brains from the free energy principle? In adopting the “primordial soup” physical model, Bruineberg et al. perpetuate the unsupported notion that the free-energy principle has a meaningful physical – and neuronal – interpretation. We examine how minimization of free energy arises in physical contexts, and what this can and cannot tell us about brains.

This paper examines, for the first time, the relationship between realization relations and the free energy principle in cognitive neuroscience. I argue, firstly, that the free energy principle has ramifications for the wide versus narrow realization distinction: if the free energy principle is correct, then organismic realizers are insufficient for realizing free energy minimization. I argue, secondly, that the free energy principle has implications for synchronic realization relations, because (...) class='Hi'>free energy minimization is realized in dynamical agent-environment couplings embedded at multiple time scales. (shrink)

The prediction of protein–protein interactions based on independently obtained structural information for each interacting partner remains an important challenge in computational chemistry. Procedures where hypothetical interaction models (or decoys) are generated, then ranked using a biochemically relevant scoring function have been garnering interest as an avenue for addressing such challenges. The program PatchDock has been shown to produce reasonable decoys for modeling the association between pig alpha-amylase and the VH-domains of camelide antibody raised against it. We designed a biochemically relevant (...) method by which PatchDock decoys could be ranked in order to separate near-native structures from false positives. Several thousand steps of energy minimization were used to simulate induced fit within the otherwise rigid decoys and to rank them. We applied a partial free energy function to rank each of the binding modes, improving discrimination between near-native structures and false positives. Sorting decoys according to strain energy increased the proportion of near-native decoys near the bottom of the ranked list. Additionally, we propose a novel method which utilizes regression analysis for the selection of minimization convergence criteria and provides approximation of the partial free energy function as the number of algorithmic steps approaches infinity. (shrink)

Plant predictive processing suggests that plants anticipatorily perceive their environment. This hypothesis runs up against a challenge which takes the form of two constraints on per- ception advanced by Tyler Burge: the veridicality constraint and the constancy constraint. This paper argues that the veridicality constraint can be satisfied by assuming a general account of predictive processing. To show how the constancy constraint may be fulfilled, an ecologically informed account of invariant pick-up is developed and given a place within plant predictive (...) processing. It is concluded that, against our anthro- pocentric folk-psychological notions of perception, there is reason to believe that plants engage in minimal perception. (shrink)

This chapter focuses on what’s novel in the perspective that the prediction error minimization (PEM) framework affords on the cognitive-scientific project of explaining intelligence by appeal to internal representations. It shows how truth-conditional and resemblance-based approaches to representation in generative models may be integrated. The PEM framework in cognitive science is an approach to cognition and perception centered on a simple idea: organisms represent the world by constantly predicting their own internal states. PEM theories often stress the hierarchical structure (...) of the generative models they posit. The novel explanatory power of the PEM account derives largely from the way in which pairs of generative and recognition models interact. “Predictive coding” refers to an encoding strategy in which predicted portions of an input signal are subtracted from the actual signal received, so that only the difference between the two is passed as output to the next stage of information processing. (shrink)

In a recent paper, Jakob Hohwy argues that the emerging predictive processing perspective on cognition requires us to explain cognitive functioning in purely internalistic and neurocentric terms. The purpose of the present paper is to challenge the view that PP entails a wholesale rejection of positions that are interested in the embodied, embedded, extended, or enactive dimensions of cognitive processes. I will argue that Hohwy’s argument from analogy, which forces an evidentiary boundary into the picture, lacks the argumentative resources to (...) make a convincing case for the conceptual necessity to interpret PP in solely internalistic terms. For this reason, I will reconsider the postulation and explanatory role of the evidentiary boundary. I will arrive at an account of prediction error minimization and its foundation on the free energy principle that is fully consistent with approaches to cognition that emphasize the embodied and interactive properties of cognitive processes. This gives rise to the suggestion that explanatory pluralism about the application of PP is to be preferred over Hohwy’s explanatory monism that follows from his internalistic and neurocentric view of predictive cognitive systems. (shrink)

The goal of the paper is to review existing work on consciousness within the frameworks of Predictive Processing, Active Inference, and Free Energy Principle. The emphasis is put on the role played by the precision and complexity of the internal generative model. In the light of those proposals, these two properties appear to be the minimal necessary components for the emergence of conscious experience—a Minimal Unifying Model of consciousness.

If one formulates Helmholtz's ideas about perception in terms of modern-day theories one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring what cause our sensory inputs and learning causal regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on (...) Empirical Bayes and hierarchical models of how sensory information is generated. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of the brain's organisation and responses. In this paper, we suggest that these perceptual processes are just one emergent property of systems that conform to a free-energy principle. The free-energy considered here represents a bound on the surprise inherent in any exchange with the environment, under expectations encoded by its state or configuration. A system can minimise free-energy by changing its configuration to change the way it samples the environment, or to change its expectations. These changes correspond to action and perception, respectively, and lead to an adaptive exchange with the environment that is characteristic of biological systems. This treatment implies that the system's state and structure encode an implicit and probabilistic model of the environment. We will look at models entailed by the brain and how minimisation of free-energy can explain its dynamics and structure. (shrink)

Philosophical writings on the free energy principle in the life sciences often give the impression that minimising free energy is sufficient for life. But minimising free energy is not a sufficient condition for life. In fact, one can perfectly well conceive of a system that actively minimises its free energy, and for this very reason moves inexorably towards death. So, where does the assumption of this entailment relation come from? There is indeed (...) an entailment relation, but it goes the other way around: life entails minimising free energy. Put another way, if you exist, now, under the right conditions, it is because you’ve done something like minimising your free energy. However, the question of whether you will exist tomorrow cannot be settled purely by resorting to the fact that you will minimise your free energy to get there. The simple point I make in this paper is that the free energy principle is not concerned with the sufficient conditions of existence, but rather with what must have been the case, given that you exist. It’s not about figuring out what it takes to be alive; it’s about figuring out what took you there. (shrink)

The life–mind continuity thesis is difficult to study, especially because the relation between life and mind is not yet fully understood, and given that there is still no consensus view neither on what qualifies as life nor on what defines mind. Rather than taking up the much more difficult task of addressing the many different ways of explaining how life relates to mind, and vice versa, this paper considers two influential accounts addressing how best to understand the life–mind continuity thesis: (...) first, the theory of autopoiesis (AT) developed in biology and in enactivist theories of mind; and second, the recently formulated free energy principle in theoretical neurobiology, with roots in thermodynamics and statistical physics. This paper advances two claims. The first is that the free energy principle (FEP) should be preferred to the theory of AT, as classically formulated. The second is that the FEP and the recently formulated framework of autopoietic enactivism can be shown to be genuinely continuous on a number of central issues, thus raising the possibility of a joint venture when it comes to answering the life–mind continuity thesis. (shrink)

Over the last fifteen years, an ambitious explanatory framework has been proposed to unify explanations across biology and cognitive science. Active inference, whose most famous tenet is the free energy principle, has inspired excitement and confusion in equal measure. Here, we lay the ground for proper critical analysis of active inference, in three ways. First, we give simplified versions of its core mathematical models. Second, we outline the historical development of active inference and its relationship to other theoretical (...) approaches. Third, we describe three different kinds of claim -- labelled mathematical, empirical and general -- routinely made by proponents of the framework, and suggest dialectical links between them. Overall, we aim to increase philosophical understanding of active inference so that it may be more readily evaluated. -/- This the final submitted version of the Introduction to the Topical Collection "The Free Energy Principle: From Biology to Cognition", forthcoming in Biology & Philosophy. (shrink)

Both a method of therapy and an exploration of psychic reality, free association is a fundamental element of psychoanalytical practices that refers to the way a patient is asked to describe what comes spontaneously to mind in the therapeutic setting. This paper examines the role of free association from the point of view of psychoanalysis and neuroscience in order to improve our understanding of therapeutic effects induced by psychoanalytic therapies and psychoanalysis. In this regard, we first propose a (...) global overview of the historical origins of the concept of free association in psychoanalysis and examine how Freud established its principles. Then, from Freud’s distinction between primary and secondary processes, we proceed to compare the psychoanalytic model with research originating from cognitive psychology and neuroscience. The notions of entropy and free energy appear particularly relevant at the intersection of these different domains. Finally, we propose the notion of symbolizing transmodality to describe certain specificities of symbolization processes within free association and we summarize the main functions of free association in psychoanalytic practices. (shrink)

If one formulates Helmholtz’s ideas about perception in terms of modern-day theories one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring what cause our sensory inputs and learning causal regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on (...) Empirical Bayes and hierarchical models of how sensory information is generated. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of the brain’s organisation and responses. In this paper, we suggest that these perceptual processes are just one emergent property of systems that conform to a free-energy principle. The free-energy considered here represents a bound on the surprise inherent in any exchange with the environment, under expectations encoded by its state or configuration. A system can minimise free-energy by changing its configuration to change the way it samples the environment, or to change its expectations. These changes correspond to action and perception, respectively, and lead to an adaptive exchange with the environment that is characteristic of biological systems. This treatment implies that the system’s state and structure encode an implicit and probabilistic model of the environment. We will look at models entailed by the brain and how minimisation of free-energy can explain its dynamics and structure. (shrink)

The paper draws on scientific resources formed around the notion of Free Energy Principle to reconstruct two well-known defences of panpsychism. I reconstruct the argument from continuity by expanding the mind-life continuity thesis under the rubric of the Free Energy Principle (FEP), by showing that FEP does not provide an objective criterion for demarcating the living from the inanimate. Then I will reconstruct the argument from intrinsic nature. The FEP-based account of consciousness is centred on the (...) notion of ‘temporal depth’ of generative models. I argue that even evolution can be modelled as a temporally deep system. Since we have no access to the intrinsic perspective of evolution to see whether or not it models itself as a temporally deep system, we must draw an analogy from our own case and conclude that evolution is consciousness involving. Thus the paper reconstructs two main arguments for panpsychism. (shrink)

According to the free energy principle all living systems aim to minimise free energy in their sensory exchanges with the environment. Processes of free energy minimisation are thus ubiquitous in the biological world. Indeed it has been argued that even plants engage in free energy minimisation. Not all living things however feel alive. How then did the feeling of being alive get started? In line with the arguments of the phenomenologists, I will (...) claim that every feeling must be felt by someone. It must have mineness built into it if it is to feel a particular way. The question I take up in this paper asks how mineness might have arisen out of processes of free energy minimisation, given that many systems that keep themselves alive lack mineness. The hypothesis I develop in this paper is that the life of an organism can be seen as an inferential process. Every living system embodies a probability distribution conditioned on a model of the sensory, physiological, and morphological states that are highly probably given the life it leads and the niche it inhabits. I argue for an ecological and enactive interpretation of free energy. I show how once the life of an organism reaches a certain level of complexity mineness emerges as an intrinsic part of the process of life itself. (shrink)

A mark of the cognitive should allow us to specify theoretical principles for demarcating cognitive from non-cognitive causes of behaviour in organisms. Specific criteria are required to settle the question of when in the evolution of life cognition first emerged. An answer to this question should however avoid two pitfalls. It should avoid overintellectualising the minds of other organisms, ascribing to them cognitive capacities for which they have no need given the lives they lead within the niches they inhabit. But (...) equally it should do justice to the remarkable flexibility and adaptiveness that can be observed in the behaviour of microorganisms that do not have a nervous system. We should resist seeking non-cognitive explanations of behaviour simply because an organism fails to exhibit human-like feats of thinking, reasoning and problem-solving. We will show how Karl Friston’s Free-Energy Principle (FEP) can serve as the basis for a mark of the cognitive that avoids the twin pitfalls of overintellectualising or underestimating the cognitive achievements of evolutionarily primitive organisms. The FEP purports to describe principles of organisation that any organism must instantiate if it is to remain well-adapted to its environment. Living systems from plants and microorganisms all the way up to humans act in ways that tend in the long run to minimise free energy. If the FEP provides a mark of the cognitive, as we will argue it does, it mandates that cognition should indeed be ascribed to plants, microorganisms and other organisms that lack a nervous system. (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s levels of explanation cannot explain (...) such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

This paper compares the free energy neuroscience now advocated by Karl Friston and his colleagues with that hypothesised by Freud, arguing that Freud's notions of conflict and trauma can be understood in terms of computational complexity. It relates Hobson and Friston's work on dreaming and the reduction of complexity to contemporary accounts of dreaming and the consolidation of memory, and advances the hypothesis that mental disorder can be understood in terms of computational complexity and the mechanisms, including synaptic (...) pruning, that have evolved to reduce it. (shrink)

The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, (...) its epistemic status is unclear. Also unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences. (shrink)

Disagreement about how best to think of the relation between theories and the realities they represent has a longstanding and venerable history. We take up this debate in relation to the free energy principle (FEP) - a contemporary framework in computational neuroscience, theoretical biology and the philosophy of cognitive science. The FEP is very ambitious, extending from the brain sciences to the biology of self-organisation. In this context, some find apparent discrepancies between the map (the FEP) and the (...) territory (target systems) a compelling reason to defend instrumentalism about the FEP. We take this to be misguided. We identify an important fallacy made by those defending instrumentalism about the FEP. We call it the literalist fallacy: this is the fallacy of inferring the truth of instrumentalism based on the claim that the properties of FEP models do not literally map onto real-world, target systems. We conclude that scientific realism about the FEP is a live and tenable option. (shrink)

The aim of this paper is twofold: (1) to assess whether the construct of neural representations plays an explanatory role under the variational free-energy principle and its corollary process theory, active inference; and (2) if so, to assess which philosophical stance - in relation to the ontological and epistemological status of representations - is most appropriate. We focus on non-realist (deflationary and fictionalist-instrumentalist) approaches. We consider a deflationary account of mental representation, according to which the explanatorily relevant contents (...) of neural representations are mathematical, rather than cognitive, and a fictionalist or instrumentalist account, according to which representations are scientifically useful fictions that serve explanatory (and other) aims. After reviewing the free-energy principle and active inference, we argue that the model of adaptive phenotypes under the free-energy principle can be used to furnish a formal semantics, enabling us to assign semantic content to specific phenotypic states (the internal states of a Markovian system that exists far from equilibrium). We propose a modified fictionalist account: an organism-centered fictionalism or instrumentalism. We argue that, under the free-energy principle, pursuing even a deflationary account of the content of neural representations licenses the appeal to the kind of semantic content involved in the aboutness or intentionality of cognitive systems; our position is thus coherent with, but rests on distinct assumptions from, the realist position. We argue that the free-energy principle thereby explains the aboutness or intentionality in living systems and hence their capacity to parse their sensory stream using an ontology or set of semantic factors. (shrink)

We question the free energy principle (FEP) as it is used in contemporary physics. If the FEP is incorrect in physics, then it cannot ground the authors' arguments. We also question the assumption that perception requires inference. We argue that perception (including perception of social affordances) can be direct, in which case inference is not required.

The free energy principle is notoriously difficult to understand. In this paper, we relate the principle to a framework that philosophers of biology are familiar with: Ruth Millikan’s teleosemantics. We argue that: systems that minimise free energy are systems with a proper function; and Karl Friston’s notion of implicit modelling can be understood in terms of Millikan’s notion of mapping relations. Our analysis reveals some surprising formal similarities between the two frameworks, and suggests interesting lines of (...) future research. We hope this will aid further philosophical evaluation of the free energy principle. (shrink)

The paper proposes a way to naturalise Charles S. Peirce’s conception of the scientific method, which he specified in terms of abduction, deduction and induction. The focus is on the central issue of the economy of research in abduction and self-correction by error reduction in induction. We show how Peirce’s logic of science receives support from modern breakthroughs in computational neuroscience, and more specifically from Karl Friston’s statements of active inference and the Free Energy Principle, namely the account (...) of how organisms’ capacity to decrease the discrepancy between the expected value and actual outcomes entails the minimisation of errors in their hypotheses about the world. A scientific account of organisms’ capacity to choose policies and form expectations is aligned with Peirce’s theories of abduction and induction, and especially with the economy of research. The upshot is the recovery of Peirce’s theory of the logic of science in the context of active inquiry. (shrink)

We target the ontological and epistemological ramifications of the proposed distinction between Friston and Pearl blankets. We emphasize the need for empirical testing next to computational modeling. A peculiar aspect of the free energy principle (FEP) is its purported support of radically opposed ontologies of the mind. In our view, the objective ontological aspiration itself should be rejected for a pragmatic instrumentalist view.

An exciting theory in neuroscience is that the brain is an organ for prediction error minimization. This theory is rapidly gaining influence and is set to dominate the science of mind and brain in the years to come. PEM has extreme explanatory ambition, and profound philosophical implications. Here, I assume the theory, briefly explain it, and then I argue that PEM implies that the brain is essentially self-evidencing. This means it is imperative to identify an evidentiary boundary between the (...) brain and its environment. This boundary defines the mind-world relation, opens the door to skepticism, and makes the mind transpire as more inferentially secluded and neurocentrically skull-bound than many would nowadays think. Therefore, PEM somewhat deflates contemporary hypotheses that cognition is extended, embodied and enactive; however, it can nevertheless accommodate the kinds of cases that fuel these hypotheses. (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)

There are realist and antirealist interpretations of the free energy principle (FEP). This paper aims to chart out a structural realist interpretation of FEP. To do so, it draws on Worrall’s (Dialectica 43(1–2): 99–124, 1989) proposal. The general insight of Worrall’s paper is that there is progress at the level of the structure of theories rather than their content. To enact Worrall’s strategy in the context of FEP, this paper will focus on characterising the formal continuity between fundamental (...) equations of thermodynamics—such as Boltzmann’s equation and Gibbs’s equation—on the one hand, and Friston’s characterisation of FEP on the other. Lack of a universal consensus on the physical character of entities that feature in thermodynamics, information theory and FEP notwithstanding, I argue that there is structural continuity and unity at the level of mathematical equations that regiment entropy, information and free energy. The existence of such structural continuity and unity provides grounds for structural realism about FEP. (shrink)

In this paper I propose a model of the fundamental components of psychoanalytic psychotherapies that I try to explicate with contemporary theories of the Bayesian brain and the Free Energy Principle (FEP). I first show that psychoanalytic therapies require a setting (made up of several envelopes), a particular psychic state and specific processes (transference, free association, dreaming, play, reflexivity and narrativity) in order to induce psychic transformations. I then analyze how these processes of transformations operate and how (...) they can be enlightened by the FEP. I first underline the fact that psychoanalytic therapies imply non-linear processes taking time to unfold and require a setting containing high entropy processes. More precisely, these processes are characterized by an interplay between extension and reduction of free energy. This interplay also favors the emergence of new orders of subjective experience, which occur following states of disorder, according to a certain energetic threshold allowing the modification and improvement of mental functioning. These high entropy states are also characterized by random functioning and psychic malleability which favors the exploration of subjective experience in an original manner. Overall, the approach proposed in this paper support the dialogue between psychoanalysis and other fields of research while underlining how psychoanalytical theoretical and conceptual constructs can also be useful to other disciplines, in particular the neurosciences of subjectivity. (shrink)

In this paper, I argue that enactivism and computationalism—two seemingly incompatible research traditions in modern cognitive science—can be fruitfully reconciled under the framework of the free energy principle. FEP holds that cognitive systems encode generative models of their niches and cognition can be understood in terms of minimizing the free energy of these models. There are two philosophical interpretations of this picture. A computationalist will argue that as FEP claims that Bayesian inference underpins both perception and (...) action, it entails a concept of cognition as a computational process. An enactivist, on the other hand, will point out that FEP explains cognitive systems as constantly self-organizing to non-equilibrium steady-state. My claim is that these two interpretations are both true at the same time and that they enlighten each other. (shrink)

This work addresses the autonomous organization of biological systems. It does so by considering the boundaries of biological systems, from individual cells to Home sapiens, in terms of the presence of Markov blankets under the active inference scheme—a corollary of the free energy principle. A Markov blanket defines the boundaries of a system in a statistical sense. Here we consider how a collective of Markov blankets can self-assemble into a global system that itself has a Markov blanket; thereby (...) providing an illustration of how autonomous systems can be understood as having layers of nested and self-sustaining boundaries. This allows us to show that: (i) any living system is a Markov blanketed system and (ii) the boundaries of such systems need not be co-extensive with the biophysical boundaries of a living organism. In other words, autonomous systems are hierarchically composed of Markov blankets of Markov blankets—all the way down to individual cells, all the way up to you and me, and all the way out to include elements of the local environment. (shrink)

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

An approach to implementing variational Bayesian inference in biological systems is considered, under which the thermodynamic free energy of a system directly encodes its variational free energy. In the case of the brain, this assumption places constraints on the neuronal encoding of generative and recognition densities, in particular requiring a stochastic population code. The resulting relationship between thermodynamic and variational free energies is prefigured in mind–brain identity theses in philosophy and in the Gestalt hypothesis of (...) psychophysical isomorphism. (shrink)

Much has been written about the free energy principle (FEP), and much misunderstood. The principle has traditionally been put forth as a theory of brain function or biological self-organisation. Critiques of the framework have focused on its lack of empirical support and a failure to generate concrete, falsifiable predictions. I take both positive and negative evaluations of the FEP thus far to have been largely in error, and appeal to a robust literature on scientific modelling to rectify the (...) situation. A prominent account of scientific modelling distinguishes between model structure and model construal. I propose that the FEP be reserved to designate a model structure, to which philosophers and scientists add various construals, leading to a plethora of models based on the formal structure of the FEP. An entailment of this position is that demands placed on the FEP that it be falsifiable or that it conform to some degree of biological realism rest on a category error. To this end, I deliver first an account of the phenomenon of model transfer and the breakdown between model structure and model construal. In the second section, I offer an overview of the formal elements of the framework, tracing their history of model transfer and illustrating how the formalism comes apart from any interpretation thereof. Next, I evaluate existing comprehensive critical assessments of the FEP, and hypothesise as to potential sources of existing confusions in the literature. In the final section, I distinguish between what I hold to be the FEP—taken to be a modelling language or modelling framework—and what I term “FEP models.”. (shrink)

Courtesy of its free energy formulation, the hierarchical predictive processing theory of the brain (PTB) is often claimed to be a grand unifying theory. To test this claim, we examine a central case: activity of mesocorticolimbic dopaminergic (DA) systems. After reviewing the three most prominent hypotheses of DA activity—the anhedonia, incentive salience, and reward prediction error hypotheses—we conclude that the evidence currently vindicates explanatory pluralism. This vindication implies that the grand unifying claims of advocates of PTB are unwarranted. (...) More generally, we suggest that the form of scientific progress in the cognitive sciences is unlikely to be a single overarching grand unifying theory. (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.