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Manrique HM, Friston KJ, Walker MJ. 'Snakes and ladders' in paleoanthropology: From cognitive surprise to skillfulness a million years ago. Phys Life Rev 2024; 49:40-70. [PMID: 38513522 DOI: 10.1016/j.plrev.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 03/23/2024]
Abstract
A paradigmatic account may suffice to explain behavioral evolution in early Homo. We propose a parsimonious account that (1) could explain a particular, frequently-encountered, archeological outcome of behavior in early Homo - namely, the fashioning of a Paleolithic stone 'handaxe' - from a biological theoretic perspective informed by the free energy principle (FEP); and that (2) regards instances of the outcome as postdictive or retrodictive, circumstantial corroboration. Our proposal considers humankind evolving as a self-organizing biological ecosystem at a geological time-scale. We offer a narrative treatment of this self-organization in terms of the FEP. Specifically, we indicate how 'cognitive surprises' could underwrite an evolving propensity in early Homo to express sporadic unorthodox or anomalous behavior. This co-evolutionary propensity has left us a legacy of Paleolithic artifacts that is reminiscent of a 'snakes and ladders' board game of appearances, disappearances, and reappearances of particular archeological traces of Paleolithic behavior. When detected in the Early and Middle Pleistocene record, anthropologists and archeologists often imagine evidence of unusual or novel behavior in terms of early humankind ascending the rungs of a figurative phylogenetic 'ladder' - as if these corresponded to progressive evolution of cognitive abilities that enabled incremental achievements of increasingly innovative technical prowess, culminating in the cognitive ascendancy of Homo sapiens. The conjecture overlooks a plausible likelihood that behavior by an individual who was atypical among her conspecifics could have been disregarded in a community of Hominina (for definition see Appendix 1) that failed to recognize, imagine, or articulate potential advantages of adopting hitherto unorthodox behavior. Such failure, as well as diverse fortuitous demographic accidents, would cause exceptional personal behavior to be ignored and hence unremembered. It could disappear by a pitfall, down a 'snake', as it were, in the figurative evolutionary board game; thereby causing a discontinuity in the evolution of human behavior that presents like an evolutionary puzzle. The puzzle discomforts some paleoanthropologists trained in the natural and life sciences. They often dismiss it, explaining it away with such self-justifying conjectures as that, maybe, separate paleospecies of Homo differentially possessed different cognitive abilities, which, supposedly, could account for the presence or absence in the Pleistocene archeological record of traces of this or that behavioral outcome or skill. We argue that an alternative perspective - that inherits from the FEP and an individual's 'active inference' about its surroundings and of its own responses - affords a prosaic, deflationary, and parsimonious way to account for appearances, disappearances, and reappearances of particular behavioral outcomes and skills of early humankind.
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Affiliation(s)
- Héctor Marín Manrique
- Department of Psychology and Sociology, Universidad de Zaragoza, Ciudad Escolar, s/n, Teruel 44003, Spain
| | - Karl John Friston
- Imaging Neuroscience, Institute of Neurology, and The Wellcome Centre for Human Imaging, University College London, London WC1N 3AR, UK
| | - Michael John Walker
- Physical Anthropology, Departamento de Zoología y Antropología Física, Facultad de Biología, Universidad de Murcia, Campus Universitario de Espinardo Edificio 20, Murcia 30100, Spain.
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2
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Badcock PB. The mechanics of evolution: Phylogeny, ontogeny, and adaptive priors. Phys Life Rev 2024; 50:53-56. [PMID: 38943865 DOI: 10.1016/j.plrev.2024.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 07/01/2024]
Affiliation(s)
- Paul B Badcock
- Centre for Youth Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3052, Australia; Orygen, Parkville, Melbourne, Victoria, 3052, Australia.
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3
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Mougenot D, Matheson H. Theoretical strategies for an embodied cognitive neuroscience: Mechanistic explanations of brain-body-environment systems. Cogn Neurosci 2024:1-13. [PMID: 38736314 DOI: 10.1080/17588928.2024.2349546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Indexed: 05/14/2024]
Abstract
Cognitive neuroscience seeks to explain mind, brain, and behavior. But how do we generate explanations? In this integrative theoretical paper, we review the commitments of the 'New Mechanist' movement within the philosophy of science, focusing specifically on the role of mechanistic models in scientific explanation. We highlight how this approach differs from other explanatory approaches within the field, showing its unique contributions to the efforts of scientific explanation. We then argue that the commitments of the Embodied Cognition framework converge with the commitments of the New Mechanist movement in a way that provides a necessary explanatory strategy available to cognitive neuroscience. We then discuss a number of consequences of this convergence, including issues related to the inadequacy of statistical prediction, neuroscientific reduction, the autonomy of psychology from neuroscience, and psychological and neuroscientific ontology. We hope that our integrative thesis provides researchers with a theoretical strategy for an embodied cognitive neuroscience.
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Affiliation(s)
- Davy Mougenot
- Department of Psychology, Memorial University of Newfoundland, St. John's, Canada
| | - Heath Matheson
- Department of Psychology, Memorial University of Newfoundland, St. John's, Canada
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4
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Denfield GH, Kyzar EJ. The Nested States Model: An Empirical Framework for Integrating Brain and Mind. JOURNAL OF CONSCIOUSNESS STUDIES : CONTROVERSIES IN SCIENCE & THE HUMANITIES 2024; 31:28-55. [PMID: 38725942 PMCID: PMC11081467 DOI: 10.53765/20512201.31.3.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Philosophy of mind has made substantial progress on biologically-rooted approaches to understanding the mind and subjectivity through the enactivist perspective, but research on subjectivity within neuroscience has not kept apace. Indeed, we possess no principled means of relating experiential phenomena to neurophysiological processes. Here, we present the Nested States Model as a framework to guide empirical investigation into the relationship between subjectivity and neurobiology. Building on recent work in phenomenology and philosophy of mind, we develop an account of experiential states as layered, or nested. We argue that this nested structure is also apparent in brain activity. The recognition of this structural homology - that both experiential and brain states can be characterized as systems of nested states - brings our views of subjective mental states into broad alignment with our understanding of general principles and properties of brain activity. This alignment enables a more systematic approach to formulating specific hypotheses and predictions about how the two domains relate to one another.
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Affiliation(s)
- George H Denfield
- Department of Psychiatry, Columbia University, New York, USA
- Research Foundation for Mental Hygiene, Menands, NY, USA
- New York State Psychiatric Institute, New York, USA
| | - Evan J Kyzar
- Department of Psychiatry, Columbia University, New York, USA
- Research Foundation for Mental Hygiene, Menands, NY, USA
- New York State Psychiatric Institute, New York, USA
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5
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Albarracin M, Bouchard-Joly G, Sheikhbahaee Z, Miller M, Pitliya RJ, Poirier P. Feeling our place in the world: an active inference account of self-esteem. Neurosci Conscious 2024; 2024:niae007. [PMID: 38562605 PMCID: PMC10984624 DOI: 10.1093/nc/niae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 12/21/2023] [Accepted: 02/20/2024] [Indexed: 04/04/2024] Open
Abstract
Self-esteem, the evaluation of one's own worth or value, is a critical aspect of psychological well-being and mental health. In this paper, we propose an active inference account of self-esteem, casting it as a sociometer or an inferential capacity to interpret one's standing within a social group. This approach allows us to explore the interaction between an individual's self-perception and the expectations of their social environment.When there is a mismatch between these perceptions and expectations, the individual needs to adjust their actions or update their self-perception to better align with their current experiences. We also consider this hypothesis in relation with recent research on affective inference, suggesting that self-esteem enables the individual to track and respond to this discrepancy through affective states such as anxiety or positive affect. By acting as an inferential sociometer, self-esteem allows individuals to navigate and adapt to their social environment, ultimately impacting their psychological well-being and mental health.
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Affiliation(s)
- Mahault Albarracin
- Département d'Informatique, Université du Québec à Montréal, 405 Rue Sainte-Catherine Est, Montreal H2L 2C4, QC, Canada
| | - Gabriel Bouchard-Joly
- Département d'Informatique, Université du Québec à Montréal, 405 Rue Sainte-Catherine Est, Montreal H2L 2C4, QC, Canada
| | - Zahra Sheikhbahaee
- CHU Sainte-Justine Research Center, University of Montreal, 5757, Av. Decelles bureau 500, Montreal, QC H3S 2C3, Canada
| | - Mark Miller
- Monash Centre for Consciousness and Contemplative Studies, Monash University, Melboume, Australia
- Psychology Department, University of Toronto, Toronto, ON M5S 3G3, Canada
| | - Riddhi J Pitliya
- Department of Experimental Psychology Oxford University, Oxford OX1 2JD, United Kingdom
| | - Pierre Poirier
- Département d'Informatique, Université du Québec à Montréal, 405 Rue Sainte-Catherine Est, Montreal H2L 2C4, QC, Canada
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Ibanez A, Kringelbach ML, Deco G. A synergetic turn in cognitive neuroscience of brain diseases. Trends Cogn Sci 2024; 28:319-338. [PMID: 38246816 DOI: 10.1016/j.tics.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/15/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024]
Abstract
Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.
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Affiliation(s)
- Agustin Ibanez
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile; Global Brain Health Institute (GBHI), University California San Francisco (UCSF), San Francisco, CA, USA; Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Department of Psychiatry, University of Oxford, Oxford, UK.
| | - Morten L Kringelbach
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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McMillen P, Levin M. Collective intelligence: A unifying concept for integrating biology across scales and substrates. Commun Biol 2024; 7:378. [PMID: 38548821 PMCID: PMC10978875 DOI: 10.1038/s42003-024-06037-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 03/11/2024] [Indexed: 04/01/2024] Open
Abstract
A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.
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Affiliation(s)
- Patrick McMillen
- Department of Biology, Tufts University, Medford, MA, 02155, USA
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Michael Levin
- Department of Biology, Tufts University, Medford, MA, 02155, USA.
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA.
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA.
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8
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Ibanez A, Northoff G. Intrinsic timescales and predictive allostatic interoception in brain health and disease. Neurosci Biobehav Rev 2024; 157:105510. [PMID: 38104789 PMCID: PMC11184903 DOI: 10.1016/j.neubiorev.2023.105510] [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: 09/07/2023] [Revised: 11/29/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023]
Abstract
The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.
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Affiliation(s)
- Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, USA; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Trinity College Dublin, Dublin, Ireland.
| | - Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China; Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada.
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9
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Krupnik V, Danilova N. To be or not to be: The active inference of suicide. Neurosci Biobehav Rev 2024; 157:105531. [PMID: 38176631 DOI: 10.1016/j.neubiorev.2023.105531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/27/2023] [Accepted: 12/29/2023] [Indexed: 01/06/2024]
Abstract
Suicide presents an apparent paradox as a behavior whose motivation is not obvious since its outcome is non-existence and cannot be experienced. To address this paradox, we propose to frame suicide in the integrated theory of stress and active inference. We present an active inference-based cognitive model of suicide as a type of stress response hanging in cognitive balance between predicting self-preservation and self-destruction. In it, self-efficacy emerges as a meta-cognitive regulator that can bias the model toward either survival or suicide. The model suggests conditions under which cognitive homeostasis can override physiological homeostasis in motivating self-destruction. We also present a model proto-suicidal behavior, programmed cell death (apoptosis), in active inference terms to illustrate how an active inference model of self-destruction can be embodied in molecular mechanisms and to offer a hypothesis on another puzzle of suicide: why only humans among brain-endowed animals are known to practice it.
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Affiliation(s)
- Valery Krupnik
- Department of Mental Health, Naval Hospital Camp Pendleton, Camp Pendleton, CA, USA.
| | - Nadia Danilova
- Department of Cell Biology, UCLA (retired), Los Angeles, CA, USA
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Krupnik V. I like therefore I can, and I can therefore I like: the role of self-efficacy and affect in active inference of allostasis. Front Neural Circuits 2024; 18:1283372. [PMID: 38322807 PMCID: PMC10839114 DOI: 10.3389/fncir.2024.1283372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 01/02/2024] [Indexed: 02/08/2024] Open
Abstract
Active inference (AIF) is a theory of the behavior of information-processing open dynamic systems. It describes them as generative models (GM) generating inferences on the causes of sensory input they receive from their environment. Based on these inferences, GMs generate predictions about sensory input. The discrepancy between a prediction and the actual input results in prediction error. GMs then execute action policies predicted to minimize the prediction error. The free-energy principle provides a rationale for AIF by stipulating that information-processing open systems must constantly minimize their free energy (through suppressing the cumulative prediction error) to avoid decay. The theory of homeostasis and allostasis has a similar logic. Homeostatic set points are expectations of living organisms. Discrepancies between set points and actual states generate stress. For optimal functioning, organisms avoid stress by preserving homeostasis. Theories of AIF and homeostasis have recently converged, with AIF providing a formal account for homeo- and allostasis. In this paper, we present bacterial chemotaxis as molecular AIF, where mutual constraints by extero- and interoception play an essential role in controlling bacterial behavior supporting homeostasis. Extending this insight to the brain, we propose a conceptual model of the brain homeostatic GM, in which we suggest partition of the brain GM into cognitive and physiological homeostatic GMs. We outline their mutual regulation as well as their integration based on the free-energy principle. From this analysis, affect and self-efficacy emerge as the main regulators of the cognitive homeostatic GM. We suggest fatigue and depression as target neurocognitive phenomena for studying the neural mechanisms of such regulation.
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Affiliation(s)
- Valery Krupnik
- Department of Mental Health, Naval Hospital Camp Pendleton, Camp Pendleton, Oceanside, CA, United States
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Fresco N, Elber-Dorozko L. Scientists Invent New Hypotheses, Do Brains? Cogn Sci 2024; 48:e13400. [PMID: 38196160 DOI: 10.1111/cogs.13400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 10/19/2023] [Accepted: 12/19/2023] [Indexed: 01/11/2024]
Abstract
How are new Bayesian hypotheses generated within the framework of predictive processing? This explanatory framework purports to provide a unified, systematic explanation of cognition by appealing to Bayes rule and hierarchical Bayesian machinery alone. Given that the generation of new hypotheses is fundamental to Bayesian inference, the predictive processing framework faces an important challenge in this regard. By examining several cognitive-level and neurobiological architecture-inspired models of hypothesis generation, we argue that there is an essential difference between the two types of models. Cognitive-level models do not specify how they can be implemented in brains and include structures and assumptions that are external to the predictive processing framework. By contrast, neurobiological architecture-inspired models, which aim to better resemble brain processes, fail to explain important capacities of cognition, such as categorization and few-shot learning. The "scaling-up" challenge for proponents of predictive processing is to explain the relationship between these two types of models using only the theoretical and conceptual machinery of Bayesian inference.
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Affiliation(s)
- Nir Fresco
- Departments of Cognitive & Brain Sciences and Philosophy, Ben-Gurion University of the Negev
| | - Lotem Elber-Dorozko
- The Humanities and Arts Department, Technion - Israel Institute of Technology
- The Center for Philosophy of Science, University of Pittsburgh
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12
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Bettinger JS, Friston KJ. Conceptual foundations of physiological regulation incorporating the free energy principle and self-organized criticality. Neurosci Biobehav Rev 2023; 155:105459. [PMID: 37956880 DOI: 10.1016/j.neubiorev.2023.105459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 11/02/2023] [Accepted: 11/03/2023] [Indexed: 11/15/2023]
Abstract
Bettinger, J. S., K. J. Friston. Conceptual Foundations of Physiological Regulation incorporating the Free Energy Principle & Self-Organized Criticality. NEUROSCI BIOBEHAV REV 23(x) 144-XXX, 2022. Since the late nineteen-nineties, the concept of homeostasis has been contextualized within a broader class of "allostatic" dynamics characterized by a wider-berth of causal factors including social, psychological and environmental entailments; the fundamental nature of integrated brain-body dynamics; plus the role of anticipatory, top-down constraints supplied by intrinsic regulatory models. Many of these evidentiary factors are integral in original descriptions of homeostasis; subsequently integrated; and/or cite more-general operating principles of self-organization. As a result, the concept of allostasis may be generalized to a larger category of variational systems in biology, engineering and physics in terms of advances in complex systems, statistical mechanics and dynamics involving heterogenous (hierarchical/heterarchical, modular) systems like brain-networks and the internal milieu. This paper offers a three-part treatment. 1) interpret "allostasis" to emphasize a variational and relational foundation of physiological stability; 2) adapt the role of allostasis as "stability through change" to include a "return to stability" and 3) reframe the model of homeostasis with a conceptual model of criticality that licenses the upgrade to variational dynamics.
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Affiliation(s)
- Jesse S Bettinger
- Center for Process Studies, Claremont, CA, United States; The Cobb Institute, Claremont, CA, United States.
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK; Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK; The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
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Zaragoza-Jimenez N, Niehaus H, Thome I, Vogelbacher C, Ende G, Kamp-Becker I, Endres D, Jansen A. Modeling face recognition in the predictive coding framework: A combined computational modeling and functional imaging study. Cortex 2023; 168:203-225. [PMID: 37832490 DOI: 10.1016/j.cortex.2023.05.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 03/16/2023] [Accepted: 05/23/2023] [Indexed: 10/15/2023]
Abstract
The learning of new facial identities and the recognition of familiar faces are crucial processes for social interactions. Recently, a combined computational modeling and functional magnetic resonance imaging (fMRI) study used predictive coding as a biologically plausible framework to model face identity learning and to relate specific model parameters with brain activity (Apps and Tsakiris, Nat Commun 4, 2698, 2013). On the one hand, it was shown that behavioral responses on a two-option face recognition task could be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. On the other hand, brain activity in specific brain regions was associated with these parameters. More specifically, brain activity in the superior temporal sulcus (STS) varied with contextual familiarity, whereas activity in the fusiform face area (FFA) covaried with the prediction error parameter that updated facial familiarity. Literature combining fMRI assessments and computational modeling in humans still needs to be expanded. Furthermore, prior results are largely not replicated. The present study was, therefore, specifically set up to replicate these previous findings. Our results support the original findings in two critical aspects. First, on a group level, the behavioral responses were modeled best by the same computational model reported by the original authors. Second, we showed that estimates of these model parameters covary with brain activity in specific, face-sensitive brain regions. Our results thus provide further evidence that the functional properties of the face perception network conform to central principles of predictive coding. However, our study yielded diverging findings on specific computational model parameters reflected in brain activity. On the one hand, we did not find any evidence of a computational involvement of the STS. On the other hand, our results showed that activity in the right FFA was associated with multiple computational model parameters. Our data do not provide evidence for functional segregation between particular face-sensitive brain regions, as previously proposed.
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Affiliation(s)
- Nestor Zaragoza-Jimenez
- Laboratory for Multimodal Neuroimaging, Department of Psychiatry, University of Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany
| | - Hauke Niehaus
- Theoretical Cognitive Science Lab, Department of Psychology, University of Marburg, Germany.
| | - Ina Thome
- Laboratory for Multimodal Neuroimaging, Department of Psychiatry, University of Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany
| | - Christoph Vogelbacher
- Laboratory for Multimodal Neuroimaging, Department of Psychiatry, University of Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany
| | - Gabriele Ende
- Department of Neuroimaging, Central Institute of Mental Health (CIMH), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Inge Kamp-Becker
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany; Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Marburg, Germany
| | - Dominik Endres
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany; Theoretical Cognitive Science Lab, Department of Psychology, University of Marburg, Germany
| | - Andreas Jansen
- Laboratory for Multimodal Neuroimaging, Department of Psychiatry, University of Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany; Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Germany.
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14
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Bramley NR, Zhao B, Quillien T, Lucas CG. Local Search and the Evolution of World Models. Top Cogn Sci 2023. [PMID: 37850714 DOI: 10.1111/tops.12703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 10/19/2023]
Abstract
An open question regarding how people develop their models of the world is how new candidates are generated for consideration out of infinitely many possibilities. We discuss the role that evolutionary mechanisms play in this process. Specifically, we argue that when it comes to developing a global world model, innovation is necessarily incremental, involving the generation and selection among random local mutations and recombinations of (parts of) one's current model. We argue that, by narrowing and guiding exploration, this feature of cognitive search is what allows human learners to discover better theories, without ever grappling directly with the problem of finding a "global optimum," or best possible world model. We suggest this aspect of cognitive processing works analogously to how blind variation and selection mechanisms drive biological evolution. We propose algorithms developed for program synthesis provide candidate mechanisms for how human minds might achieve this. We discuss objections and implications of this perspective, finally suggesting that a better process-level understanding of how humans incrementally explore compositional theory spaces can shed light on how we think, and provide explanatory traction on fundamental cognitive biases, including anchoring, probability matching, and confirmation bias.
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Affiliation(s)
| | - Bonan Zhao
- Department of Psychology, University of Edinburgh
| | - Tadeg Quillien
- Institute of Language, Cognition & Computation, Informatics University of Edinburgh
| | - Christopher G Lucas
- Institute of Language, Cognition & Computation, Informatics University of Edinburgh
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15
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Rahman S. Myth of objectivity and the origin of symbols. FRONTIERS IN SOCIOLOGY 2023; 8:1269621. [PMID: 37885904 PMCID: PMC10598666 DOI: 10.3389/fsoc.2023.1269621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 09/13/2023] [Indexed: 10/28/2023]
Abstract
An age-old challenge in epistemology and moral philosophy is whether objectivity exists independent of subjective perspective. Alfred North Whitehead labeled it a "fallacy of misplaced concreteness"; after all, knowledge is represented elusively in symbols. I employ the free energy principle (FEP) to argue that the belief in moral objectivity, although perhaps fallacious, amounts to an ancient and universal human myth that is essential for our symbolic capacity. To perceive any object in a world of non-diminishing (perhaps irreducible) uncertainty, according to the FEP, its constituent parts must display common probabilistic tendencies, known as statistical beliefs, prior to its interpretation, or active inference, as a stable entity. Behavioral bias, subjective emotions, and social norms scale the scope of identity by coalescing agents with otherwise disparate goals and aligning their perspectives into a coherent structure. I argue that by declaring belief in norms as objective, e.g., expressing that a particular theft or infidelity was generally wrong, our ancestors psychologically constructed a type of identity bound only by shared faith in a perspective that technically transcended individual subjectivity. Signaling explicit belief in what were previously non-symbolic norms, as seen in many non-human animals, simulates a top-down point of view of our social interactions and thereby constructs our cultural niche and symbolic capacity. I demonstrate that, largely by contrasting with overly reductive analytical models that assume individual rational pursuit of extrinsic rewards, shared belief in moral conceptions, i.e., what amounts to a religious faith, remains a motivational cornerstone of our language, economic and civic institutions, stories, and psychology. Finally, I hypothesize that our bias for familiar accents (shibboleth), plausibly represents the phylogenetic and ontogenetic contextual origins of our impulse to minimize social surprise by declaring belief in the myth of objectivity.
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Affiliation(s)
- Shagor Rahman
- Independent Researcher, Westfield, NJ, United States
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16
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Lundbak Olesen C, Waade PT, Albantakis L, Mathys C. Phi fluctuates with surprisal: An empirical pre-study for the synthesis of the free energy principle and integrated information theory. PLoS Comput Biol 2023; 19:e1011346. [PMID: 37862364 PMCID: PMC10619809 DOI: 10.1371/journal.pcbi.1011346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 11/01/2023] [Accepted: 07/11/2023] [Indexed: 10/22/2023] Open
Abstract
The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second attempts a mathematical theory of conscious experience based on the intrinsic properties of a system. They are each concerned with complementary aspects of the properties of systems, one with life and behavior, the other with meaning and experience, so combining them has potential for scientific value. In this paper, we take a first step towards such a synthesis by expanding on the results of an earlier published evolutionary simulation study, which show a relationship between IIT-measures and fitness in differing complexities of tasks. We relate a basic information theoretic measure from the FEP, surprisal, to this result, finding that the surprisal of simulated agents' observations is inversely related to the general increase in fitness and integration over evolutionary time. Moreover, surprisal fluctuates together with IIT-based consciousness measures in within-trial time. This suggests that the consciousness measures used in IIT indirectly depend on the relation between the agent and the external world, and that it should therefore be possible to relate them to the theoretical concepts used in the FEP. Lastly, we suggest a future approach for investigating this relationship empirically.
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Affiliation(s)
| | | | - Larissa Albantakis
- Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Christoph Mathys
- Interacting Minds Centre (IMC), Aarhus University, Aarhus, Denmark
- Tranlational Neuromodeling Unit (TNU), University of Zurich and ETH Zurich, Zurich, Switzerland
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17
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Laukkonen RE, Webb M, Salvi C, Tangen JM, Slagter HA, Schooler JW. Insight and the selection of ideas. Neurosci Biobehav Rev 2023; 153:105363. [PMID: 37598874 DOI: 10.1016/j.neubiorev.2023.105363] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/19/2023] [Accepted: 08/15/2023] [Indexed: 08/22/2023]
Abstract
Perhaps it is no accident that insight moments accompany some of humanity's most important discoveries in science, medicine, and art. Here we propose that feelings of insight play a central role in (heuristically) selecting an idea from the stream of consciousness by capturing attention and eliciting a sense of intuitive confidence permitting fast action under uncertainty. The mechanisms underlying this Eureka heuristic are explained within an active inference framework. First, implicit restructuring via Bayesian reduction leads to a higher-order prediction error (i.e., the content of insight). Second, dopaminergic precision-weighting of the prediction error accounts for the intuitive confidence, pleasure, and attentional capture (i.e., the feeling of insight). This insight as precision account is consistent with the phenomenology, accuracy, and neural unfolding of insight, as well as its effects on belief and decision-making. We conclude by reflecting on dangers of the Eureka Heuristic, including the arising and entrenchment of false beliefs and the vulnerability of insights under psychoactive substances and misinformation.
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18
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Tabor A, Constant A. Lifeworlds in pain: a principled method for investigation and intervention. Neurosci Conscious 2023; 2023:niad021. [PMID: 37711314 PMCID: PMC10499064 DOI: 10.1093/nc/niad021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 08/03/2023] [Accepted: 08/23/2023] [Indexed: 09/16/2023] Open
Abstract
The experience of pain spans biological, psychological and sociocultural realms, both basic and complex, it is by turns necessary and devastating. Despite an extensive knowledge of the constituents of pain, the ability to translate this into effective intervention remains limited. It is suggested that current, multiscale, medical approaches, largely informed by the biopsychosocial (BPS) model, attempt to integrate knowledge but are undermined by an epistemological obligation, one that necessitates a prior isolation of the constituent parts. To overcome this impasse, we propose that an anthropological stance needs to be taken, underpinned by a Bayesian apparatus situated in computational psychiatry. Here, pain is presented within the context of lifeworlds, where attention is shifted away from the constituents of experience (e.g. nociception, reward processing and fear-avoidance), towards the dynamic affiliation that occurs between these processes over time. We argue that one can derive a principled method of investigation and intervention for pain from modelling approaches in computational psychiatry. We suggest that these modelling methods provide the necessary apparatus to navigate multiscale ontology and epistemology of pain. Finally, a unified approach to the experience of pain is presented, where the relational, inter-subjective phenomenology of pain is brought into contact with a principled method of translation; in so doing, revealing the conditions and possibilities of lifeworlds in pain.
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Affiliation(s)
- Abby Tabor
- Faculty of Health and Applied Sciences, University of the West of England, Frenchay Campus, Coldharbour Ln, Stoke Gifford, Bristol BS16 1QY, UK
- Centre for Pain Research, University of Bath, Claverton Down, Bath BA2 7AY, UK
| | - Axel Constant
- Department of Engineering and Informatics, The University of Sussex, Chichester 1 Room 002, Falmer, Brighton BN1 9QJ, UK
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19
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Lagasse E, Levin M. Future medicine: from molecular pathways to the collective intelligence of the body. Trends Mol Med 2023; 29:687-710. [PMID: 37481382 PMCID: PMC10527237 DOI: 10.1016/j.molmed.2023.06.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 07/24/2023]
Abstract
The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.
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Affiliation(s)
- Eric Lagasse
- McGowan Institute for Regenerative Medicine and Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
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20
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Badcock PB. The Zone of Bounded Surprisal: Raising further questions. Phys Life Rev 2023; 46:252-254. [PMID: 37536043 DOI: 10.1016/j.plrev.2023.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 07/11/2023] [Indexed: 08/05/2023]
Affiliation(s)
- Paul B Badcock
- Centre for Youth Mental Health, The University of Melbourne, 35 Poplar Road, Parkville, Melbourne, Victoria, 3052, Australia; Orygen, 35 Poplar Road, Parkville, Melbourne, Victoria, 3052 Australia.
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21
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Kent L. Mental Gravity: Depression as Spacetime Curvature of the Self, Mind, and Brain. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1275. [PMID: 37761574 PMCID: PMC10528036 DOI: 10.3390/e25091275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/09/2023] [Accepted: 08/18/2023] [Indexed: 09/29/2023]
Abstract
The principle of mental gravity contends that the mind uses physical gravity as a mental model or simulacrum to express the relation between the inner self and the outer world in terms of "UP"-ness and "DOWN"-ness. The simulation of increased gravity characterises a continuum of mental gravity which states includes depression as the paradigmatic example of being down, low, heavy, and slow. The physics of gravity can also be used to model spacetime curvature in depression, particularly gravitational time dilation as a property of MG analogous to subjective time dilation (i.e., the slowing of temporal flow in conscious experience). The principle has profound implications for the Temporo-spatial Theory of Consciousness (TTC) with regard to temporo-spatial alignment that establishes a "world-brain relation" that is centred on embodiment and the socialisation of conscious states. The principle of mental gravity provides the TTC with a way to incorporate the structure of the world into the structure of the brain, conscious experience, and thought. In concert with other theories of cognitive and neurobiological spacetime, the TTC can also work towards the "common currency" approach that also potentially connects the TTC to predictive processing frameworks such as free energy, neuronal gauge theories, and active inference accounts of depression. It gives the up/down dimension of space, as defined by the gravitational field, a unique status that is connected to both our embodied interaction with the physical world, and also the inverse, reflective, emotional but still embodied experience of ourselves.
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Affiliation(s)
- Lachlan Kent
- Mental Wellbeing Initiatives, Royal Melbourne Institute of Technology, Melbourne, VIC 3001, Australia
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22
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Peng X, Liu Q, Hubbard CS, Wang D, Zhu W, Fox MD, Liu H. Robust dynamic brain coactivation states estimated in individuals. SCIENCE ADVANCES 2023; 9:eabq8566. [PMID: 36652524 PMCID: PMC9848428 DOI: 10.1126/sciadv.abq8566] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 12/14/2022] [Indexed: 06/01/2023]
Abstract
A confluence of evidence indicates that brain functional connectivity is not static but rather dynamic. Capturing transient network interactions in the individual brain requires a technology that offers sufficient within-subject reliability. Here, we introduce an individualized network-based dynamic analysis technique and demonstrate that it is reliable in detecting subject-specific brain states during both resting state and a cognitively challenging language task. We evaluate the extent to which brain states show hemispheric asymmetries and how various phenotypic factors such as handedness and gender might influence network dynamics, discovering a right-lateralized brain state that occurred more frequently in men than in women and more frequently in right-handed versus left-handed individuals. Longitudinal brain state changes were also shown in 42 patients with subcortical stroke over 6 months. Our approach could quantify subject-specific dynamic brain states and has potential for use in both basic and clinical neuroscience research.
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Affiliation(s)
- Xiaolong Peng
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Liu
- Changping Laboratory, Beijing, China
| | - Catherine S. Hubbard
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Michael D. Fox
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Hesheng Liu
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
- Changping Laboratory, Beijing, China
- Biomedical Pioneering Innovation Center, Peking University, Beijing, China
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23
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Redshaw J, Ganea PA. Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210333. [PMID: 36314156 PMCID: PMC9620743 DOI: 10.1098/rstb.2021.0333] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/01/2022] [Indexed: 11/05/2022] Open
Abstract
Humans possess the remarkable capacity to imagine possible worlds and to demarcate possibilities and impossibilities in reasoning. We can think about what might happen in the future and consider what the present would look like had the past turned out differently. We reason about cause and effect, weigh up alternative courses of action and regret our mistakes. In this theme issue, leading experts from across the life sciences provide ground-breaking insights into the proximate questions of how thinking about possibilities works and develops, and the ultimate questions of its adaptive functions and evolutionary history. Together, the contributions delineate neurophysiological, cognitive and social mechanisms involved in mentally simulating possible states of reality; and point to conceptual changes in the understanding of singular and multiple possibilities during human development. The contributions also demonstrate how thinking about possibilities can augment learning, decision-making and judgement, and highlight aspects of the capacity that appear to be shared with non-human animals and aspects that may be uniquely human. Throughout the issue, it becomes clear that many developmental milestones achieved during childhood, and many of the most significant evolutionary and cultural triumphs of the human species, can only be understood with reference to increasingly complex reasoning about possibilities. This article is part of the theme issue 'Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny'.
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Affiliation(s)
- Jonathan Redshaw
- School of Psychology, The University of Queensland, Brisbane 4072, Australia
| | - Patricia A. Ganea
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada M5S 1V6
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24
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Safron A. Integrated world modeling theory expanded: Implications for the future of consciousness. Front Comput Neurosci 2022; 16:642397. [PMID: 36507308 PMCID: PMC9730424 DOI: 10.3389/fncom.2022.642397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 10/24/2022] [Indexed: 11/27/2022] Open
Abstract
Integrated world modeling theory (IWMT) is a synthetic theory of consciousness that uses the free energy principle and active inference (FEP-AI) framework to combine insights from integrated information theory (IIT) and global neuronal workspace theory (GNWT). Here, I first review philosophical principles and neural systems contributing to IWMT's integrative perspective. I then go on to describe predictive processing models of brains and their connections to machine learning architectures, with particular emphasis on autoencoders (perceptual and active inference), turbo-codes (establishment of shared latent spaces for multi-modal integration and inferential synergy), and graph neural networks (spatial and somatic modeling and control). Future directions for IIT and GNWT are considered by exploring ways in which modules and workspaces may be evaluated as both complexes of integrated information and arenas for iterated Bayesian model selection. Based on these considerations, I suggest novel ways in which integrated information might be estimated using concepts from probabilistic graphical models, flow networks, and game theory. Mechanistic and computational principles are also considered with respect to the ongoing debate between IIT and GNWT regarding the physical substrates of different kinds of conscious and unconscious phenomena. I further explore how these ideas might relate to the "Bayesian blur problem," or how it is that a seemingly discrete experience can be generated from probabilistic modeling, with some consideration of analogies from quantum mechanics as potentially revealing different varieties of inferential dynamics. I go on to describe potential means of addressing critiques of causal structure theories based on network unfolding, and the seeming absurdity of conscious expander graphs (without cybernetic symbol grounding). Finally, I discuss future directions for work centered on attentional selection and the evolutionary origins of consciousness as facilitated "unlimited associative learning." While not quite solving the Hard problem, this article expands on IWMT as a unifying model of consciousness and the potential future evolution of minds.
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Affiliation(s)
- Adam Safron
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Center for Psychedelic and Consciousness Research, Baltimore, MD, United States
- Cognitive Science Program, Indiana University, Bloomington, IN, United States
- Institute for Advanced Consciousness Studies (IACS), Santa Monica, CA, United States
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25
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Dodig-Crnkovic G. Cognition as Morphological/Morphogenetic Embodied Computation In Vivo. ENTROPY (BASEL, SWITZERLAND) 2022; 24:e24111576. [PMID: 36359666 PMCID: PMC9689251 DOI: 10.3390/e24111576] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 10/25/2022] [Accepted: 10/26/2022] [Indexed: 05/25/2023]
Abstract
Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is understood as a network of concurrent morphological/morphogenetic computations unfolding as a result of self-assembly, self-organization, and autopoiesis of physical, chemical, and biological agents. The present-day human-centric view of cognition still prevailing in major encyclopedias has a variety of open problems. This article considers recent research about morphological computation, morphogenesis, agency, basal cognition, extended evolutionary synthesis, free energy principle, cognition as Bayesian learning, active inference, and related topics, offering new theoretical and practical perspectives on problems inherent to the old computationalist cognitive models which were based on abstract symbol processing, and unaware of actual physical constraints and affordances of the embodiment of cognizing agents. A better understanding of cognition is centrally important for future artificial intelligence, robotics, medicine, and related fields.
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Affiliation(s)
- Gordana Dodig-Crnkovic
- Department of Computer Science and Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden;
- Division of Computer Science and Software Engineering, School of Innovation, Design and Engineering, Mälardalen University, 722 20 Västerås, Sweden
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26
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Bottemanne H. Théories du complot et COVID-19 : comment naissent les croyances complotistes ? Encephale 2022; 48:571-582. [PMID: 35597682 PMCID: PMC8818386 DOI: 10.1016/j.encep.2021.12.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/12/2021] [Accepted: 12/21/2021] [Indexed: 11/26/2022]
Abstract
La pandémie COVID-19 causée par le nouveau coronavirus SARS-CoV-2 a provoqué une crise mondiale sans précédent, associée à une prolifération de théories du complot. La prévalence de ces croyances complotistes a participé à affaiblir la crédibilité des mesures gouvernementales de santé publique, limiter l'accès des citoyens aux sources d’information fiables, et perturber la réponse des systèmes de santé face à la crise sanitaire. Plusieurs hypothèses ont été proposées en psychologie et en sciences sociales pour comprendre la genèse de ces croyances dans des contextes épidémiques, associant l’implication conjointe de facteurs psychologiques (comme la volonté de préserver sa sécurité, de maintenir une image de soi positive, ou encore de renforcer son rôle social) et sociodémographiques (comme les caractéristiques générationnelles, socioculturelles et politiques des individus). Toutefois, les découvertes récentes en sciences cognitives à propos des mécanismes élémentaires de traitement de l'information offrent un nouvel éclairage sur la génération des croyances conspirationnistes à travers les époques et les cultures. Dans cet article, nous proposons une définition de la théorie du complot et une classification des croyances complotistes pendant la pandémie de COVID-19. Nous montrons comment les mécanismes de génération et de mise à jour des croyances permettent d'expliquer la genèse des théories du complot, et nous proposons plusieurs hypothèses étayées par les recherches contemporaines en sciences cognitives et en sciences sociales à propos des théories du complot.
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27
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Rabeyron T. Psychoanalytic psychotherapies and the free energy principle. Front Hum Neurosci 2022; 16:929940. [PMID: 36016665 PMCID: PMC9395580 DOI: 10.3389/fnhum.2022.929940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/19/2022] [Indexed: 11/29/2022] Open
Abstract
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.
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Affiliation(s)
- Thomas Rabeyron
- Department of Psychology (Interpsy), University of Lorraine, Nancy, France
- Department of Psychology (KPU), University of Edinburgh, Edinburgh, United Kingdom
- Institut Universitaire de France, Paris, France
- *Correspondence: Thomas Rabeyron
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28
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Sarasso P, Francesetti G, Roubal J, Gecele M, Ronga I, Neppi-Modona M, Sacco K. Beauty and Uncertainty as Transformative Factors: A Free Energy Principle Account of Aesthetic Diagnosis and Intervention in Gestalt Psychotherapy. Front Hum Neurosci 2022; 16:906188. [PMID: 35911596 PMCID: PMC9325967 DOI: 10.3389/fnhum.2022.906188] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Drawing from field theory, Gestalt therapy conceives psychological suffering and psychotherapy as two intentional field phenomena, where unprocessed and chaotic experiences seek the opportunity to emerge and be assimilated through the contact between the patient and the therapist (i.e., the intentionality of contacting). This therapeutic approach is based on the therapist’s aesthetic experience of his/her embodied presence in the flow of the healing process because (1) the perception of beauty can provide the therapist with feedback on the assimilation of unprocessed experiences; (2) the therapist’s attentional focus on intrinsic aesthetic diagnostic criteria can facilitate the modification of rigid psychopathological fields by supporting the openness to novel experiences. The aim of the present manuscript is to review recent evidence from psychophysiology, neuroaesthetic research, and neurocomputational models of cognition, such as the free energy principle (FEP), which support the notion of the therapeutic potential of aesthetic sensibility in Gestalt psychotherapy. Drawing from neuroimaging data, psychophysiology and recent neurocognitive accounts of aesthetic perception, we propose a novel interpretation of the sense of beauty as a self-generated reward motivating us to assimilate an ever-greater spectrum of sensory and affective states in our predictive representation of ourselves and the world and supporting the intentionality of contact. Expecting beauty, in the psychotherapeutic encounter, can help therapists tolerate uncertainty avoiding impulsive behaviours and to stay tuned to the process of change.
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Affiliation(s)
- Pietro Sarasso
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
- *Correspondence: Pietro Sarasso,
| | - Gianni Francesetti
- International Institute for Gestalt Therapy and Psychopathology, Turin Center for Gestalt Therapy, Turin, Italy
| | - Jan Roubal
- Psychotherapy Training Gestalt Studia, Training in Psychotherapy Integration, Center for Psychotherapy Research in Brno, Masaryk University, Brno, Czechia
| | - Michela Gecele
- International Institute for Gestalt Therapy and Psychopathology, Turin Center for Gestalt Therapy, Turin, Italy
| | - Irene Ronga
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
| | - Marco Neppi-Modona
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
| | - Katiuscia Sacco
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
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29
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Andersen BP. Autistic-Like Traits and Positive Schizotypy as Diametric Specializations of the Predictive Mind. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2022; 17:1653-1672. [PMID: 35816687 DOI: 10.1177/17456916221075252] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
According to the predictive-processing framework, only prediction errors (rather than all sensory inputs) are processed by an organism's perceptual system. Prediction errors can be weighted such that errors from more reliable sources will be more influential in updating prior beliefs. It has previously been argued that autism-spectrum conditions can be understood as resulting from a predictive-processing mechanism in which an inflexibly high weight is given to sensory-prediction errors that results in overfitting their predictive models to the world. Deficits in executive functioning, theory of mind, and central coherence are all argued to flow naturally from this core underlying mechanism. The diametric model of autism and psychosis suggests a simple extension of this hypothesis. If people on the autism spectrum give an inflexibly high weight to sensory input, could it be that people with a predisposition to psychosis (i.e., people high in positive schizotypy) give an inflexibly low weight to sensory input? In this article I argue that evidence strongly supports this hypothesis. An inflexibly low weight given to sensory input can explain such disparate features of positive schizotypy as increased exploratory behavior, apophenia, hyper theory of mind, hyperactive imagination, attentional differences, and having idiosyncratic worldviews.
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30
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Caporuscio C, Fink SB, Sterzer P, Martin JM. When seeing is not believing: A mechanistic basis for predictive divergence. Conscious Cogn 2022; 102:103334. [DOI: 10.1016/j.concog.2022.103334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 02/13/2022] [Accepted: 04/10/2022] [Indexed: 11/15/2022]
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McParlin Z, Cerritelli F, Rossettini G, Friston KJ, Esteves JE. Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Biobehavioural Synchrony in Musculoskeletal Care. Front Behav Neurosci 2022; 16:897247. [PMID: 35846789 PMCID: PMC9280207 DOI: 10.3389/fnbeh.2022.897247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/24/2022] [Indexed: 12/05/2022] Open
Abstract
Touch is recognised as crucial for survival, fostering cooperative communication, accelerating recovery, reducing hospital stays, and promoting overall wellness and the therapeutic alliance. In this hypothesis and theory paper, we present an entwined model that combines touch for alignment and active inference to explain how the brain develops "priors" necessary for the health care provider to engage with the patient effectively. We appeal to active inference to explain the empirically integrative neurophysiological and behavioural mechanisms that underwrite synchronous relationships through touch. Specifically, we offer a formal framework for understanding - and explaining - the role of therapeutic touch and hands-on care in developing a therapeutic alliance and synchrony between health care providers and their patients in musculoskeletal care. We first review the crucial importance of therapeutic touch and its clinical role in facilitating the formation of a solid therapeutic alliance and in regulating allostasis. We then consider how touch is used clinically - to promote cooperative communication, demonstrate empathy, overcome uncertainty, and infer the mental states of others - through the lens of active inference. We conclude that touch plays a crucial role in achieving successful clinical outcomes and adapting previous priors to create intertwined beliefs. The ensuing framework may help healthcare providers in the field of musculoskeletal care to use hands-on care to strengthen the therapeutic alliance, minimise prediction errors (a.k.a., free energy), and thereby promote recovery from physical and psychological impairments.
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Affiliation(s)
- Zoe McParlin
- Clinical-Based Human Research Department, Foundation COME Collaboration, Pescara, Italy
| | - Francesco Cerritelli
- Clinical-Based Human Research Department, Foundation COME Collaboration, Pescara, Italy
| | | | - Karl J. Friston
- Institute of Neurology, Wellcome Centre for Human Neuroimaging, London, United Kingdom
| | - Jorge E. Esteves
- Clinical-Based Human Research Department, Foundation COME Collaboration, Pescara, Italy
- Malta ICOM Educational, Gzira, Malta
- University College of Osteopathy, London, United Kingdom
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Badcock PB, Ramstead MJD, Sheikhbahaee Z, Constant A. Applying the Free Energy Principle to Complex Adaptive Systems. ENTROPY 2022; 24:e24050689. [PMID: 35626572 PMCID: PMC9141822 DOI: 10.3390/e24050689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 05/11/2022] [Indexed: 11/30/2022]
Affiliation(s)
- Paul B. Badcock
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC 3010, Australia
- Orygen, Parkville, VIC 3052, Australia
- Correspondence:
| | - Maxwell J. D. Ramstead
- VERSES Research Lab and the Spatial Web Foundation, Los Angeles, CA 90016, USA;
- Wellcome Centre for Human Neuroimaging, University College London, London WC1E 6BT, UK
| | - Zahra Sheikhbahaee
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada;
| | - Axel Constant
- Charles Perkins Centre, The University of Sydney, John Hopkins Drive, Camperdown, NSW 2006, Australia;
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Constant A, Badcock P, Friston K, Kirmayer LJ. Integrating Evolutionary, Cultural, and Computational Psychiatry: A Multilevel Systemic Approach. Front Psychiatry 2022; 13:763380. [PMID: 35444580 PMCID: PMC9013887 DOI: 10.3389/fpsyt.2022.763380] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 02/14/2022] [Indexed: 12/21/2022] Open
Abstract
This paper proposes an integrative perspective on evolutionary, cultural and computational approaches to psychiatry. These three approaches attempt to frame mental disorders as multiscale entities and offer modes of explanations and modeling strategies that can inform clinical practice. Although each of these perspectives involves systemic thinking, each is limited in its ability to address the complex developmental trajectories and larger social systemic interactions that lead to mental disorders. Inspired by computational modeling in theoretical biology, this paper aims to integrate the modes of explanation offered by evolutionary, cultural and computational psychiatry in a multilevel systemic perspective. We apply the resulting Evolutionary, Cultural and Computational (ECC) model to Major Depressive Disorder (MDD) to illustrate how this integrative approach can guide research and practice in psychiatry.
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Affiliation(s)
- Axel Constant
- Department of Philosophy, The University of Sydney, Darlington, NSW, Australia
| | - Paul Badcock
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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Levin M. Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds. Front Syst Neurosci 2022; 16:768201. [PMID: 35401131 PMCID: PMC8988303 DOI: 10.3389/fnsys.2022.768201] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/24/2022] [Indexed: 12/11/2022] Open
Abstract
Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.
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Affiliation(s)
- Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, United States
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Cambridge, MA, United States
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Pezzulo G, Parr T, Friston K. The evolution of brain architectures for predictive coding and active inference. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200531. [PMID: 34957844 PMCID: PMC8710884 DOI: 10.1098/rstb.2020.0531] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 09/08/2021] [Indexed: 01/13/2023] Open
Abstract
This article considers the evolution of brain architectures for predictive processing. We argue that brain mechanisms for predictive perception and action are not late evolutionary additions of advanced creatures like us. Rather, they emerged gradually from simpler predictive loops (e.g. autonomic and motor reflexes) that were a legacy from our earlier evolutionary ancestors-and were key to solving their fundamental problems of adaptive regulation. We characterize simpler-to-more-complex brains formally, in terms of generative models that include predictive loops of increasing hierarchical breadth and depth. These may start from a simple homeostatic motif and be elaborated during evolution in four main ways: these include the multimodal expansion of predictive control into an allostatic loop; its duplication to form multiple sensorimotor loops that expand an animal's behavioural repertoire; and the gradual endowment of generative models with hierarchical depth (to deal with aspects of the world that unfold at different spatial scales) and temporal depth (to select plans in a future-oriented manner). In turn, these elaborations underwrite the solution to biological regulation problems faced by increasingly sophisticated animals. Our proposal aligns neuroscientific theorising-about predictive processing-with evolutionary and comparative data on brain architectures in different animal species. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino della Battaglia, 44, 00185 Rome, Italy
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, UK
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Safron A, Klimaj V, Hipólito I. On the Importance of Being Flexible: Dynamic Brain Networks and Their Potential Functional Significances. Front Syst Neurosci 2022; 15:688424. [PMID: 35126062 PMCID: PMC8814434 DOI: 10.3389/fnsys.2021.688424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 11/10/2021] [Indexed: 12/14/2022] Open
Abstract
In this theoretical review, we begin by discussing brains and minds from a dynamical systems perspective, and then go on to describe methods for characterizing the flexibility of dynamic networks. We discuss how varying degrees and kinds of flexibility may be adaptive (or maladaptive) in different contexts, specifically focusing on measures related to either more disjoint or cohesive dynamics. While disjointed flexibility may be useful for assessing neural entropy, cohesive flexibility may potentially serve as a proxy for self-organized criticality as a fundamental property enabling adaptive behavior in complex systems. Particular attention is given to recent studies in which flexibility methods have been used to investigate neurological and cognitive maturation, as well as the breakdown of conscious processing under varying levels of anesthesia. We further discuss how these findings and methods might be contextualized within the Free Energy Principle with respect to the fundamentals of brain organization and biological functioning more generally, and describe potential methodological advances from this paradigm. Finally, with relevance to computational psychiatry, we propose a research program for obtaining a better understanding of ways that dynamic networks may relate to different forms of psychological flexibility, which may be the single most important factor for ensuring human flourishing.
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Affiliation(s)
- Adam Safron
- Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Kinsey Institute, Indiana University, Bloomington, IN, United States
- Cognitive Science Program, Indiana University, Bloomington, IN, United States
| | - Victoria Klimaj
- Cognitive Science Program, Indiana University, Bloomington, IN, United States
- Complex Networks and Systems, Informatics Department, Indiana University, Bloomington, IN, United States
| | - Inês Hipólito
- Department of Philosophy, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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37
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Houser TM. Spatialization of Time in the Entorhinal-Hippocampal System. Front Behav Neurosci 2022; 15:807197. [PMID: 35069143 PMCID: PMC8770534 DOI: 10.3389/fnbeh.2021.807197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/06/2021] [Indexed: 11/19/2022] Open
Abstract
The functional role of the entorhinal-hippocampal system has been a long withstanding mystery. One key theory that has become most popular is that the entorhinal-hippocampal system represents space to facilitate navigation in one's surroundings. In this Perspective article, I introduce a novel idea that undermines the inherent uniqueness of spatial information in favor of time driving entorhinal-hippocampal activity. Specifically, by spatializing events that occur in succession (i.e., across time), the entorhinal-hippocampal system is critical for all types of cognitive representations. I back up this argument with empirical evidence that hints at a role for the entorhinal-hippocampal system in non-spatial representation, and computational models of the logarithmic compression of time in the brain.
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Affiliation(s)
- Troy M. Houser
- Department of Psychology, University of Oregon, Eugene, OR, United States
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38
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Borgstede M. Why Do Individuals Seek Information? A Selectionist Perspective. Front Psychol 2021; 12:684544. [PMID: 34867580 PMCID: PMC8639505 DOI: 10.3389/fpsyg.2021.684544] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 10/19/2021] [Indexed: 11/16/2022] Open
Abstract
Several authors have proposed that mechanisms of adaptive behavior, and reinforcement learning in particular, can be explained by an innate tendency of individuals to seek information about the local environment. In this article, I argue that these approaches adhere to an essentialist view of learning that avoids the question why information seeking should be favorable in the first place. I propose a selectionist account of adaptive behavior that explains why individuals behave as if they had a tendency to seek information without resorting to essentialist explanations. I develop my argument using a formal selectionist framework for adaptive behavior, the multilevel model of behavioral selection (MLBS). The MLBS has been introduced recently as a formal theory of behavioral selection that links reinforcement learning to natural selection within a single unified model. I show that the MLBS implies an average gain in information about the availability of reinforcement. Formally, this means that behavior reaches an equilibrium state, if and only if the Fisher information of the conditional probability of reinforcement is maximized. This coincides with a reduction in the randomness of the expected environmental feedback as captured by the information theoretic concept of expected surprise (i.e., entropy). The main result is that behavioral selection maximizes the information about the expected fitness consequences of behavior, which, in turn, minimizes average surprise. In contrast to existing attempts to link adaptive behavior to information theoretic concepts (e.g., the free energy principle), neither information gain nor surprise minimization is treated as a first principle. Instead, the result is formally deduced from the MLBS and therefore constitutes a mathematical property of the more general principle of behavioral selection. Thus, if reinforcement learning is understood as a selection process, there is no need to assume an active agent with an innate tendency to seek information or minimize surprise. Instead, information gain and surprise minimization emerge naturally because it lies in the very nature of selection to produce order from randomness.
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39
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Deane G. Consciousness in active inference: Deep self-models, other minds, and the challenge of psychedelic-induced ego-dissolution. Neurosci Conscious 2021; 2021:niab024. [PMID: 34484808 PMCID: PMC8408766 DOI: 10.1093/nc/niab024] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 07/26/2021] [Accepted: 08/02/2021] [Indexed: 11/16/2022] Open
Abstract
Predictive processing approaches to brain function are increasingly delivering promise for illuminating the computational underpinnings of a wide range of phenomenological states. It remains unclear, however, whether predictive processing is equipped to accommodate a theory of consciousness itself. Furthermore, objectors have argued that without specification of the core computational mechanisms of consciousness, predictive processing is unable to inform the attribution of consciousness to other non-human (biological and artificial) systems. In this paper, I argue that an account of consciousness in the predictive brain is within reach via recent accounts of phenomenal self-modelling in the active inference framework. The central claim here is that phenomenal consciousness is underpinned by 'subjective valuation'-a deep inference about the precision or 'predictability' of the self-evidencing ('fitness-promoting') outcomes of action. Based on this account, I argue that this approach can critically inform the distribution of experience in other systems, paying particular attention to the complex sensory attenuation mechanisms associated with deep self-models. I then consider an objection to the account: several recent papers argue that theories of consciousness that invoke self-consciousness as constitutive or necessary for consciousness are undermined by states (or traits) of 'selflessness'; in particular the 'totally selfless' states of ego-dissolution occasioned by psychedelic drugs. Drawing on existing work that accounts for psychedelic-induced ego-dissolution in the active inference framework, I argue that these states do not threaten to undermine an active inference theory of consciousness. Instead, these accounts corroborate the view that subjective valuation is the constitutive facet of experience, and they highlight the potential of psychedelic research to inform consciousness science, computational psychiatry and computational phenomenology.
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Affiliation(s)
- George Deane
- School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, 3 Charles Street, Edinburgh EH8 9AD, UK
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40
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Tison R, Poirier P. Active Inference and Cooperative Communication: An Ecological Alternative to the Alignment View. Front Psychol 2021; 12:708780. [PMID: 34456822 PMCID: PMC8397515 DOI: 10.3389/fpsyg.2021.708780] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 07/19/2021] [Indexed: 02/03/2023] Open
Abstract
We present and contrast two accounts of cooperative communication, both based on Active Inference, a framework that unifies biological and cognitive processes. The mental alignment account, defended in Vasil et al., takes the function of cooperative communication to be the alignment of the interlocutor's mental states, and cooperative communicative behavior to be driven by an evolutionarily selected adaptive prior belief favoring the selection of action policies that promote such an alignment. We argue that the mental alignment account should be rejected because it neglects the action-oriented nature of cooperative communication, which skews its view of the dynamics of communicative interaction. We introduce our own conception of cooperative communication, inspired by a more radical ecological interpretation of the active inference framework. Cooperative communication, on our ecological conception, serves to guide and constrain the dynamics of the cooperative interaction via the construction and restructuring of shared fields of affordances, in order to reach the local goals of the joint actions in which episodes of cooperative communication are embedded. We argue that our ecological conception provides a better theoretical standpoint to account for the action-oriented nature of cooperative communication in the active inference framework.
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Affiliation(s)
- Rémi Tison
- Department of Philosophy, Université du Québec à Montréal (UQAM), Montreal, QC, Canada
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41
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Molapour T, Hagan CC, Silston B, Wu H, Ramstead M, Friston K, Mobbs D. Seven computations of the social brain. Soc Cogn Affect Neurosci 2021; 16:745-760. [PMID: 33629102 PMCID: PMC8343565 DOI: 10.1093/scan/nsab024] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 12/01/2020] [Accepted: 02/24/2021] [Indexed: 02/07/2023] Open
Abstract
The social environment presents the human brain with the most complex information processing demands. The computations that the brain must perform occur in parallel, combine social and nonsocial cues, produce verbal and nonverbal signals and involve multiple cognitive systems, including memory, attention, emotion and learning. This occurs dynamically and at timescales ranging from milliseconds to years. Here, we propose that during social interactions, seven core operations interact to underwrite coherent social functioning; these operations accumulate evidence efficiently-from multiple modalities-when inferring what to do next. We deconstruct the social brain and outline the key components entailed for successful human-social interaction. These include (i) social perception; (ii) social inferences, such as mentalizing; (iii) social learning; (iv) social signaling through verbal and nonverbal cues; (v) social drives (e.g. how to increase one's status); (vi) determining the social identity of agents, including oneself and (vii) minimizing uncertainty within the current social context by integrating sensory signals and inferences. We argue that while it is important to examine these distinct aspects of social inference, to understand the true nature of the human social brain, we must also explain how the brain integrates information from the social world.
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Affiliation(s)
- Tanaz Molapour
- Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA
| | - Cindy C Hagan
- Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA
| | - Brian Silston
- Department of Psychology, Columbia University, New York, NY 10027, USA
| | - Haiyan Wu
- Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA
- CAS Key Laboratory of Behavioral Science, Department of Psychology, University of Chinese Academy of Sciences, Beijing, 10010, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 10010 China
| | - Maxwell Ramstead
- Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A2, Canada
- Culture, Mind, and Brain Program, McGill University, Montreal, Quebec H3A 1A2, Canada
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Dean Mobbs
- Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA
- Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA 91125, USA
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42
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Abstract
In this paper I offer an overview of the possible links between psychoanalytical metapsychology and contemporary work in neuroscience concerning entropy and the free energy principle. After briefly describing the theory of living systems put forward by the neuroscientist Karl Friston based on the notion of entropy, we sum up the use of the notion of free energy by Friston and Freud. I then analyze how these notions improve the intelligibility of psychic functioning and can be associated with several psychoanalytical concepts, in particular the death drive. I approach from the same perspective the regulation of free energy associated with psychic envelopes and early intersubjectivity. It thus appears that the psychic apparatus can be considered at its different levels, from the most primary to the most secondary, as having the essential function of reducing entropy and free energy. Various forms of "failure" of this process of linking, regulation and transformation of energy within the psychic apparatus could be considered as the origin of different psychopathological manifestations as suggested in the last part of this paper.
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Affiliation(s)
- Thomas Rabeyron
- Psychology Department, Université de Lorraine, Nancy, France
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An Active Inference Model of Collective Intelligence. ENTROPY 2021; 23:e23070830. [PMID: 34210008 PMCID: PMC8306784 DOI: 10.3390/e23070830] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 06/11/2021] [Accepted: 06/12/2021] [Indexed: 12/05/2022]
Abstract
Collective intelligence, an emergent phenomenon in which a composite system of multiple interacting agents performs at levels greater than the sum of its parts, has long compelled research efforts in social and behavioral sciences. To date, however, formal models of collective intelligence have lacked a plausible mathematical description of the relationship between local-scale interactions between autonomous sub-system components (individuals) and global-scale behavior of the composite system (the collective). In this paper we use the Active Inference Formulation (AIF), a framework for explaining the behavior of any non-equilibrium steady state system at any scale, to posit a minimal agent-based model that simulates the relationship between local individual-level interaction and collective intelligence. We explore the effects of providing baseline AIF agents (Model 1) with specific cognitive capabilities: Theory of Mind (Model 2), Goal Alignment (Model 3), and Theory of Mind with Goal Alignment (Model 4). These stepwise transitions in sophistication of cognitive ability are motivated by the types of advancements plausibly required for an AIF agent to persist and flourish in an environment populated by other highly autonomous AIF agents, and have also recently been shown to map naturally to canonical steps in human cognitive ability. Illustrative results show that stepwise cognitive transitions increase system performance by providing complementary mechanisms for alignment between agents’ local and global optima. Alignment emerges endogenously from the dynamics of interacting AIF agents themselves, rather than being imposed exogenously by incentives to agents’ behaviors (contra existing computational models of collective intelligence) or top-down priors for collective behavior (contra existing multiscale simulations of AIF). These results shed light on the types of generic information-theoretic patterns conducive to collective intelligence in human and other complex adaptive systems.
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Fox S. Psychomotor Predictive Processing. ENTROPY (BASEL, SWITZERLAND) 2021; 23:806. [PMID: 34202804 PMCID: PMC8303599 DOI: 10.3390/e23070806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023]
Abstract
Psychomotor experience can be based on what people predict they will experience, rather than on sensory inputs. It has been argued that disconnects between human experience and sensory inputs can be addressed better through further development of predictive processing theory. In this paper, the scope of predictive processing theory is extended through three developments. First, by going beyond previous studies that have encompassed embodied cognition but have not addressed some fundamental aspects of psychomotor functioning. Second, by proposing a scientific basis for explaining predictive processing that spans objective neuroscience and subjective experience. Third, by providing an explanation of predictive processing that can be incorporated into the planning and operation of systems involving robots and other new technologies. This is necessary because such systems are becoming increasingly common and move us farther away from the hunter-gatherer lifestyles within which our psychomotor functioning evolved. For example, beliefs that workplace robots are threatening can generate anxiety, while wearing hardware, such as augmented reality headsets and exoskeletons, can impede the natural functioning of psychomotor systems. The primary contribution of the paper is the introduction of a new formulation of hierarchical predictive processing that is focused on psychomotor functioning.
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Affiliation(s)
- Stephen Fox
- VTT Technical Research Centre of Finland, FI-02150 Espoo, Finland
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45
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From many to (n)one: Meditation and the plasticity of the predictive mind. Neurosci Biobehav Rev 2021; 128:199-217. [PMID: 34139248 DOI: 10.1016/j.neubiorev.2021.06.021] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 12/21/2022]
Abstract
How profoundly can humans change their own minds? In this paper we offer a unifying account of deconstructive meditation under the predictive processing view. We start from simple axioms. First, the brain makes predictions based on past experience, both phylogenetic and ontogenetic. Second, deconstructive meditation brings one closer to the here and now by disengaging anticipatory processes. We propose that practicing meditation therefore gradually reduces counterfactual temporally deep cognition, until all conceptual processing falls away, unveiling a state of pure awareness. Our account also places three main styles of meditation (focused attention, open monitoring, and non-dual) on a single continuum, where each technique relinquishes increasingly engrained habits of prediction, including the predicted self. This deconstruction can also permit certain insights by making the above processes available to introspection. Our framework is consistent with the state of empirical and (neuro)phenomenological evidence and illuminates the top-down plasticity of the predictive mind. Experimental rigor, neurophenomenology, and no-report paradigms are needed to further understanding of how meditation affects predictive processing and the self.
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46
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The entropy of chaotic transitions of EEG phase growth in bipolar disorder with lithium carbonate. Sci Rep 2021; 11:11888. [PMID: 34088967 PMCID: PMC8178301 DOI: 10.1038/s41598-021-91350-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 05/25/2021] [Indexed: 11/08/2022] Open
Abstract
The application of chaos measures the association of EEG signals which allows for differentiating pre and post-medicated epochs for bipolar patients. We propose a new approach on chaos necessary for proof of EEG metastability. Shannon entropies of concealed patterns of Schwarzian derivatives from absolute instantaneous frequency transformations of EEG signals after Hilbert transform are compared and found significantly statistically different between pre and post-medication periods when fitted to von Bertalanffy's functions. Schwarzian dynamics measures was compared at first baseline and then at the end of the first hour of one dose 300 mg lithium carbonate intake for the same subject in depressive patients. With an application of Schwarzian derivative on the prediction of von Bertalanffy's models, integration and segregation of phase growth orbits of neural oscillations can be understood as an influence of chaos on the mixing of frequencies. A phase growth constant parameter was performed to determine the bifurcation parameter of von Bertalanffy's model at each given non-overlapped EEG segment. Schwarzian derivative was sometimes very close positive near the origin but stayed negative for most of the number of segments. Lithium carbonate changed the chaotic invariants of the EEG Schwarzian dynamics and removed sharp boundaries in the bipolar spectrum.
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Constant A, Hesp C, Davey CG, Friston KJ, Badcock PB. Why Depressed Mood is Adaptive: A Numerical Proof of Principle for an Evolutionary Systems Theory of Depression. COMPUTATIONAL PSYCHIATRY (CAMBRIDGE, MASS.) 2021; 5:60-80. [PMID: 34113717 PMCID: PMC7610949 DOI: 10.5334/cpsy.70] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
We provide a proof of principle for an evolutionary systems theory (EST) of depression. This theory suggests that normative depressive symptoms counter socioenvironmental volatility by increasing interpersonal support via social signalling and that this response depends upon the encoding of uncertainty about social contingencies, which can be targeted by neuromodulatory antidepressants. We simulated agents that committed to a series of decisions in a social two-arm bandit task before and after social adversity, which precipitated depressive symptoms. Responses to social adversity were modelled under various combinations of social support and pharmacotherapy. The normative depressive phenotype responded positively to social support and simulated treatments with antidepressants. Attracting social support and administering antidepressants also alleviated anhedonia and social withdrawal, speaking to improvements in interpersonal relationships. These results support the EST of depression by demonstrating that following adversity, normative depressed mood preserved social inclusion with appropriate interpersonal support or pharmacotherapy.
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Affiliation(s)
- Axel Constant
- Charles Perkins Centre, The University of Sydney, AU; Culture, Mind, and Brain Program, McGill University, CA; Wellcome Trust Centre for Human Neuroimaging, University College London, UK
| | - Casper Hesp
- Wellcome Trust Centre for Human Neuroimaging, University College London, UK; Department of Developmental Psychology, University of Amsterdam, NL; Amsterdam Brain and Cognition Center, University of Amsterdam, NL; Institute for Advanced Study, University of Amsterdam, NL
| | - Christopher G Davey
- Centre for Youth Mental Health, The University of Melbourne, AU; Department of Psychiatry, The University of Melbourne, AU
| | - Karl J Friston
- Wellcome Trust Centre for Human Neuroimaging, University College London, UK
| | - Paul B Badcock
- Centre for Youth Mental Health, The University of Melbourne, AU; Department of Psychiatry, The University of Melbourne, AU; Orygen, AU
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Hipólito I, Ramstead MJD, Convertino L, Bhat A, Friston K, Parr T. Markov blankets in the brain. Neurosci Biobehav Rev 2021; 125:88-97. [PMID: 33607182 PMCID: PMC8373616 DOI: 10.1016/j.neubiorev.2021.02.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 01/18/2021] [Accepted: 02/01/2021] [Indexed: 01/19/2023]
Abstract
Recent characterisations of self-organising systems depend upon the presence of a 'Markov blanket': a statistical boundary that mediates the interactions between the inside and outside of a system. We leverage this idea to provide an analysis of partitions in neuronal systems. This is applicable to brain architectures at multiple scales, enabling partitions into single neurons, brain regions, and brain-wide networks. This treatment is based upon the canonical micro-circuitry used in empirical studies of effective connectivity, so as to speak directly to practical applications. The notion of effective connectivity depends upon the dynamic coupling between functional units, whose form recapitulates that of a Markov blanket at each level of analysis. The nuance afforded by partitioning neural systems in this way highlights certain limitations of 'modular' perspectives of brain function that only consider a single level of description.
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Affiliation(s)
- Inês Hipólito
- Humboldt-Universität zu Berlin, Department of Philosophy & Berlin School of Mind and Brain, Germany; Wellcome Centre for Human Neuroimaging, University College London, United Kingdom.
| | - Maxwell J D Ramstead
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom; Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Culture, Mind, and Brain Program, McGill University, Montreal, Quebec, Canada
| | - Laura Convertino
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom; Institute of Cognitive Neuroscience (ICN), University College London, London, United Kingdom
| | - Anjali Bhat
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom
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Tabas A, von Kriegstein K. Adjudicating Between Local and Global Architectures of Predictive Processing in the Subcortical Auditory Pathway. Front Neural Circuits 2021; 15:644743. [PMID: 33776657 PMCID: PMC7994860 DOI: 10.3389/fncir.2021.644743] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/16/2021] [Indexed: 11/13/2022] Open
Abstract
Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.
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Affiliation(s)
- Alejandro Tabas
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Katharina von Kriegstein
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Constant A, Clark A, Friston KJ. Representation Wars: Enacting an Armistice Through Active Inference. Front Psychol 2021; 11:598733. [PMID: 33488462 PMCID: PMC7817850 DOI: 10.3389/fpsyg.2020.598733] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 12/08/2020] [Indexed: 12/18/2022] Open
Abstract
Over the last 30 years, representationalist and dynamicist positions in the philosophy of cognitive science have argued over whether neurocognitive processes should be viewed as representational or not. Major scientific and technological developments over the years have furnished both parties with ever more sophisticated conceptual weaponry. In recent years, an enactive generalization of predictive processing – known as active inference – has been proposed as a unifying theory of brain functions. Since then, active inference has fueled both representationalist and dynamicist campaigns. However, we believe that when diving into the formal details of active inference, one should be able to find a solution to the war; if not a peace treaty, surely an armistice of a sort. Based on an analysis of these formal details, this paper shows how both representationalist and dynamicist sensibilities can peacefully coexist within the new territory of active inference.
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Affiliation(s)
- Axel Constant
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
| | - Andy Clark
- Department of Philosophy, The University of Sussex, Brighton, United Kingdom.,Department of Informatics, The University of Sussex, Brighton, United Kingdom.,Department of Philosophy, Macquarie University, Sydney, NSW, Australia
| | - Karl J Friston
- Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom
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