On Markov blankets and hierarchical self-organisation

Palacios, Ensor Rafael; Razi, Adeel; Parr, Thomas; Kirchhoff, Michael D.; Friston, Karl J.

doi:10.1016/j.jtbi.2019.110089

Cited by 88 publications

(98 citation statements)

References 59 publications

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“…In autopoiesis, attractor dynamics produce the very mechanisms out of which they are generated. FEP-AI views these autopoietic attractor configurations and ensuing trajectories as self-predicting generative models (Palacios et al, 2020 ), where that which is generated is the very probabilistic densities that define the existence of particular systems.…”

Section: Fep-ai and Iit: Unified Systems Theoriesmentioning

confidence: 99%

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation

Safron

2020

Front. Artif. Intell.

140

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The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.

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Section: Fep-ai and Iit: Unified Systems Theoriesmentioning

confidence: 99%

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation

Safron

2020

Front. Artif. Intell.

140

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“…Active inference rests on a few fundamental, interlocking mathematical constructs: these comprise the nonequilibrium steady state densities just discussed, as well Markov blankets, generative models, and variational free-energy ( Ramstead et al, 2019a , 2019b ; Ramstead et al, 2020 , 2019a , 2019b ). A growing literature appeals to Markov blankets to account for biological self-organization and the ability of living systems to remain alive over time ( Constant et al, 2018 ; Friston, 2013 , 2020 ; Hipólito, 2019 ; Kirchhoff et al, 2018 ; Kuchling et al, 2019 ; Palacios et al, 2020 ; Ramstead et al, 2018 , 2019a , 2019b ). This scheme gives us a principled definition of what it means to exist as a system ( Kirchhoff et al, 2018 ; Ramstead et al, 2018 ).…”

Section: Background: Multiscale Active Inferencementioning

confidence: 99%

“…Extant work on this topic has focused on the representational capacities of individual systems ( Friston, 2013 ; Kuchling et al, 2019 ), sometimes composed of other systems ( Palacios et al, 2020 ). In this paper, we extend this line of reasoning to patterns of group activity that enable a group of agents (be they neurons or other elements of larger systems that realise the appropriate dynamics) to collectively represent features of an external environment.…”

Section: Introductionmentioning

confidence: 99%

Neural and phenotypic representation under the free-energy principle

Ramstead

Hesp

Tschantz

et al. 2021

Neuroscience & Biobehavioral Reviews

Self Cite

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Highlights We develop a generalizable model of the representational capacities of living creatures based on the free-energy principle. We review the free-energy formulation and its account of the emergence of representational capacities in living creatures. We review formulations of self-assembly and pattern formation in living systems, premised on the free-energy principle. We provide numerical demonstrations for the neuronal packet hypothesis (that Markov blankets encode stimulus features).

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“…Markov blankets are ascribed to real-world systems in order to model the conditional independence between internal states and external states [50][51][52]: for example, conditional independence between a production process and the environment in which it is carried out. Markov blankets are not real features of real-world systems.…”

Section: Markov Blanketsmentioning

confidence: 99%

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Fox

2021

Entropy

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Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.

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On Markov blankets and hierarchical self-organisation

Cited by 88 publications

References 59 publications

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation

Neural and phenotypic representation under the free-energy principle

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

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