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Falandays JB, Yoshimi J, Warren WH, Spivey MJ. A potential mechanism for Gibsonian resonance: behavioral entrainment emerges from local homeostasis in an unsupervised reservoir network. Cogn Neurodyn 2024; 18:1811-1834. [PMID: 39104666 PMCID: PMC11297877 DOI: 10.1007/s11571-023-09988-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 06/15/2023] [Accepted: 06/25/2023] [Indexed: 08/07/2024] Open
Abstract
While the cognitivist school of thought holds that the mind is analogous to a computer, performing logical operations over internal representations, the tradition of ecological psychology contends that organisms can directly "resonate" to information for action and perception without the need for a representational intermediary. The concept of resonance has played an important role in ecological psychology, but it remains a metaphor. Supplying a mechanistic account of resonance requires a non-representational account of central nervous system (CNS) dynamics. Towards this, we present a series of simple models in which a reservoir network with homeostatic nodes is used to control a simple agent embedded in an environment. This network spontaneously produces behaviors that are adaptive in each context, including (1) visually tracking a moving object, (2) substantially above-chance performance in the arcade game Pong, (2) and avoiding walls while controlling a mobile agent. Upon analyzing the dynamics of the networks, we find that behavioral stability can be maintained without the formation of stable or recurring patterns of network activity that could be identified as neural representations. These results may represent a useful step towards a mechanistic grounding of resonance and a view of the CNS that is compatible with ecological psychology.
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Affiliation(s)
| | - Jeffrey Yoshimi
- Department of Cognitive and Information Sciences, University of California, Merced, Merced, USA
| | - William H. Warren
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, USA
| | - Michael J. Spivey
- Department of Cognitive and Information Sciences, University of California, Merced, Merced, USA
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Albarracin M, Pitliya RJ, St. Clere Smithe T, Friedman DA, Friston K, Ramstead MJD. Shared Protentions in Multi-Agent Active Inference. ENTROPY (BASEL, SWITZERLAND) 2024; 26:303. [PMID: 38667857 PMCID: PMC11049075 DOI: 10.3390/e26040303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/14/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024]
Abstract
In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals. We begin with an overview of Husserlian phenomenology, focusing on aspects of inner time-consciousness, namely, retention, primal impression, and protention. We then review active inference as a formal approach to modeling agent behavior based on variational (approximate Bayesian) inference. Expanding upon Husserl's model of time consciousness, we consider collective goal-directed behavior, emphasizing shared protentions among agents and their connection to the shared generative models of active inference. This integrated framework aims to formalize shared goals in terms of shared protentions, and thereby shed light on the emergence of group intentionality. Building on this foundation, we incorporate mathematical tools from category theory, in particular, sheaf and topos theory, to furnish a mathematical image of individual and group interactions within a stochastic environment. Specifically, we employ morphisms between polynomial representations of individual agent models, allowing predictions not only of their own behaviors but also those of other agents and environmental responses. Sheaf and topos theory facilitates the construction of coherent agent worldviews and provides a way of representing consensus or shared understanding. We explore the emergence of shared protentions, bridging the phenomenology of temporal structure, multi-agent active inference systems, and category theory. Shared protentions are highlighted as pivotal for coordination and achieving common objectives. We conclude by acknowledging the intricacies stemming from stochastic systems and uncertainties in realizing shared goals.
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Affiliation(s)
- Mahault Albarracin
- VERSES Research Lab and Spatial Web Foundation, Los Angeles, CA 90016, USA; (R.J.P.); (T.S.C.S.); (K.F.); (M.J.D.R.)
- Département d’Informatique, l’Université du Québec à Montréal, Montreal, QC H3C 3P8, Canada
| | - Riddhi J. Pitliya
- VERSES Research Lab and Spatial Web Foundation, Los Angeles, CA 90016, USA; (R.J.P.); (T.S.C.S.); (K.F.); (M.J.D.R.)
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK
| | - Toby St. Clere Smithe
- VERSES Research Lab and Spatial Web Foundation, Los Angeles, CA 90016, USA; (R.J.P.); (T.S.C.S.); (K.F.); (M.J.D.R.)
- Topos Institute, Berkeley, CA 94704, USA
| | | | - Karl Friston
- VERSES Research Lab and Spatial Web Foundation, Los Angeles, CA 90016, USA; (R.J.P.); (T.S.C.S.); (K.F.); (M.J.D.R.)
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Maxwell J. D. Ramstead
- VERSES Research Lab and Spatial Web Foundation, Los Angeles, CA 90016, USA; (R.J.P.); (T.S.C.S.); (K.F.); (M.J.D.R.)
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, UK
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Fan L, Li Y, Zhao X, Huang ZG, Liu T, Wang J. Dynamic nonreversibility view of intrinsic brain organization and brain dynamic analysis of repetitive transcranial magnitude stimulation. Cereb Cortex 2024; 34:bhae098. [PMID: 38494890 DOI: 10.1093/cercor/bhae098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/19/2024] Open
Abstract
Intrinsic neural activities are characterized as endless spontaneous fluctuation over multiple time scales. However, how the intrinsic brain organization changes over time under local perturbation remains an open question. By means of statistical physics, we proposed an approach to capture whole-brain dynamics based on estimating time-varying nonreversibility and k-means clustering of dynamic varying nonreversibility patterns. We first used synthetic fMRI to investigate the effects of window parameters on the temporal variability of varying nonreversibility. Second, using real test-retest fMRI data, we examined the reproducibility, reliability, biological, and physiological correlation of the varying nonreversibility substates. Finally, using repetitive transcranial magnetic stimulation-fMRI data, we investigated the modulation effects of repetitive transcranial magnetic stimulation on varying nonreversibility substate dynamics. The results show that: (i) as window length increased, the varying nonreversibility variance decreased, while the sliding step almost did not alter it; (ii) the global high varying nonreversibility states and low varying nonreversibility states were reproducible across multiple datasets and different window lengths; and (iii) there were increased low varying nonreversibility states and decreased high varying nonreversibility states when the left frontal lobe was stimulated, but not the occipital lobe. Taken together, these results provide a thermodynamic equilibrium perspective of intrinsic brain organization and reorganization under local perturbation.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Xingjian Zhao
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Zi-Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
- The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China
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Ilan Y. The constrained disorder principle defines living organisms and provides a method for correcting disturbed biological systems. Comput Struct Biotechnol J 2022; 20:6087-6096. [DOI: 10.1016/j.csbj.2022.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/26/2022] [Accepted: 11/06/2022] [Indexed: 11/11/2022] Open
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Spatiotemporal constraints of causality: Blanket closure emerges from localized interactions between temporally separable subsystems. Behav Brain Sci 2022; 45:e197. [PMID: 36172774 DOI: 10.1017/s0140525x22000620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
In this commentary, I first acknowledge points of common ground with the target article by Bruineberg and colleagues. Then, I consider how certain ambiguities could be resolved by considering spatiotemporal constraints on causality. In particular I show how blanket closure emerges from localized interactions between temporally separable subsystems, and how this points to valuable directions of future research. Finally, I close with a process note discussing the allegorical implications of the authors' creative title.
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Examining the Continuity between Life and Mind: Is There a Continuity between Autopoietic Intentionality and Representationality? PHILOSOPHIES 2021. [DOI: 10.3390/philosophies6010018] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
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’.
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