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  • Functional architectures in the brain.

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    Authors: Badcock, Paul B.; Friston, Karl J.; Ramstead, Maxwell J.D.;

    This article presents a unifying theory of the embodied, situated human brain called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that actively minimises the decay of our sensory and physical states by producing self-fulfilling action-perception cycles via dynamical interactions between hierarchically organised neurocognitive mechanisms. This theory synthesises the free-energy principle (FEP) in neuroscience with an evolutionary systems theory of psychology that explains our brains, minds, and behaviour by appealing to Tinbergen's four questions: adaptation, phylogeny, ontogeny, and mechanism. After leveraging the FEP to formally define the HMM across different spatiotemporal scales, we conclude by exploring its implications for theorising and research in the sciences of the mind and behaviour. Highlights • We present an interdisciplinary theory of the embodied, situated human brain called the Hierarchically Mechanistic Mind (HMM). • We describe the HMM as a model of neural architecture. • We explore how the HMM synthesises the free-energy principle in neuroscience with an evolutionary systems theory of psychology. • We translate our model into a new heuristic for theorising and research in neuroscience and psychology.

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    Europe PubMed Central
    Article . 2019
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      Europe PubMed Central
      Article . 2019
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    Authors: Thomas Parr; Lancelot Da Costa; Conor Heins; Maxwell J. D. Ramstead; +1 Authors

    In theoretical biology, we are often interested in random dynamical systems—like the brain—that appear to model their environments. This can be formalized by appealing to the existence of a (possibly non-equilibrium) steady state, whose density preserves a conditional independence between a biological entity and its surroundings. From this perspective, the conditioning set, or Markov blanket, induces a form of vicarious synchrony between creature and world—as if one were modelling the other. However, this results in an apparent paradox. If all conditional dependencies between a system and its surroundings depend upon the blanket, how do we account for the mnemonic capacity of living systems? It might appear that any shared dependence upon past blanket states violates the independence condition, as the variables on either side of the blanket now share information not available from the current blanket state. This paper aims to resolve this paradox, and to demonstrate that conditional independence does not preclude memory. Our argument rests upon drawing a distinction between the dependencies implied by a steady state density, and the density dynamics of the system conditioned upon its configuration at a previous time. The interesting question then becomes: What determines the length of time required for a stochastic system to ‘forget’ its initial conditions? We explore this question for an example system, whose steady state density possesses a Markov blanket, through simple numerical analyses. We conclude with a discussion of the relevance for memory in cognitive systems like us.

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      Other literature type . Article . 2021
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    Authors: Maxwell J. D. Ramstead; Karl J. Friston; Inês Hipólito;

    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&mdash 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. 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 &lsquo 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 in relation to the ontological and epistemological status of representations&mdash and (2) if so, to assess which philosophical stance&mdash or intentionality of cognitive systems aboutness&rsquo

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    https://doi.org/10.48550/arxiv...
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    Authors: Ramstead, Maxwell James Désormeau; Badcock, Paul Benjamin; Friston, Karl John;

    The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery. Highlights • We describe a meta-theoretical ontology of life based on the free energy principle. • We propose a multiscale formulation of the free energy principle. • We translate our ontology into a systematic research heuristic for life sciences. • We apply this meta-theoretical ontology and research heuristic to Homo sapiens.

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    Physics of Life Reviews
    Article . 2018
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    Authors: Badcock, Paul B.; Friston, Karl J.; Ramstead, Maxwell J. D.; Ploeger, Annemie; +1 Authors

    The purpose of this review was to integrate leading paradigms in psychology and neuroscience with a theory of the embodied, situated human brain, called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that functions to minimize the entropy of our sensory and physical states via action-perception cycles generated by hierarchical neural dynamics. First, we review the extant literature on the hierarchical structure of the brain. Next, we derive the HMM from a broader evolutionary systems theory that explains neural structure and function in terms of dynamic interactions across four nested levels of biological causation (i.e., adaptation, phylogeny, ontogeny, and mechanism). We then describe how the HMM aligns with a global brain theory in neuroscience called the free-energy principle, leveraging this theory to mathematically formulate neural dynamics across hierarchical spatiotemporal scales. We conclude by exploring the implications of the HMM for psychological inquiry.

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    Authors: Thomas Parr; Dimitrije Marković; Maxwell James D. Ramstead; Maxwell James D. Ramstead; +6 Authors
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    Frontiers in Artificial Intelligence
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      Frontiers in Artificial Intelligence
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      Article . 2021
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    Authors: Maxwell J D, Ramstead; Axel, Constant; Paul B, Badcock; Karl J, Friston;

    This paper addresses the challenges faced by multiscale formulations of the variational (free energy) approach to dynamics that obtain for large-scale ensembles. We review a framework for modelling complex adaptive control systems for multiscale free energy bounding organism–niche dynamics, thereby integrating the modelling strategies and heuristics of variational neuroethology with a broader perspective on the ecological nestedness of biotic systems. We extend the multiscale variational formulation beyond the action–perception loops of individual organisms by appealing to the variational approach to niche construction to explain the dynamics of coupled systems constituted by organisms and their ecological niche. We suggest that the statistical robustness of living systems is inherited, in part, from their eco-niches, as niches help coordinate dynamical patterns across larger spatiotemporal scales. We call this approach variational ecology. We argue that, when applied to cultural animals such as humans, variational ecology enables us to formulate not just a physics of individual minds, but also a physics of interacting minds across spatial and temporal scales – a physics of sentient systems that range from cells to societies. Highlights • We extend the multiscale variational free energy approach to large-scale ensembles. • We integrate multiscale modelling with a broad perspective on ecological nestedness. • We argue that the statistical robustness of living systems is ecologically inherited. • We propose variational ecology as a physics of sentient systems.

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    Europe PubMed Central
    Article . 2019
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      Europe PubMed Central
      Article . 2019
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    Authors: Axel, Constant; Maxwell J D, Ramstead; Samuel P L, Veissière; Karl, Friston;

    How do humans come to acquire shared expectations about how they ought to behave in distinct normalized social settings? This paper offers a normative framework to answer this question. We introduce the computational construct of ‘deontic value’ – based on active inference and Markov decision processes – to formalize conceptions of social conformity and human decision-making. Deontic value is an attribute of choices, behaviors, or action sequences that inherit directly from deontic cues in our econiche (e.g., red traffic lights); namely, cues that denote an obligatory social rule. Crucially, the prosocial aspect of deontic value rests upon a particular form of circular causality: deontic cues exist in the environment in virtue of the environment being modified by repeated actions, while action itself is contingent upon the deontic value of environmental cues. We argue that this construction of deontic cues enables the epistemic (i.e., information-seeking) and pragmatic (i.e., goal- seeking) values of any behavior to be ‘cached’ or ‘outsourced’ to the environment, where the environment effectively ‘learns’ about the behavior of its denizens. We describe the process whereby this particular aspect of value enables learning of habitual behavior over neurodevelopmental and transgenerational timescales.

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    Europe PubMed Central
    Article . 2019
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      Europe PubMed Central
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    Authors: Maxwell James Ramstead; Anil Seth; Casper Hesp; Lars Sandved-Smith; +8 Authors

    AbstractThis paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as computational phenomenology because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience.

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    https://doi.org/10.31234/osf.i...
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    Review of Philosophy and Psychology
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      https://doi.org/10.31234/osf.i...
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      Review of Philosophy and Psychology
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    Authors: Constant, Axel; Ramstead, Maxwell J. D.; Veissière, Samuel P. L.; Campbell, John O.; +1 Authors

    In evolutionary biology, niche construction is sometimes described as a genuine evolutionary process whereby organisms, through their activities and regulatory mechanisms, modify their environment such as to steer their own evolutionary trajectory, and that of other species. There is ongoing debate, however, on the extent to which niche construction ought to be considered a bona fide evolutionary force, on a par with natural selection. Recent formulations of the variational free-energy principle as applied to the life sciences describe the properties of living systems, and their selection in evolution, in terms of variational inference. We argue that niche construction can be described using a variational approach. We propose new arguments to support the niche construction perspective, and to extend the variational approach to niche construction to current perspectives in various scientific fields.

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    Europe PubMed Central
    Article . 2018
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    Authors: Badcock, Paul B.; Friston, Karl J.; Ramstead, Maxwell J.D.;

    This article presents a unifying theory of the embodied, situated human brain called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that actively minimises the decay of our sensory and physical states by producing self-fulfilling action-perception cycles via dynamical interactions between hierarchically organised neurocognitive mechanisms. This theory synthesises the free-energy principle (FEP) in neuroscience with an evolutionary systems theory of psychology that explains our brains, minds, and behaviour by appealing to Tinbergen's four questions: adaptation, phylogeny, ontogeny, and mechanism. After leveraging the FEP to formally define the HMM across different spatiotemporal scales, we conclude by exploring its implications for theorising and research in the sciences of the mind and behaviour. Highlights • We present an interdisciplinary theory of the embodied, situated human brain called the Hierarchically Mechanistic Mind (HMM). • We describe the HMM as a model of neural architecture. • We explore how the HMM synthesises the free-energy principle in neuroscience with an evolutionary systems theory of psychology. • We translate our model into a new heuristic for theorising and research in neuroscience and psychology.

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    Article . 2019
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    Authors: Thomas Parr; Lancelot Da Costa; Conor Heins; Maxwell J. D. Ramstead; +1 Authors

    In theoretical biology, we are often interested in random dynamical systems—like the brain—that appear to model their environments. This can be formalized by appealing to the existence of a (possibly non-equilibrium) steady state, whose density preserves a conditional independence between a biological entity and its surroundings. From this perspective, the conditioning set, or Markov blanket, induces a form of vicarious synchrony between creature and world—as if one were modelling the other. However, this results in an apparent paradox. If all conditional dependencies between a system and its surroundings depend upon the blanket, how do we account for the mnemonic capacity of living systems? It might appear that any shared dependence upon past blanket states violates the independence condition, as the variables on either side of the blanket now share information not available from the current blanket state. This paper aims to resolve this paradox, and to demonstrate that conditional independence does not preclude memory. Our argument rests upon drawing a distinction between the dependencies implied by a steady state density, and the density dynamics of the system conditioned upon its configuration at a previous time. The interesting question then becomes: What determines the length of time required for a stochastic system to ‘forget’ its initial conditions? We explore this question for an example system, whose steady state density possesses a Markov blanket, through simple numerical analyses. We conclude with a discussion of the relevance for memory in cognitive systems like us.

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    Entropy
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    Authors: Maxwell J. D. Ramstead; Karl J. Friston; Inês Hipólito;

    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&mdash 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. 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 &lsquo 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 in relation to the ontological and epistemological status of representations&mdash and (2) if so, to assess which philosophical stance&mdash or intentionality of cognitive systems aboutness&rsquo

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    Authors: Ramstead, Maxwell James Désormeau; Badcock, Paul Benjamin; Friston, Karl John;

    The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery. Highlights • We describe a meta-theoretical ontology of life based on the free energy principle. • We propose a multiscale formulation of the free energy principle. • We translate our ontology into a systematic research heuristic for life sciences. • We apply this meta-theoretical ontology and research heuristic to Homo sapiens.

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    Physics of Life Reviews
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    Authors: Badcock, Paul B.; Friston, Karl J.; Ramstead, Maxwell J. D.; Ploeger, Annemie; +1 Authors

    The purpose of this review was to integrate leading paradigms in psychology and neuroscience with a theory of the embodied, situated human brain, called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that functions to minimize the entropy of our sensory and physical states via action-perception cycles generated by hierarchical neural dynamics. First, we review the extant literature on the hierarchical structure of the brain. Next, we derive the HMM from a broader evolutionary systems theory that explains neural structure and function in terms of dynamic interactions across four nested levels of biological causation (i.e., adaptation, phylogeny, ontogeny, and mechanism). We then describe how the HMM aligns with a global brain theory in neuroscience called the free-energy principle, leveraging this theory to mathematically formulate neural dynamics across hierarchical spatiotemporal scales. We conclude by exploring the implications of the HMM for psychological inquiry.

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    Authors: Thomas Parr; Dimitrije Marković; Maxwell James D. Ramstead; Maxwell James D. Ramstead; +6 Authors
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    Frontiers in Artificial Intelligence
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      Frontiers in Artificial Intelligence
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    Authors: Maxwell J D, Ramstead; Axel, Constant; Paul B, Badcock; Karl J, Friston;

    This paper addresses the challenges faced by multiscale formulations of the variational (free energy) approach to dynamics that obtain for large-scale ensembles. We review a framework for modelling complex adaptive control systems for multiscale free energy bounding organism–niche dynamics, thereby integrating the modelling strategies and heuristics of variational neuroethology with a broader perspective on the ecological nestedness of biotic systems. We extend the multiscale variational formulation beyond the action–perception loops of individual organisms by appealing to the variational approach to niche construction to explain the dynamics of coupled systems constituted by organisms and their ecological niche. We suggest that the statistical robustness of living systems is inherited, in part, from their eco-niches, as niches help coordinate dynamical patterns across larger spatiotemporal scales. We call this approach variational ecology. We argue that, when applied to cultural animals such as humans, variational ecology enables us to formulate not just a physics of individual minds, but also a physics of interacting minds across spatial and temporal scales – a physics of sentient systems that range from cells to societies. Highlights • We extend the multiscale variational free energy approach to large-scale ensembles. • We integrate multiscale modelling with a broad perspective on ecological nestedness. • We argue that the statistical robustness of living systems is ecologically inherited. • We propose variational ecology as a physics of sentient systems.

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    Europe PubMed Central
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    Authors: Axel, Constant; Maxwell J D, Ramstead; Samuel P L, Veissière; Karl, Friston;

    How do humans come to acquire shared expectations about how they ought to behave in distinct normalized social settings? This paper offers a normative framework to answer this question. We introduce the computational construct of ‘deontic value’ – based on active inference and Markov decision processes – to formalize conceptions of social conformity and human decision-making. Deontic value is an attribute of choices, behaviors, or action sequences that inherit directly from deontic cues in our econiche (e.g., red traffic lights); namely, cues that denote an obligatory social rule. Crucially, the prosocial aspect of deontic value rests upon a particular form of circular causality: deontic cues exist in the environment in virtue of the environment being modified by repeated actions, while action itself is contingent upon the deontic value of environmental cues. We argue that this construction of deontic cues enables the epistemic (i.e., information-seeking) and pragmatic (i.e., goal- seeking) values of any behavior to be ‘cached’ or ‘outsourced’ to the environment, where the environment effectively ‘learns’ about the behavior of its denizens. We describe the process whereby this particular aspect of value enables learning of habitual behavior over neurodevelopmental and transgenerational timescales.

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    Europe PubMed Central
    Article . 2019
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      Europe PubMed Central
      Article . 2019
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    Authors: Maxwell James Ramstead; Anil Seth; Casper Hesp; Lars Sandved-Smith; +8 Authors

    AbstractThis paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as computational phenomenology because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience.

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    https://doi.org/10.31234/osf.i...
    Preprint . 2021
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    Review of Philosophy and Psychology
    Article . 2022
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      https://doi.org/10.31234/osf.i...
      Preprint . 2021
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      Review of Philosophy and Psychology
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    Authors: Constant, Axel; Ramstead, Maxwell J. D.; Veissière, Samuel P. L.; Campbell, John O.; +1 Authors

    In evolutionary biology, niche construction is sometimes described as a genuine evolutionary process whereby organisms, through their activities and regulatory mechanisms, modify their environment such as to steer their own evolutionary trajectory, and that of other species. There is ongoing debate, however, on the extent to which niche construction ought to be considered a bona fide evolutionary force, on a par with natural selection. Recent formulations of the variational free-energy principle as applied to the life sciences describe the properties of living systems, and their selection in evolution, in terms of variational inference. We argue that niche construction can be described using a variational approach. We propose new arguments to support the niche construction perspective, and to extend the variational approach to niche construction to current perspectives in various scientific fields.

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    Europe PubMed Central
    Article . 2018
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      Europe PubMed Central
      Article . 2018
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