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Palacios ER, Chadderton P, Friston K, Houghton C. Cerebellar state estimation enables resilient coupling across behavioural domains. Sci Rep 2024; 14:6641. [PMID: 38503802 PMCID: PMC10951354 DOI: 10.1038/s41598-024-56811-x] [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: 08/09/2023] [Accepted: 03/11/2024] [Indexed: 03/21/2024] Open
Abstract
Cerebellar computations are necessary for fine behavioural control and may rely on internal models for estimation of behaviourally relevant states. Here, we propose that the central cerebellar function is to estimate how states interact with each other, and to use these estimates to coordinates extra-cerebellar neuronal dynamics underpinning a range of interconnected behaviours. To support this claim, we describe a cerebellar model for state estimation that includes state interactions, and link this model with the neuronal architecture and dynamics observed empirically. This is formalised using the free energy principle, which provides a dual perspective on a system in terms of both the dynamics of its physical-in this case neuronal-states, and the inferential process they entail. As a demonstration of this proposal, we simulate cerebellar-dependent synchronisation of whisking and respiration, which are known to be tightly coupled in rodents, as well as limb and tail coordination during locomotion. In summary, we propose that the ubiquitous involvement of the cerebellum in behaviour arises from its central role in precisely coupling behavioural domains.
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Affiliation(s)
- Ensor Rafael Palacios
- University of Bristol, School of Physiology Pharmacology and Neuroscience, Bristol, BS8 1TD, UK.
| | - Paul Chadderton
- University of Bristol, School of Physiology Pharmacology and Neuroscience, Bristol, BS8 1TD, UK
| | - Karl Friston
- UCL, Wellcome Centre for Human Neuroimaging, London, WC1N 3AR, UK
| | - Conor Houghton
- University of Bristol, Department of Computer Science, Bristol, BS8 1UB, UK
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2
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Corcoran AW, Perrykkad K, Feuerriegel D, Robinson JE. Body as First Teacher: The Role of Rhythmic Visceral Dynamics in Early Cognitive Development. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2023:17456916231185343. [PMID: 37694720 DOI: 10.1177/17456916231185343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Embodied cognition-the idea that mental states and processes should be understood in relation to one's bodily constitution and interactions with the world-remains a controversial topic within cognitive science. Recently, however, increasing interest in predictive processing theories among proponents and critics of embodiment alike has raised hopes of a reconciliation. This article sets out to appraise the unificatory potential of predictive processing, focusing in particular on embodied formulations of active inference. Our analysis suggests that most active-inference accounts invoke weak, potentially trivial conceptions of embodiment; those making stronger claims do so independently of the theoretical commitments of the active-inference framework. We argue that a more compelling version of embodied active inference can be motivated by adopting a diachronic perspective on the way rhythmic physiological activity shapes neural development in utero. According to this visceral afferent training hypothesis, early-emerging physiological processes are essential not only for supporting the biophysical development of neural structures but also for configuring the cognitive architecture those structures entail. Focusing in particular on the cardiovascular system, we propose three candidate mechanisms through which visceral afferent training might operate: (a) activity-dependent neuronal development, (b) periodic signal modeling, and (c) oscillatory network coordination.
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Affiliation(s)
- Andrew W Corcoran
- Monash Centre for Consciousness and Contemplative Studies, Monash University
- Cognition and Philosophy Laboratory, School of Philosophical, Historical, and International Studies, Monash University
| | - Kelsey Perrykkad
- Cognition and Philosophy Laboratory, School of Philosophical, Historical, and International Studies, Monash University
| | | | - Jonathan E Robinson
- Cognition and Philosophy Laboratory, School of Philosophical, Historical, and International Studies, Monash University
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3
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Leite S, Mota B, Silva AR, Commons ML, Miller PM, Rodrigues PP. Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity. PLoS One 2023; 18:e0290743. [PMID: 37651418 PMCID: PMC10470958 DOI: 10.1371/journal.pone.0290743] [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: 04/21/2023] [Accepted: 08/14/2023] [Indexed: 09/02/2023] Open
Abstract
Several studies demonstrate that the structure of the brain increases in hierarchical complexity throughout development. We tested if the structure of artificial neural networks also increases in hierarchical complexity while learning a developing task, called the balance beam problem. Previous simulations of this developmental task do not reflect a necessary premise underlying development: a more complex structure can be built out of less complex ones, while ensuring that the more complex structure does not replace the less complex one. In order to address this necessity, we segregated the input set by subsets of increasing Orders of Hierarchical Complexity. This is a complexity measure that has been extensively shown to underlie the complexity behavior and hypothesized to underlie the complexity of the neural structure of the brain. After segregating the input set, minimal neural network models were trained separately for each input subset, and adjacent complexity models were analyzed sequentially to observe whether there was a structural progression. Results show that three different network structural progressions were found, performing with similar accuracy, pointing towards self-organization. Also, more complex structures could be built out of less complex ones without substituting them, successfully addressing catastrophic forgetting and leveraging performance of previous models in the literature. Furthermore, the model structures trained on the two highest complexity subsets performed better than simulations of the balance beam present in the literature. As a major contribution, this work was successful in addressing hierarchical complexity structural growth in neural networks, and is the first that segregates inputs by Order of Hierarchical Complexity. Since this measure can be applied to all domains of data, the present method can be applied to future simulations, systematizing the simulation of developmental and evolutionary structural growth in neural networks.
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Affiliation(s)
- Sofia Leite
- CINTESIS – Center for Health Technology and Services Research, Porto, Portugal
- Dare Association, Inc. Boston, Massachusetts, United States of America
| | - Bruno Mota
- Laboratory of Experimental Mathematics and Theoretical Biology, Physics Institute, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil
| | - António Ramos Silva
- Department of Mechanical Engineering, Faculty of Engineering University of Porto, Porto, Portugal
- INEGI Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal
| | - Michael Lamport Commons
- Dare Association, Inc. Boston, Massachusetts, United States of America
- Beth Israel Deaconess Medical Center, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Patrice Marie Miller
- Dare Association, Inc. Boston, Massachusetts, United States of America
- Department of Psychology, Salem State University, Salem, Massachusetts, United States of America
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Zakaria Z, Idris Z, Abdul Halim S, Ghani ARI, Abdullah JM. Subthalamic Nucleus (STN)-Deep Brain Stimulation Reduces the Power of Mu and Beta Rhythms and Enhances Synchrony at the Motor Cortices in Parkinson's Disease: A Report of Two Cases. Cureus 2023; 15:e35057. [PMID: 36942168 PMCID: PMC10024512 DOI: 10.7759/cureus.35057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/16/2023] [Indexed: 02/18/2023] Open
Abstract
The motor circuit in Parkinson's disease (PD) involves the basal ganglia, thalamus, motor cortex, and cerebellum. Hence, subthalamic nucleus (STN) or globus pallidus internus deep brain stimulation is commonly used in treating refractory Parkinson's patients. During the procedure, the local field potential (LPF) is commonly made along the trajectory of the STN. Two cases were assessed, where an electroencephalographic recording at the sensorimotor cortices was also performed with and without stimulation at the optimal STN electrode site. The 'on' stimulation state associated with clinical improvement correlated with a marked reduction in the late theta (7.5 Hz), alpha (10.5 Hz) (Mu wave), and beta (20 Hz) wave power. Besides, more synchronized and coherent brainwaves were noted when the stimulation was 'on'.
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Affiliation(s)
- Zaitun Zakaria
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia (USM), Kota Bharu, MYS
| | - Zamzuri Idris
- Department of Neurosciences, School of Medical Sciences, Hospital Universiti Sains Malaysia (HUSM), Kota Bharu, MYS
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia (USM), Kota Bharu, MYS
| | - Sanihah Abdul Halim
- Department of Medicine, School of Medical Sciences, Universiti Sains Malaysia (USM) Kubang Kerian, Kota Bharu, MYS
| | - Abdul Rahman Izaini Ghani
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia (USM) Kubang Kerian, Kota Bharu, MYS
| | - Jafri M Abdullah
- Department of Neurosurgery, Universiti Sains Malaysia (USM) Health Campus, Kota Bharu, MYS
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5
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Kastel N, Hesp C, Ridderinkhof KR, Friston KJ. Small steps for mankind: Modeling the emergence of cumulative culture from joint active inference communication. Front Neurorobot 2023; 16:944986. [PMID: 36699948 PMCID: PMC9868743 DOI: 10.3389/fnbot.2022.944986] [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: 05/16/2022] [Accepted: 11/30/2022] [Indexed: 01/11/2023] Open
Abstract
Although the increase in the use of dynamical modeling in the literature on cultural evolution makes current models more mathematically sophisticated, these models have yet to be tested or validated. This paper provides a testable deep active inference formulation of social behavior and accompanying simulations of cumulative culture in two steps: First, we cast cultural transmission as a bi-directional process of communication that induces a generalized synchrony (operationalized as a particular convergence) between the belief states of interlocutors. Second, we cast social or cultural exchange as a process of active inference by equipping agents with the choice of who to engage in communication with. This induces trade-offs between confirmation of current beliefs and exploration of the social environment. We find that cumulative culture emerges from belief updating (i.e., active inference and learning) in the form of a joint minimization of uncertainty. The emergent cultural equilibria are characterized by a segregation into groups, whose belief systems are actively sustained by selective, uncertainty minimizing, dyadic exchanges. The nature of these equilibria depends sensitively on the precision afforded by various probabilistic mappings in each individual's generative model of their encultured niche.
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Affiliation(s)
- Natalie Kastel
- Amsterdam Brain and Cognition Centre, University of Amsterdam, Amsterdam, Netherlands,Institute for Advanced Study, University of Amsterdam, Amsterdam, Netherlands,Precision Psychiatry and Social Physiology Laboratory, Department of Psychiatry, CHU Sainte-Justine Research Center, Université de Montréal, Montreal, QC, Canada,*Correspondence: Natalie Kastel
| | - Casper Hesp
- Amsterdam Brain and Cognition Centre, University of Amsterdam, Amsterdam, Netherlands,Institute for Advanced Study, University of Amsterdam, Amsterdam, Netherlands,Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom,Department of Developmental Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - K. Richard Ridderinkhof
- Amsterdam Brain and Cognition Centre, University of Amsterdam, Amsterdam, Netherlands,Department of Developmental Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Karl J. Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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Redressing the emperor in causal clothing. Behav Brain Sci 2022; 45:e188. [PMID: 36172765 DOI: 10.1017/s0140525x22000176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Over-flexibility in the definition of Friston blankets obscures a key distinction between observational and interventional inference. The latter requires cognizers form not just a causal representation of the world but also of their own boundary and relationship with it, in order to diagnose the consequences of their actions. We suggest this locates the blanket in the eye of the beholder.
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The dual action of glioma-derived exosomes on neuronal activity: synchronization and disruption of synchrony. Cell Death Dis 2022; 13:705. [PMID: 35963860 PMCID: PMC9376103 DOI: 10.1038/s41419-022-05144-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 06/28/2022] [Accepted: 07/28/2022] [Indexed: 01/21/2023]
Abstract
Seizures represent a frequent symptom in gliomas and significantly impact patient morbidity and quality of life. Although the pathogenesis of tumor-related seizures is not fully understood, accumulating evidence indicates a key role of the peritumoral microenvironment. Brain cancer cells interact with neurons by forming synapses with them and by releasing exosomes, cytokines, and other small molecules. Strong interactions among neurons often lead to the synchronization of their activity. In this paper, we used an in vitro model to investigate the role of exosomes released by glioma cell lines and by patient-derived glioma stem cells (GSCs). The addition of exosomes released by U87 glioma cells to neuronal cultures at day in vitro (DIV) 4, when neurons are not yet synchronous, induces synchronization. At DIV 7-12 neurons become highly synchronous, and the addition of the same exosomes disrupts synchrony. By combining Ca2+ imaging, electrical recordings from single neurons with patch-clamp electrodes, substrate-integrated microelectrode arrays, and immunohistochemistry, we show that synchronization and de-synchronization are caused by the combined effect of (i) the formation of new neuronal branches, associated with a higher expression of Arp3, (ii) the modification of synaptic efficiency, and (iii) a direct action of exosomes on the electrical properties of neurons, more evident at DIV 7-12 when the threshold for spike initiation is significantly reduced. At DIV 7-12 exosomes also selectively boost glutamatergic signaling by increasing the number of excitatory synapses. Remarkably, de-synchronization was also observed with exosomes released by glioma-associated stem cells (GASCs) from patients with low-grade glioma but not from patients with high-grade glioma, where a more variable outcome was observed. These results show that exosomes released from glioma modify the electrical properties of neuronal networks and that de-synchronization caused by exosomes from low-grade glioma can contribute to the neurological pathologies of patients with brain cancers.
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Gandolfi D, Puglisi FM, Boiani GM, Pagnoni G, Friston KJ, D'Angelo EU, Mapelli J. Emergence of associative learning in a neuromorphic inference network. J Neural Eng 2022; 19. [PMID: 35508120 DOI: 10.1088/1741-2552/ac6ca7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 05/04/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE In the theoretical framework of predictive coding and active inference, the brain can be viewed as instantiating a rich generative model of the world that predicts incoming sensory data while continuously updating its parameters via minimization of prediction errors. While this theory has been successfully applied to cognitive processes - by modelling the activity of functional neural networks at a mesoscopic scale - the validity of the approach when modelling neurons as an ensemble of inferring agents, in a biologically plausible architecture, remained to be explored. APPROACH We modelled a simplified cerebellar circuit with individual neurons acting as Bayesian agents to simulate the classical delayed eyeblink conditioning protocol. Neurons and synapses adjusted their activity to minimize their prediction error, which was used as the network cost function. This cerebellar network was then implemented in hardware by replicating digital neuronal elements via a low-power microcontroller. MAIN RESULTS Persistent changes of synaptic strength - that mirrored neurophysiological observations - emerged via local (neurocentric) prediction error minimization, leading to the expression of associative learning. The same paradigm was effectively emulated in low-power hardware showing remarkably efficient performance compared to conventional neuromorphic architectures. SIGNIFICANCE These findings show that: i) an ensemble of free energy minimizing neurons - organized in a biological plausible architecture - can recapitulate functional self-organization observed in nature, such as associative plasticity, and ii) a neuromorphic network of inference units can learn unsupervised tasks without embedding predefined learning rules in the circuit, thus providing a potential avenue to a novel form of brain-inspired artificial intelligence.
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Affiliation(s)
- Daniela Gandolfi
- Department Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, Modena, Emilia-Romagna, 41121, ITALY
| | - Francesco Maria Puglisi
- DIEF, Universita degli Studi di Modena e Reggio Emilia, Via P. Vivarelli 10/1, Modena, MO, 41121, ITALY
| | - Giulia Maria Boiani
- Department Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, Modena, Emilia-Romagna, 41121, ITALY
| | - Giuseppe Pagnoni
- Department Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, Modena, Emilia-Romagna, 41121, ITALY
| | - Karl J Friston
- Institute of Neurology, University College London, 23 Queen Square, LONDON, WC1N 3BG, London, WC1N 3AR, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Egidio Ugo D'Angelo
- Department Brain and Behavioral Sciences, University of Pavia, Via Forlanini 6, Pavia, Pavia, Lombardia, 27100, ITALY
| | - Jonathan Mapelli
- Department Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, Modena, 41125, ITALY
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9
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Müller V. Neural Synchrony and Network Dynamics in Social Interaction: A Hyper-Brain Cell Assembly Hypothesis. Front Hum Neurosci 2022; 16:848026. [PMID: 35572007 PMCID: PMC9101304 DOI: 10.3389/fnhum.2022.848026] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 03/25/2022] [Indexed: 11/13/2022] Open
Abstract
Mounting neurophysiological evidence suggests that interpersonal interaction relies on continual communication between cell assemblies within interacting brains and continual adjustments of these neuronal dynamic states between the brains. In this Hypothesis and Theory article, a Hyper-Brain Cell Assembly Hypothesis is suggested on the basis of a conceptual review of neural synchrony and network dynamics and their roles in emerging cell assemblies within the interacting brains. The proposed hypothesis states that such cell assemblies can emerge not only within, but also between the interacting brains. More precisely, the hyper-brain cell assembly encompasses and integrates oscillatory activity within and between brains, and represents a common hyper-brain unit, which has a certain relation to social behavior and interaction. Hyper-brain modules or communities, comprising nodes across two or several brains, are considered as one of the possible representations of the hypothesized hyper-brain cell assemblies, which can also have a multidimensional or multilayer structure. It is concluded that the neuronal dynamics during interpersonal interaction is brain-wide, i.e., it is based on common neuronal activity of several brains or, more generally, of the coupled physiological systems including brains.
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Affiliation(s)
- Viktor Müller
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
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10
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Da Costa L, Friston K, Heins C, Pavliotis GA. Bayesian mechanics for stationary processes. Proc Math Phys Eng Sci 2022; 477:20210518. [PMID: 35153603 PMCID: PMC8652275 DOI: 10.1098/rspa.2021.0518] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 10/27/2021] [Indexed: 01/02/2023] Open
Abstract
This paper develops a Bayesian mechanics for adaptive systems. Firstly, we model the interface between a system and its environment with a Markov blanket. This affords conditions under which states internal to the blanket encode information about external states. Second, we introduce dynamics and represent adaptive systems as Markov blankets at steady state. This allows us to identify a wide class of systems whose internal states appear to infer external states, consistent with variational inference in Bayesian statistics and theoretical neuroscience. Finally, we partition the blanket into sensory and active states. It follows that active states can be seen as performing active inference and well-known forms of stochastic control (such as PID control), which are prominent formulations of adaptive behaviour in theoretical biology and engineering.
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Affiliation(s)
- Lancelot Da Costa
- Department of Mathematics, Imperial College London, London SW7 2AZ, UK.,Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
| | - Conor Heins
- Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz D-78457, Germany.,Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz D-78457, Germany.,Department of Biology, University of Konstanz, Konstanz D-78457, Germany
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11
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Affect-Logic, Embodiment, Synergetics, and the Free Energy Principle: New Approaches to the Understanding and Treatment of Schizophrenia. ENTROPY 2021; 23:e23121619. [PMID: 34945925 PMCID: PMC8700589 DOI: 10.3390/e23121619] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 11/24/2021] [Accepted: 11/29/2021] [Indexed: 11/16/2022]
Abstract
This theoretical paper explores the affect-logic approach to schizophrenia in light of the general complexity theories of cognition: embodied cognition, Haken's synergetics, and Friston's free energy principle. According to affect-logic, the mental apparatus is an embodied system open to its environment, driven by bioenergetic inputs of emotions. Emotions are rooted in goal-directed embodied states selected by evolutionary pressure for coping with specific situations such as fight, flight, attachment, and others. According to synergetics, nonlinear bifurcations and the emergence of new global patterns occur in open systems when control parameters reach a critical level. Applied to the emergence of psychotic states, synergetics and the proposed energetic understanding of emotions lead to the hypothesis that critical levels of emotional tension may be responsible for the transition from normal to psychotic modes of functioning in vulnerable individuals. In addition, the free energy principle through learning suggests that psychotic symptoms correspond to alternative modes of minimizing free energy, which then entails distorted perceptions of the body, self, and reality. This synthetic formulation has implications for novel therapeutic and preventive strategies in the treatment of psychoses, among these are milieu-therapeutic approaches of the Soteria type that focus on a sustained reduction of emotional tension and phenomenologically oriented methods for improving the perception of body, self, and reality.
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12
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Luppi AI, Mediano PAM, Rosas FE, Harrison DJ, Carhart-Harris RL, Bor D, Stamatakis EA. What it is like to be a bit: an integrated information decomposition account of emergent mental phenomena. Neurosci Conscious 2021; 2021:niab027. [PMID: 34804593 PMCID: PMC8600547 DOI: 10.1093/nc/niab027] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 06/24/2021] [Accepted: 08/12/2021] [Indexed: 01/08/2023] Open
Abstract
A central question in neuroscience concerns the relationship between consciousness and its physical substrate. Here, we argue that a richer characterization of consciousness can be obtained by viewing it as constituted of distinct information-theoretic elements. In other words, we propose a shift from quantification of consciousness-viewed as integrated information-to its decomposition. Through this approach, termed Integrated Information Decomposition (ΦID), we lay out a formal argument that whether the consciousness of a given system is an emergent phenomenon depends on its information-theoretic composition-providing a principled answer to the long-standing dispute on the relationship between consciousness and emergence. Furthermore, we show that two organisms may attain the same amount of integrated information, yet differ in their information-theoretic composition. Building on ΦID's revised understanding of integrated information, termed ΦR, we also introduce the notion of ΦR-ing ratio to quantify how efficiently an entity uses information for conscious processing. A combination of ΦR and ΦR-ing ratio may provide an important way to compare the neural basis of different aspects of consciousness. Decomposition of consciousness enables us to identify qualitatively different 'modes of consciousness', establishing a common space for mapping the phenomenology of different conscious states. We outline both theoretical and empirical avenues to carry out such mapping between phenomenology and information-theoretic modes, starting from a central feature of everyday consciousness: selfhood. Overall, ΦID yields rich new ways to explore the relationship between information, consciousness, and its emergence from neural dynamics.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge CB2 1SB, UK
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Fernando E Rosas
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London W12 0NN, UK
- Data Science Institute, Imperial College London, London SW7 2AZ, UK
- Centre for Complexity Science, Imperial College London, London SW7 2AZ, UK
| | - David J Harrison
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge CB2 1SB, UK
- Department of History and Philosophy of Science, University of Cambridge, Cambridge CB2 3RH, UK
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London W12 0NN, UK
| | - Daniel Bor
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
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13
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Abstract
Human social interactions depend on the ability to resolve uncertainty about the mental states of others. The context in which social interactions take place is crucial for mental state attribution as sensory inputs may be perceived differently depending on the context. In this paper, we introduce a mental state attribution task where a target-face with either an ambiguous or an unambiguous emotion is embedded in different social contexts. The social context is determined by the emotions conveyed by other faces in the scene. This task involves mental state attribution to a target-face (either happy or sad) depending on the social context. Using active inference models, we provide a proof of concept that an agent's perception of sensory stimuli may be altered by social context. We show with simulations that context congruency and facial expression coherency improve behavioural performance in terms of decision times. Furthermore, we show through simulations that the abnormal viewing strategies employed by patients with schizophrenia may be due to (i) an imbalance between the precisions of local and global features in the scene and (ii) a failure to modulate the sensory precision to contextualise emotions.
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14
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Albarracin M, Constant A, Friston KJ, Ramstead MJD. A Variational Approach to Scripts. Front Psychol 2021; 12:585493. [PMID: 34354621 PMCID: PMC8329037 DOI: 10.3389/fpsyg.2021.585493] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 06/28/2021] [Indexed: 01/14/2023] Open
Abstract
This paper proposes a formal reconstruction of the script construct by leveraging the active inference framework, a behavioral modeling framework that casts action, perception, emotions, and attention as processes of (Bayesian or variational) inference. We propose a first principles account of the script construct that integrates its different uses in the behavioral and social sciences. We begin by reviewing the recent literature that uses the script construct. We then examine the main mathematical and computational features of active inference. Finally, we leverage the resources of active inference to offer a formal model of scripts. Our integrative model accounts for the dual nature of scripts (as internal, psychological schema used by agents to make sense of event types and as constitutive behavioral categories that make up the social order) and also for the stronger and weaker conceptions of the construct (which do and do not relate to explicit action sequences, respectively).
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Affiliation(s)
- Mahault Albarracin
- Département d’informatique Cognitive, Université du Québec à Montréal, Montreal, QC, Canada
| | - Axel Constant
- Division of Social Transcultural Psychiatry, McGill University, Montreal, QC, Canada
| | - Karl J. Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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15
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Miller DR, Guenther DT, Maurer AP, Hansen CA, Zalesky A, Khoshbouei H. Dopamine Transporter Is a Master Regulator of Dopaminergic Neural Network Connectivity. J Neurosci 2021; 41:5453-5470. [PMID: 33980544 PMCID: PMC8221606 DOI: 10.1523/jneurosci.0223-21.2021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 04/19/2021] [Accepted: 05/01/2021] [Indexed: 12/13/2022] Open
Abstract
Dopaminergic neurons of the substantia nigra pars compacta (SNC) and ventral tegmental area (VTA) exhibit spontaneous firing activity. The dopaminergic neurons in these regions have been shown to exhibit differential sensitivity to neuronal loss and psychostimulants targeting dopamine transporter. However, it remains unclear whether these regional differences scale beyond individual neuronal activity to regional neuronal networks. Here, we used live-cell calcium imaging to show that network connectivity greatly differs between SNC and VTA regions with higher incidence of hub-like neurons in the VTA. Specifically, the frequency of hub-like neurons was significantly lower in SNC than in the adjacent VTA, consistent with the interpretation of a lower network resilience to SNC neuronal loss. We tested this hypothesis, in DAT-cre/loxP-GCaMP6f mice of either sex, when activity of an individual dopaminergic neuron is suppressed, through whole-cell patch clamp electrophysiology, in either SNC or VTA networks. Neuronal loss in the SNC increased network clustering, whereas the larger number of hub-neurons in the VTA overcompensated by decreasing network clustering in the VTA. We further show that network properties are regulatable via a dopamine transporter but not a D2 receptor dependent mechanism. Our results demonstrate novel regulatory mechanisms of functional network topology in dopaminergic brain regions.SIGNIFICANCE STATEMENT In this work, we begin to untangle the differences in complex network properties between the substantia nigra pars compacta (SNC) and VTA, that may underlie differential sensitivity between regions. The methods and analysis employed provide a springboard for investigations of network topology in multiple deep brain structures and disorders.
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Affiliation(s)
- Douglas R Miller
- Department of Neuroscience, University of Florida, Gainesville, Florida
| | - Dylan T Guenther
- Department of Neuroscience, University of Florida, Gainesville, Florida
| | - Andrew P Maurer
- Department of Neuroscience, University of Florida, Gainesville, Florida
| | - Carissa A Hansen
- Department of Neuroscience, University of Florida, Gainesville, Florida
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, Victoria 3010, Australia
- Department of Biomedical Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, Victoria 3010, Australia
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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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Ramstead MJD, Hesp C, Tschantz A, Smith R, Constant A, Friston K. Neural and phenotypic representation under the free-energy principle. Neurosci Biobehav Rev 2021; 120:109-122. [PMID: 33271162 PMCID: PMC7955287 DOI: 10.1016/j.neubiorev.2020.11.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 11/19/2020] [Accepted: 11/27/2020] [Indexed: 01/19/2023]
Abstract
The aim of this paper is to leverage the free-energy principle and its corollary process theory, active inference, to develop a generic, generalizable model of the representational capacities of living creatures; that is, a theory of phenotypic representation. Given their ubiquity, we are concerned with distributed forms of representation (e.g., population codes), whereby patterns of ensemble activity in living tissue come to represent the causes of sensory input or data. The active inference framework rests on the Markov blanket formalism, which allows us to partition systems of interest, such as biological systems, into internal states, external states, and the blanket (active and sensory) states that render internal and external states conditionally independent of each other. In this framework, the representational capacity of living creatures emerges as a consequence of their Markovian structure and nonequilibrium dynamics, which together entail a dual-aspect information geometry. This entails a modest representational capacity: internal states have an intrinsic information geometry that describes their trajectory over time in state space, as well as an extrinsic information geometry that allows internal states to encode (the parameters of) probabilistic beliefs about (fictive) external states. Building on this, we describe here how, in an automatic and emergent manner, information about stimuli can come to be encoded by groups of neurons bound by a Markov blanket; what is known as the neuronal packet hypothesis. As a concrete demonstration of this type of emergent representation, we present numerical simulations showing that self-organizing ensembles of active inference agents sharing the right kind of probabilistic generative model are able to encode recoverable information about a stimulus array.
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Affiliation(s)
- Maxwell J D Ramstead
- Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Culture, Mind, and Brain Program, McGill University, Montreal, Quebec, Canada; Wellcome Centre for Human Neuroimaging, University College London, London, WC1N3BG, UK.
| | - Casper Hesp
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N3BG, UK; Department of Psychology, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands; Amsterdam Brain and Cognition Centre, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands; Institute for Advanced Study, University of Amsterdam, Oude Turfmarkt 147, 1012 GC Amsterdam, the Netherlands.
| | - Alexander Tschantz
- Sackler Centre for Consciousness Science, University of Sussex, Brighton, UK; Department of Informatics, University of Sussex, Brighton, UK.
| | - Ryan Smith
- Laureate Institute for Brain Research, Tulsa, OK, USA.
| | - Axel Constant
- Culture, Mind, and Brain Program, McGill University, Montreal, Quebec, Canada; Wellcome Centre for Human Neuroimaging, University College London, London, WC1N3BG, UK; Theory and Method in Biosciences, Level 6, Charles Perkins Centre D17, Johns Hopkins Drive, University of Sydney, NSW, 2006, Australia.
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N3BG, UK.
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Hesp C. Beyond connectionism: A neuronal dance of ephaptic and synaptic interactions: Commentary on "The growth of cognition: Free energy minimization and the embryogenesis of cortical computation" by Wright and Bourke (2020). Phys Life Rev 2020; 36:40-43. [PMID: 32807647 DOI: 10.1016/j.plrev.2020.08.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 08/04/2020] [Indexed: 01/05/2023]
Affiliation(s)
- Casper Hesp
- Department of Psychology, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, Netherlands; Amsterdam Brain and Cognition Centre, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, Netherlands; Institute for Advanced Study, University of Amsterdam, Oude Turfmarkt 147, 1012 GC Amsterdam, Netherlands; Wellcome Centre for Human Neuroimaging, University College London, WC1N 3BG, London, UK.
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Tummolini L, Pezzulo G. The epistemic value of conformity: Comment on "The sense of should: A biologically-based framework for modeling social pressure" by Jordan E. Theriault, Liane Young, and Lisa Feldman Barrett. Phys Life Rev 2020; 36:74-76. [PMID: 32651147 DOI: 10.1016/j.plrev.2020.06.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 06/29/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Luca Tummolini
- Institute of Cognitive Sciences and Technologies, Italian National Research Council, Via San Martino della Battaglia 44, 00185, Rome, Italy.
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, Italian National Research Council, Via San Martino della Battaglia 44, 00185, Rome, Italy
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Safron A. An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation. Front Artif Intell 2020; 3:30. [PMID: 33733149 PMCID: PMC7861340 DOI: 10.3389/frai.2020.00030] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/03/2020] [Indexed: 01/01/2023] Open
Abstract
The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.
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Affiliation(s)
- Adam Safron
- Indiana University, Bloomington, IN, United States
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Abstract
This commentary focuses upon the relationship between two themes in the target article: the ways in which a Markov blanket may be defined and the role of precision and salience in mediating the interactions between what is internal and external to a system. These each rest upon the different perspectives we might take while "choosing" a Markov blanket.
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