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Senden M, van Albada SJ, Pezzulo G, Falotico E, Hashim I, Kroner A, Kurth AC, Lanillos P, Narayanan V, Pennartz C, Petrovici MA, Steffen L, Weidler T, Goebel R. Modular-integrative modeling: a new framework for building brain models that blend biological realism and functional performance. Natl Sci Rev 2024; 11:nwad318. [PMID: 38577673 PMCID: PMC10989280 DOI: 10.1093/nsr/nwad318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 12/04/2023] [Accepted: 12/18/2023] [Indexed: 04/06/2024] Open
Abstract
This Perspective presents the Modular-Integrative Modeling approach, a novel framework in neuroscience for developing brain models that blend biological realism with functional performance to provide a holistic view on brain function in interaction with the body and environment.
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Affiliation(s)
- Mario Senden
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Sacha J van Albada
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Center, Germany
- Institute of Zoology, University of Cologne, Germany
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Italy
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Italy
| | - Ibrahim Hashim
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Alexander Kroner
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Anno C Kurth
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Center, Germany
- RWTH Aachen University, Germany
| | - Pablo Lanillos
- Donders Institute for Brain, Cognition and Behavior, Radboud University, The Netherlands
| | - Vaishnavi Narayanan
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Cyriel Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, The Netherlands
| | | | - Lea Steffen
- FZI Research Center of Information Technology, Germany
| | - Tonio Weidler
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
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Pezzulo G, D'Amato L, Mannella F, Priorelli M, Van de Maele T, Stoianov IP, Friston K. Neural representation in active inference: Using generative models to interact with-and understand-the lived world. Ann N Y Acad Sci 2024; 1534:45-68. [PMID: 38528782 DOI: 10.1111/nyas.15118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that underwrite planning and imagination; namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people-to action-oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities-and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Leo D'Amato
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
- Polytechnic University of Turin, Turin, Italy
| | - Francesco Mannella
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Matteo Priorelli
- Institute of Cognitive Sciences and Technologies, National Research Council, Padua, Italy
| | - Toon Van de Maele
- IDLab, Department of Information Technology, Ghent University - imec, Ghent, Belgium
| | - Ivilin Peev Stoianov
- Institute of Cognitive Sciences and Technologies, National Research Council, Padua, Italy
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- VERSES Research Lab, Los Angeles, California, USA
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Eluchans M, Donnarumma F, Pezzulo G. From particles to collectives: Commentary on "Path integrals, particular kinds, and strange things" by Friston et al. Phys Life Rev 2024; 48:106-108. [PMID: 38181489 DOI: 10.1016/j.plrev.2023.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 12/26/2023] [Indexed: 01/07/2024]
Affiliation(s)
- Mattia Eluchans
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy; University of Rome "La Sapienza"
| | - Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
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Pezzulo G, Parr T, Friston K. Active inference as a theory of sentient behavior. Biol Psychol 2024; 186:108741. [PMID: 38182015 DOI: 10.1016/j.biopsycho.2023.108741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 12/05/2023] [Accepted: 12/29/2023] [Indexed: 01/07/2024]
Abstract
This review paper offers an overview of the history and future of active inference-a unifying perspective on action and perception. Active inference is based upon the idea that sentient behavior depends upon our brains' implicit use of internal models to predict, infer, and direct action. Our focus is upon the conceptual roots and development of this theory of (basic) sentience and does not follow a rigid chronological narrative. We trace the evolution from Helmholtzian ideas on unconscious inference, through to a contemporary understanding of action and perception. In doing so, we touch upon related perspectives, the neural underpinnings of active inference, and the opportunities for future development. Key steps in this development include the formulation of predictive coding models and related theories of neuronal message passing, the use of sequential models for planning and policy optimization, and the importance of hierarchical (temporally) deep internal (i.e., generative or world) models. Active inference has been used to account for aspects of anatomy and neurophysiology, to offer theories of psychopathology in terms of aberrant precision control, and to unify extant psychological theories. We anticipate further development in all these areas and note the exciting early work applying active inference beyond neuroscience. This suggests a future not just in biology, but in robotics, machine learning, and artificial intelligence.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Thomas Parr
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK; VERSES AI Research Lab, Los Angeles, CA 90016, USA
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Pezzulo G, Parr T, Cisek P, Clark A, Friston K. Generating meaning: active inference and the scope and limits of passive AI. Trends Cogn Sci 2024; 28:97-112. [PMID: 37973519 DOI: 10.1016/j.tics.2023.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 10/03/2023] [Accepted: 10/05/2023] [Indexed: 11/19/2023]
Abstract
Prominent accounts of sentient behavior depict brains as generative models of organismic interaction with the world, evincing intriguing similarities with current advances in generative artificial intelligence (AI). However, because they contend with the control of purposive, life-sustaining sensorimotor interactions, the generative models of living organisms are inextricably anchored to the body and world. Unlike the passive models learned by generative AI systems, they must capture and control the sensory consequences of action. This allows embodied agents to intervene upon their worlds in ways that constantly put their best models to the test, thus providing a solid bedrock that is - we argue - essential to the development of genuine understanding. We review the resulting implications and consider future directions for generative AI.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Thomas Parr
- Nuffield Department of Clinical Neurosciences, University of Oxford
| | - Paul Cisek
- Department of Neuroscience, University of Montréal, Montréal, Québec, Canada
| | - Andy Clark
- Department of Philosophy, University of Sussex, Brighton, UK; Department of Informatics, University of Sussex, Brighton, UK; Department of Philosophy, Macquarie University, Sydney, New South Wales, Australia
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK; VERSES AI Research Lab, Los Angeles, CA, USA
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Ibáñez-Berganza M, Lucibello C, Mariani L, Pezzulo G. Information-theoretical analysis of the neural code for decoupled face representation. PLoS One 2024; 19:e0295054. [PMID: 38277355 PMCID: PMC10817192 DOI: 10.1371/journal.pone.0295054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 11/15/2023] [Indexed: 01/28/2024] Open
Abstract
Processing faces accurately and efficiently is a key capability of humans and other animals that engage in sophisticated social tasks. Recent studies reported a decoupled coding for faces in the primate inferotemporal cortex, with two separate neural populations coding for the geometric position of (texture-free) facial landmarks and for the image texture at fixed landmark positions, respectively. Here, we formally assess the efficiency of this decoupled coding by appealing to the information-theoretic notion of description length, which quantifies the amount of information that is saved when encoding novel facial images, with a given precision. We show that despite decoupled coding describes the facial images in terms of two sets of principal components (of landmark shape and image texture), it is more efficient (i.e., yields more information compression) than the encoding in terms of the image principal components only, which corresponds to the widely used eigenface method. The advantage of decoupled coding over eigenface coding increases with image resolution and is especially prominent when coding variants of training set images that only differ in facial expressions. Moreover, we demonstrate that decoupled coding entails better performance in three different tasks: the representation of facial images, the (daydream) sampling of novel facial images, and the recognition of facial identities and gender. In summary, our study provides a first principle perspective on the efficiency and accuracy of the decoupled coding of facial stimuli reported in the primate inferotemporal cortex.
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Affiliation(s)
- Miguel Ibáñez-Berganza
- IMT School for Advanced Studies, Lucca, Italy
- Istituto Italiano di Tecnologia, Napoli, Italy
| | - Carlo Lucibello
- Institute for Data Science and Analytics, Bocconi University, Milano, Italy
| | - Luca Mariani
- Department of Physics “E. R. Caianiello”, University of Salerno, Fisciano, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Roma, Italy
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Schoeller F, Horowitz AH, Jain A, Maes P, Reggente N, Christov-Moore L, Pezzulo G, Barca L, Allen M, Salomon R, Miller M, Di Lernia D, Riva G, Tsakiris M, Chalah MA, Klein A, Zhang B, Garcia T, Pollack U, Trousselard M, Verdonk C, Dumas G, Adrien V, Friston K. Interoceptive technologies for psychiatric interventions: From diagnosis to clinical applications. Neurosci Biobehav Rev 2024; 156:105478. [PMID: 38007168 DOI: 10.1016/j.neubiorev.2023.105478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 11/16/2023] [Accepted: 11/19/2023] [Indexed: 11/27/2023]
Abstract
Interoception-the perception of internal bodily signals-has emerged as an area of interest due to its implications in emotion and the prevalence of dysfunctional interoceptive processes across psychopathological conditions. Despite the importance of interoception in cognitive neuroscience and psychiatry, its experimental manipulation remains technically challenging. This is due to the invasive nature of existing methods, the limitation of self-report and unimodal measures of interoception, and the absence of standardized approaches across disparate fields. This article integrates diverse research efforts from psychology, physiology, psychiatry, and engineering to address this oversight. Following a general introduction to the neurophysiology of interoception as hierarchical predictive processing, we review the existing paradigms for manipulating interoception (e.g., interoceptive modulation), their underlying mechanisms (e.g., interoceptive conditioning), and clinical applications (e.g., interoceptive exposure). We suggest a classification for interoceptive technologies and discuss their potential for diagnosing and treating mental health disorders. Despite promising results, considerable work is still needed to develop standardized, validated measures of interoceptive function across domains and before these technologies can translate safely and effectively to clinical settings.
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Affiliation(s)
- Felix Schoeller
- Fluid Interfaces Group, Media Lab, Massachusetts Institute of Technology, USA; Institute for Advanced Consciousness Studies, Santa Monica, CA, USA; Department Cognitive Sciences, University of Haifa, Israel.
| | - Adam Haar Horowitz
- Fluid Interfaces Group, Media Lab, Massachusetts Institute of Technology, USA; Center for Sleep and Cognition, Beth Israel Deaconess Medical Center, Harvard Medical School, USA
| | - Abhinandan Jain
- Fluid Interfaces Group, Media Lab, Massachusetts Institute of Technology, USA
| | - Pattie Maes
- Fluid Interfaces Group, Media Lab, Massachusetts Institute of Technology, USA
| | - Nicco Reggente
- Institute for Advanced Consciousness Studies, Santa Monica, CA, USA
| | | | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Laura Barca
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Micah Allen
- Center of Functionally Integrative Neuroscience, Aarhus University, Denmark; Cambridge Psychiatry, University of Cambridge, UK
| | - Roy Salomon
- Department Cognitive Sciences, University of Haifa, Israel
| | - Mark Miller
- Center for Human Nature, Artificial Intelligence and Neuroscience, Hokkaido University, Japan
| | - Daniele Di Lernia
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy; Applied Technology for Neuro- Psychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Giuseppe Riva
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy; Applied Technology for Neuro- Psychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Manos Tsakiris
- The Warburg Institute, School of Advanced Study, University of London, UK; Department of Psychology, Royal Holloway, University of London, UK; Department of Behavioural and Cognitive Sciences, University of Luxembourg, Luxembourg
| | - Moussa A Chalah
- EA 4391, Excitabilité Nerveuse et Thérapeutique, Université Paris-Est Créteil, Créteil, France; Service de Physiologie - Explorations Fonctionnelles, Hôpital Henri Mondor, Créteil, France
| | - Arno Klein
- Child Mind Institute, New York City, USA
| | - Ben Zhang
- Institute for Advanced Consciousness Studies, Santa Monica, CA, USA
| | - Teresa Garcia
- Institute for Advanced Consciousness Studies, Santa Monica, CA, USA
| | - Ursula Pollack
- Institute for Advanced Consciousness Studies, Santa Monica, CA, USA
| | - Marion Trousselard
- Institut de Recherche Biomédicale des Armées, Place Général Valérie André, 91220 Brétigny-sur-Orge, France
| | - Charles Verdonk
- Institut de Recherche Biomédicale des Armées, Place Général Valérie André, 91220 Brétigny-sur-Orge, France
| | | | - Vladimir Adrien
- Infrastructure for Clinical Research in Neurosciences (iCRIN) Psychiatry, Paris Brain Institute, Paris, France; Department of Psychiatry, Hôpital Saint-Antoine, AP-HP, Sorbonne Université, 75012 Paris, France
| | - Karl Friston
- Queen Sq, Institute of Neurology, UCL, London WC1N 3AR, UK
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Gordon J, Chierichetti F, Panconesi A, Pezzulo G. Information foraging with an oracle. PLoS One 2023; 18:e0295005. [PMID: 38153955 PMCID: PMC10754449 DOI: 10.1371/journal.pone.0295005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 11/13/2023] [Indexed: 12/30/2023] Open
Abstract
During ecological decisions, such as when foraging for food or selecting a weekend activity, we often have to balance the costs and benefits of exploiting known options versus exploring novel ones. Here, we ask how individuals address such cost-benefit tradeoffs during tasks in which we can either explore by ourselves or seek external advice from an oracle (e.g., a domain expert or recommendation system). To answer this question, we designed two studies in which participants chose between inquiring (at a cost) for expert advice from an oracle, or to search for options without guidance, under manipulations affecting the optimal choice. We found that participants showed a greater propensity to seek expert advice when it was instrumental to increase payoff (study A), and when it reduced choice uncertainty, above and beyond payoff maximization (study B). This latter result was especially apparent in participants with greater trait-level intolerance of uncertainty. Taken together, these results suggest that we seek expert advice for both economic goals (i.e., payoff maximization) and epistemic goals (i.e., uncertainty minimization) and that our decisions to ask or not ask for advice are sensitive to cost-benefit tradeoffs.
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Affiliation(s)
- Jeremy Gordon
- University of California, Berkeley, Berkeley, CA, United States of America
| | | | | | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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Priorelli M, Pezzulo G, Stoianov IP. Deep kinematic inference affords efficient and scalable control of bodily movements. Proc Natl Acad Sci U S A 2023; 120:e2309058120. [PMID: 38085784 PMCID: PMC10743426 DOI: 10.1073/pnas.2309058120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 10/24/2023] [Indexed: 12/18/2023] Open
Abstract
Performing goal-directed movements requires mapping goals from extrinsic (workspace-relative) to intrinsic (body-relative) coordinates and then to motor signals. Mainstream approaches based on optimal control realize the mappings by minimizing cost functions, which is computationally demanding. Instead, active inference uses generative models to produce sensory predictions, which allows a cheaper inversion to the motor signals. However, devising generative models to control complex kinematic chains like the human body is challenging. We introduce an active inference architecture that affords a simple but effective mapping from extrinsic to intrinsic coordinates via inference and easily scales up to drive complex kinematic chains. Rich goals can be specified in both intrinsic and extrinsic coordinates using attractive or repulsive forces. The proposed model reproduces sophisticated bodily movements and paves the way for computationally efficient and biologically plausible control of actuated systems.
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Affiliation(s)
- Matteo Priorelli
- National Research Council, Institute of Cognitive Sciences and Technologies, Padova35137, Italy
| | - Giovanni Pezzulo
- National Research Council, Institute of Cognitive Sciences and Technologies, Rome00185, Italy
| | - Ivilin Peev Stoianov
- National Research Council, Institute of Cognitive Sciences and Technologies, Padova35137, Italy
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Muhle-Karbe PS, Sheahan H, Pezzulo G, Spiers HJ, Chien S, Schuck NW, Summerfield C. Goal-seeking compresses neural codes for space in the human hippocampus and orbitofrontal cortex. Neuron 2023; 111:3885-3899.e6. [PMID: 37725981 DOI: 10.1016/j.neuron.2023.08.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/10/2023] [Accepted: 08/18/2023] [Indexed: 09/21/2023]
Abstract
Humans can navigate flexibly to meet their goals. Here, we asked how the neural representation of allocentric space is distorted by goal-directed behavior. Participants navigated an agent to two successive goal locations in a grid world environment comprising four interlinked rooms, with a contextual cue indicating the conditional dependence of one goal location on another. Examining the neural geometry by which room and context were encoded in fMRI signals, we found that map-like representations of the environment emerged in both hippocampus and neocortex. Cognitive maps in hippocampus and orbitofrontal cortices were compressed so that locations cued as goals were coded together in neural state space, and these distortions predicted successful learning. This effect was captured by a computational model in which current and prospective locations are jointly encoded in a place code, providing a theory of how goals warp the neural representation of space in macroscopic neural signals.
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Affiliation(s)
- Paul S Muhle-Karbe
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; School of Psychology, University of Birmingham, Birmingham B15 2SA, UK; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, UK.
| | - Hannah Sheahan
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; Google DeepMind, London EC4A 3TW, UK
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
| | - Hugo J Spiers
- Department of Experimental Psychology, University College London, London WC1E 6BT, UK
| | - Samson Chien
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Nicolas W Schuck
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Aging Research, 14195 Berlin, Germany; Institute of Psychology, Universität Hamburg, 20146 Hamburg, Germany
| | - Christopher Summerfield
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, UK.
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Torricelli F, Tomassini A, Pezzulo G, Pozzo T, Fadiga L, D'Ausilio A. Actions are all we need for cognition, but do we know enough about them?: Reply to comments on "Motor invariants in action execution and perception". Phys Life Rev 2023; 47:30-32. [PMID: 37690326 DOI: 10.1016/j.plrev.2023.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/12/2023]
Affiliation(s)
- Francesco Torricelli
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy
| | - Alice Tomassini
- Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via San Martino della Battaglia 44, 00185 Rome, Italy
| | - Thierry Pozzo
- Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; INSERM UMR1093-CAPS, UFR des Sciences du Sport, Université Bourgogne Franche-Comté, F-21000, Dijon, France
| | - Luciano Fadiga
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy
| | - Alessandro D'Ausilio
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy.
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Lee DG, D'Alessandro M, Iodice P, Calluso C, Rustichini A, Pezzulo G. Risky decisions are influenced by individual attributes as a function of risk preference. Cogn Psychol 2023; 147:101614. [PMID: 37837926 DOI: 10.1016/j.cogpsych.2023.101614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 09/13/2023] [Accepted: 10/05/2023] [Indexed: 10/16/2023]
Abstract
It has long been assumed in economic theory that multi-attribute decisions involving several attributes or dimensions - such as probabilities and amounts of money to be earned during risky choices - are resolved by first combining the attributes of each option to form an overall expected value and then comparing the expected values of the alternative options, using a unique evidence accumulation process. A plausible alternative would be performing independent comparisons between the individual attributes and then integrating the results of the comparisons afterwards. Here, we devise a novel method to disambiguate between these types of models, by orthogonally manipulating the expected value of choice options and the relative salience of their attributes. Our results, based on behavioral measures and drift-diffusion models, provide evidence in favor of the framework where information about individual attributes independently impacts deliberation. This suggests that risky decisions are resolved by running in parallel multiple comparisons between the separate attributes - possibly alongside an additional comparison of expected value. This result stands in contrast with the assumption of standard economic theory that choices require a unique comparison of expected values and suggests that at the cognitive level, decision processes might be more distributed than commonly assumed. Beyond our planned analyses, we also discovered that attribute salience affects people of different risk preference type in different ways: risk-averse participants seem to focus more on probability, except when monetary amount is particularly high; risk-neutral/seeking participants, in contrast, seem to focus more on monetary amount, except when probability is particularly low.
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Affiliation(s)
- Douglas G Lee
- Tel Aviv University, School of Psychological Sciences, Tel Aviv, Israel; Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Marco D'Alessandro
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Pierpaolo Iodice
- Université de Rouen, Rouen, France; Movement Interactions Performance Lab, Le Mans Université, Le Mans, France
| | | | | | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
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Priorelli M, Pezzulo G, Stoianov IP. Active Vision in Binocular Depth Estimation: A Top-Down Perspective. Biomimetics (Basel) 2023; 8:445. [PMID: 37754196 PMCID: PMC10526497 DOI: 10.3390/biomimetics8050445] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 09/08/2023] [Accepted: 09/19/2023] [Indexed: 09/28/2023] Open
Abstract
Depth estimation is an ill-posed problem; objects of different shapes or dimensions, even if at different distances, may project to the same image on the retina. Our brain uses several cues for depth estimation, including monocular cues such as motion parallax and binocular cues such as diplopia. However, it remains unclear how the computations required for depth estimation are implemented in biologically plausible ways. State-of-the-art approaches to depth estimation based on deep neural networks implicitly describe the brain as a hierarchical feature detector. Instead, in this paper we propose an alternative approach that casts depth estimation as a problem of active inference. We show that depth can be inferred by inverting a hierarchical generative model that simultaneously predicts the eyes' projections from a 2D belief over an object. Model inversion consists of a series of biologically plausible homogeneous transformations based on Predictive Coding principles. Under the plausible assumption of a nonuniform fovea resolution, depth estimation favors an active vision strategy that fixates the object with the eyes, rendering the depth belief more accurate. This strategy is not realized by first fixating on a target and then estimating the depth; instead, it combines the two processes through action-perception cycles, with a similar mechanism of the saccades during object recognition. The proposed approach requires only local (top-down and bottom-up) message passing, which can be implemented in biologically plausible neural circuits.
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Affiliation(s)
- Matteo Priorelli
- Institute of Cognitive Sciences and Technologies, National Research Council of Italy, 35137 Padova, Italy;
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council of Italy, 00185 Rome, Italy;
| | - Ivilin Peev Stoianov
- Institute of Cognitive Sciences and Technologies, National Research Council of Italy, 35137 Padova, Italy;
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14
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Proietti R, Pezzulo G, Tessari A. An active inference model of hierarchical action understanding, learning and imitation. Phys Life Rev 2023; 46:92-118. [PMID: 37354642 DOI: 10.1016/j.plrev.2023.05.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 06/26/2023]
Abstract
We advance a novel active inference model of the cognitive processing that underlies the acquisition of a hierarchical action repertoire and its use for observation, understanding and imitation. We illustrate the model in four simulations of a tennis learner who observes a teacher performing tennis shots, forms hierarchical representations of the observed actions, and imitates them. Our simulations show that the agent's oculomotor activity implements an active information sampling strategy that permits inferring the kinematic aspects of the observed movement, which lie at the lowest level of the action hierarchy. In turn, this low-level kinematic inference supports higher-level inferences about deeper aspects of the observed actions: proximal goals and intentions. Finally, the inferred action representations can steer imitative responses, but interfere with the execution of different actions. Our simulations show that hierarchical active inference provides a unified account of action observation, understanding, learning and imitation and helps explain the neurobiological underpinnings of visuomotor cognition, including the multiple routes for action understanding in the dorsal and ventral streams and mirror mechanisms.
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Affiliation(s)
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Alessia Tessari
- Department of Psychology, University of Bologna, Italy; Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy
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15
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Maselli A, Gordon J, Eluchans M, Lancia GL, Thiery T, Moretti R, Cisek P, Pezzulo G. Beyond simple laboratory studies: Developing sophisticated models to study rich behavior. Phys Life Rev 2023; 46:220-244. [PMID: 37499620 DOI: 10.1016/j.plrev.2023.07.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/29/2023]
Abstract
Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions. In this article, we argue that psychology and neuroscience should increasingly adopt innovative experimental designs, measurement methods, analysis techniques and sophisticated computational models to probe rich, ecologically valid forms of behavior, including social behavior. We discuss the challenges of studying rich forms of behavior as well as the novel opportunities offered by state-of-the-art methodologies and new sensing technologies, and we highlight the importance of developing sophisticated formal models. We exemplify our arguments by reviewing some recent streams of research in psychology, neuroscience and other fields (e.g., sports analytics, ethology and robotics) that have addressed rich forms of behavior in a model-based manner. We hope that these "success cases" will encourage psychologists and neuroscientists to extend their toolbox of techniques with sophisticated behavioral models - and to use them to study rich forms of behavior as well as the cognitive and neural processes that they engage.
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Affiliation(s)
- Antonella Maselli
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Jeremy Gordon
- University of California, Berkeley, Berkeley, CA, 94704, United States
| | - Mattia Eluchans
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy; University of Rome "La Sapienza", Rome, Italy
| | - Gian Luca Lancia
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy; University of Rome "La Sapienza", Rome, Italy
| | - Thomas Thiery
- Department of Psychology, University of Montréal, Montréal, Québec, Canada
| | - Riccardo Moretti
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy; University of Rome "La Sapienza", Rome, Italy
| | - Paul Cisek
- Department of Neuroscience, University of Montréal, Montréal, Québec, Canada
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
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16
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Lee DG, Daunizeau J, Pezzulo G. Evidence or Confidence: What Is Really Monitored during a Decision? Psychon Bull Rev 2023; 30:1360-1379. [PMID: 36917370 PMCID: PMC10482769 DOI: 10.3758/s13423-023-02255-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2023] [Indexed: 03/16/2023]
Abstract
Assessing our confidence in the choices we make is important to making adaptive decisions, and it is thus no surprise that we excel in this ability. However, standard models of decision-making, such as the drift-diffusion model (DDM), treat confidence assessment as a post hoc or parallel process that does not directly influence the choice, which depends only on accumulated evidence. Here, we pursue the alternative hypothesis that what is monitored during a decision is an evolving sense of confidence (that the to-be-selected option is the best) rather than raw evidence. Monitoring confidence has the appealing consequence that the decision threshold corresponds to a desired level of confidence for the choice, and that confidence improvements can be traded off against the resources required to secure them. We show that most previous findings on perceptual and value-based decisions traditionally interpreted from an evidence-accumulation perspective can be explained more parsimoniously from our novel confidence-driven perspective. Furthermore, we show that our novel confidence-driven DDM (cDDM) naturally generalizes to decisions involving any number of alternative options - which is notoriously not the case with traditional DDM or related models. Finally, we discuss future empirical evidence that could be useful in adjudicating between these alternatives.
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Affiliation(s)
- Douglas G Lee
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
- School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.
| | - Jean Daunizeau
- Paris Brain Institute (ICM), Paris, France
- Translational Neuromodeling Unit (TNU), ETH, Zurich, Switzerland
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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17
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Gordon J, Knoblich G, Pezzulo G. Strategic Task Decomposition in Joint Action. Cogn Sci 2023; 47:e13316. [PMID: 37440442 DOI: 10.1111/cogs.13316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 06/15/2023] [Accepted: 06/23/2023] [Indexed: 07/15/2023]
Abstract
The core of human cooperation is people's ability to perform joint actions. Frequently, this requires effectively decomposing a joint task into individual subtasks, for example, when jointly shopping at the market to buy food. Surprisingly, little is known about how collaborators balance the costs of establishing a joint strategy for such decompositions and its expected benefits for a joint goal. We created a new online task that required pairs of randomly matched participants to jointly collect colored items. We then systematically varied the cognitive costs and benefits of applying a color-splitting strategy. The results showed that pairs adopted a color-splitting strategy more often when necessary to lower cognitive costs. However, once the strategy was jointly adopted, it continued to be used even when the cost-benefits changed. Our results provide first insights on how people decompose joint tasks into individual components and how decomposition strategies may evolve into conventions.
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Affiliation(s)
- Jeremy Gordon
- School of Information, University of California, Berkeley
| | - Guenther Knoblich
- Social Mind and Body Group, Department of Cognitive Science, Central European University
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council
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18
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Abstract
This paper aims to integrate some key constructs in the cognitive neuroscience of cognitive control and executive function by formalising the notion of cognitive (or mental) effort in terms of active inference. To do so, we call upon a task used in neuropsychology to assess impulse inhibition-a Stroop task. In this task, participants must suppress the impulse to read a colour word and instead report the colour of the text of the word. The Stroop task is characteristically effortful, and we unpack a theory of mental effort in which, to perform this task accurately, participants must overcome prior beliefs about how they would normally act. However, our interest here is not in overt action, but in covert (mental) action. Mental actions change our beliefs but have no (direct) effect on the outside world-much like deploying covert attention. This account of effort as mental action lets us generate multimodal (choice, reaction time, and electrophysiological) data of the sort we might expect from a human participant engaging in this task. We analyse how parameters determining cognitive effort influence simulated responses and demonstrate that-when provided only with performance data-these parameters can be recovered, provided they are within a certain range.
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Affiliation(s)
- Thomas Parr
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, UK.
| | - Emma Holmes
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, UK
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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19
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Rigoli F, Pezzulo G. The traps of adaptation: Addiction as maladaptive referent-dependent evaluation. Cogn Affect Behav Neurosci 2023:10.3758/s13415-023-01086-4. [PMID: 37016202 PMCID: PMC10400707 DOI: 10.3758/s13415-023-01086-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/03/2023] [Indexed: 04/06/2023]
Abstract
Referent-dependent evaluation theories propose that the ongoing context influences how the brain attributes value to stimuli. What are the implications of these theories for understanding addiction? The paper asks this question by casting this disorder as a form of maladaptive referent-dependent evaluation. Specifically, addiction is proposed to arise from the establishment of an excessive reference point following repeated drug consumption. Several key aspects of the disorder emerge from this perspective, including withdrawal, tolerance, enhanced craving, negative mood, and diminished stimulus discriminability. As highlighted in the paper, this formulation has important analogies with classical accounts of addiction, such as set point theories and associative learning theories. Moreover, this picture fits with the pattern of striatal dopaminergic activity observed in addiction, a key neural signature of the disorder. Overall, the referent-dependent evaluation approach emerges as a useful add-on to the theoretical toolkit adopted to interpret addiction. This also supports the idea that referent-dependent evaluation might offer a general framework to understand various disorders characterised by disrupted motivation.
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Affiliation(s)
- Francesco Rigoli
- Department of Psychology, City, University of London, Northampton Square, London, EC1V 0HB, UK.
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy
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20
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Lee DG, Pezzulo G. Changes in preferences reported after choices are informative, not merely statistical artifacts. Decision 2023. [DOI: 10.1037/dec0000207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
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21
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Torricelli F, Tomassini A, Pezzulo G, Pozzo T, Fadiga L, D'Ausilio A. Motor invariants in action execution and perception. Phys Life Rev 2023; 44:13-47. [PMID: 36462345 DOI: 10.1016/j.plrev.2022.11.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
The nervous system is sensitive to statistical regularities of the external world and forms internal models of these regularities to predict environmental dynamics. Given the inherently social nature of human behavior, being capable of building reliable predictive models of others' actions may be essential for successful interaction. While social prediction might seem to be a daunting task, the study of human motor control has accumulated ample evidence that our movements follow a series of kinematic invariants, which can be used by observers to reduce their uncertainty during social exchanges. Here, we provide an overview of the most salient regularities that shape biological motion, examine the role of these invariants in recognizing others' actions, and speculate that anchoring socially-relevant perceptual decisions to such kinematic invariants provides a key computational advantage for inferring conspecifics' goals and intentions.
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Affiliation(s)
- Francesco Torricelli
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy
| | - Alice Tomassini
- Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via San Martino della Battaglia 44, 00185 Rome, Italy
| | - Thierry Pozzo
- Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; INSERM UMR1093-CAPS, UFR des Sciences du Sport, Université Bourgogne Franche-Comté, F-21000, Dijon, France
| | - Luciano Fadiga
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy
| | - Alessandro D'Ausilio
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication, Italian Institute of Technology, Via Fossato di Mortara, 17-19, 44121 Ferrara, Italy.
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22
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Rens N, Lancia GL, Eluchans M, Schwartenbeck P, Cunnington R, Pezzulo G. Evidence for entropy maximisation in human free choice behaviour. Cognition 2023; 232:105328. [PMID: 36463639 DOI: 10.1016/j.cognition.2022.105328] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 11/10/2022] [Accepted: 11/12/2022] [Indexed: 12/05/2022]
Abstract
The freedom to choose between options is strongly linked to notions of free will. Accordingly, several studies have shown that individuals demonstrate a preference for choice, or the availability of multiple options, over and above utilitarian value. Yet we lack a decision-making framework that integrates preference for choice with traditional utility maximisation in free choice behaviour. Here we test the predictions of an inference-based model of decision-making in which an agent actively seeks states yielding entropy (availability of options) in addition to utility (economic reward). We designed a study in which participants freely navigated a virtual environment consisting of two consecutive choices leading to reward locations in separate rooms. Critically, the choice of one room always led to two final doors while, in the second room, only one door was permissible to choose. This design allowed us to separately determine the influence of utility and entropy on participants' choice behaviour and their self-evaluation of free will. We found that choice behaviour was better predicted by an inference-based model than by expected utility alone, and that both the availability of options and the value of the context positively influenced participants' perceived freedom of choice. Moreover, this consideration of options was apparent in the ongoing motion dynamics as individuals navigated the environment. In a second study, in which participants selected between rooms that gave access to three or four doors, we observed a similar pattern of results, with participants preferring the room that gave access to more options and feeling freer in it. These results suggest that free choice behaviour is well explained by an inference-based framework in which both utility and entropy are optimised and supports the idea that the feeling of having free will is tightly related to options availability.
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Affiliation(s)
- Natalie Rens
- Queensland Brain Institute, The University of Queensland, St Lucia, Queensland 4072, Australia
| | - Gian Luca Lancia
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino della Battaglia, 44, 00185 Rome, Italy; University of Rome "La Sapienza", Rome, Italy
| | - Mattia Eluchans
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino della Battaglia, 44, 00185 Rome, Italy; University of Rome "La Sapienza", Rome, Italy
| | - Philipp Schwartenbeck
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom; Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Baden-Württemberg, Germany
| | - Ross Cunnington
- School of Psychology, The University of Queensland, St Lucia, Queensland 4072, Australia
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino della Battaglia, 44, 00185 Rome, Italy.
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23
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Barca L, Candidi M, Lancia GL, Maglianella V, Pezzulo G. Mapping the mental space of emotional concepts through kinematic measures of decision uncertainty. Philos Trans R Soc Lond B Biol Sci 2023; 378:20210367. [PMID: 36571117 PMCID: PMC9791479 DOI: 10.1098/rstb.2021.0367] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 08/09/2022] [Indexed: 12/27/2022] Open
Abstract
Emotional concepts and their mental representations have been extensively studied. Yet, some ecologically relevant aspects, such as how they are processed in ambiguous contexts (e.g., in relation to other emotional stimuli that share similar characteristics), are incompletely known. We employed a similarity judgement of emotional concepts and manipulated the contextual congruency of the responses along the two main affective dimensions of hedonic valence and physiological activation, respectively. Behavioural and kinematics (mouse-tracking) measures were combined to gather a novel 'similarity index' between emotional concepts, to derive topographical maps of their mental representations. Self-report (interoceptive sensibility, positive-negative affectivity, depression) and physiological measures (heart rate variability, HRV) have been collected to explore their possible association with emotional conceptual representation. Results indicate that emotional concepts typically associated with low arousal profit by contextual congruency, with faster responses and reduced uncertainty when contextual ambiguity decreases. The emotional maps recreate two almost orthogonal axes of valence and arousal, and the similarity measure captures the smooth boundaries between emotions. The emotional map of a subgroup of individuals with low positive affectivity reveals a narrower conceptual distribution, with variations in positive emotions and in individuals with reduced arousal (such as those with reduced HRV). Our work introduces a novel methodology to study emotional conceptual representations, bringing the behavioural dynamics of decision-making processes and choice uncertainty into the affective domain. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.
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Affiliation(s)
- Laura Barca
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
| | - Matteo Candidi
- Department of Psychology, University of Rome ‘La Sapienza’, 00185 Rome, Italy
| | - Gian Luca Lancia
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
| | - Valerio Maglianella
- Department of Psychology, University of Rome ‘La Sapienza’, 00185 Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
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24
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Catenacci Volpi N, Greaves M, Trendafilov D, Salge C, Pezzulo G, Polani D. Skilled motor control of an inverted pendulum implies low entropy of states but high entropy of actions. PLoS Comput Biol 2023; 19:e1010810. [PMID: 36608159 PMCID: PMC9851554 DOI: 10.1371/journal.pcbi.1010810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 01/19/2023] [Accepted: 12/12/2022] [Indexed: 01/07/2023] Open
Abstract
The mastery of skills, such as balancing an inverted pendulum, implies a very accurate control of movements to achieve the task goals. Traditional accounts of skilled action control that focus on either routinization or perceptual control make opposite predictions about the ways we achieve mastery. The notion of routinization emphasizes the decrease of the variance of our actions, whereas the notion of perceptual control emphasizes the decrease of the variance of the states we visit, but not of the actions we execute. Here, we studied how participants managed control tasks of varying levels of difficulty, which consisted of controlling inverted pendulums of different lengths. We used information-theoretic measures to compare the predictions of alternative accounts that focus on routinization and perceptual control, respectively. Our results indicate that the successful performance of the control task strongly correlates with the decrease of state variability and the increase of action variability. As postulated by perceptual control theory, the mastery of skilled pendulum control consists in achieving stable control of goals by flexible means.
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Affiliation(s)
- Nicola Catenacci Volpi
- Department of Computer Science, University of Hertfordshire, Hatfield, England, United Kingdom
- * E-mail:
| | - Martin Greaves
- Department of Computer Science, University of Hertfordshire, Hatfield, England, United Kingdom
| | - Dari Trendafilov
- Institute for Pervasive Computing, Johannes Kepler University, Linz, Austria
| | - Christoph Salge
- Department of Computer Science, University of Hertfordshire, Hatfield, England, United Kingdom
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Daniel Polani
- Department of Computer Science, University of Hertfordshire, Hatfield, England, United Kingdom
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25
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Pio-Lopez L, Kuchling F, Tung A, Pezzulo G, Levin M. Active inference, morphogenesis, and computational psychiatry. Front Comput Neurosci 2022; 16:988977. [PMID: 36507307 PMCID: PMC9731232 DOI: 10.3389/fncom.2022.988977] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 10/17/2022] [Indexed: 11/26/2022] Open
Abstract
Active inference is a leading theory in neuroscience that provides a simple and neuro-biologically plausible account of how action and perception are coupled in producing (Bayes) optimal behavior; and has been recently used to explain a variety of psychopathological conditions. In parallel, morphogenesis has been described as the behavior of a (non-neural) cellular collective intelligence solving problems in anatomical morphospace. In this article, we establish a link between the domains of cell biology and neuroscience, by analyzing disorders of morphogenesis as disorders of (active) inference. The aim of this article is three-fold. We want to: (i) reveal a connection between disorders of morphogenesis and disorders of active inference as apparent in psychopathological conditions; (ii) show how disorders of morphogenesis can be simulated using active inference; (iii) suggest that active inference can shed light on developmental defects or aberrant morphogenetic processes, seen as disorders of information processing, and perhaps suggesting novel intervention and repair strategies. We present four simulations illustrating application of these ideas to cellular behavior during morphogenesis. Three of the simulations show that the same forms of aberrant active inference (e.g., deficits of sensory attenuation and low sensory precision) that have been used to explain psychopathological conditions (e.g., schizophrenia and autism) also produce familiar disorders of development and morphogenesis when implemented at the level of the collective behavior of a group of cells. The fourth simulation involves two cells with too high precision, in which we show that the reduction of concentration signaling and sensitivity to the signals of other cells treats the development defect. Finally, we present the results of an experimental test of one of the model's predictions in early Xenopus laevis embryos: thioridazine (a dopamine antagonist that may reduce sensory precision in biological systems) induced developmental (anatomical) defects as predicted. The use of conceptual and empirical tools from neuroscience to understand the morphogenetic behavior of pre-neural agents offers the possibility of new approaches in regenerative medicine and evolutionary developmental biology.
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Affiliation(s)
- Léo Pio-Lopez
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Franz Kuchling
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Angela Tung
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, United States,Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, United States,*Correspondence: Michael Levin
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26
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Stoianov I, Maisto D, Pezzulo G. The hippocampal formation as a hierarchical generative model supporting generative replay and continual learning. Prog Neurobiol 2022; 217:102329. [PMID: 35870678 DOI: 10.1016/j.pneurobio.2022.102329] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 07/15/2022] [Accepted: 07/19/2022] [Indexed: 11/28/2022]
Abstract
We advance a novel computational theory of the hippocampal formation as a hierarchical generative model that organizes sequential experiences, such as rodent trajectories during spatial navigation, into coherent spatiotemporal contexts. We propose that the hippocampal generative model is endowed with inductive biases to identify individual items of experience (first hierarchical layer), organize them into sequences (second layer) and cluster them into maps (third layer). This theory entails a novel characterization of hippocampal reactivations as generative replay: the offline resampling of fictive sequences from the generative model, which supports the continual learning of multiple sequential experiences. We show that the model learns and efficiently retains multiple spatial navigation trajectories, by organizing them into spatial maps. Furthermore, the model reproduces flexible and prospective aspects of hippocampal dynamics that are challenging to explain within existing frameworks. This theory reconciles multiple roles of the hippocampal formation in map-based navigation, episodic memory and imagination.
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Affiliation(s)
- Ivilin Stoianov
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Domenico Maisto
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
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Maselli A, Lanillos P, Pezzulo G. Active inference unifies intentional and conflict-resolution imperatives of motor control. PLoS Comput Biol 2022; 18:e1010095. [PMID: 35714105 PMCID: PMC9205531 DOI: 10.1371/journal.pcbi.1010095] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 04/11/2022] [Indexed: 11/19/2022] Open
Abstract
The field of motor control has long focused on the achievement of external goals through action (e.g., reaching and grasping objects). However, recent studies in conditions of multisensory conflict, such as when a subject experiences the rubber hand illusion or embodies an avatar in virtual reality, reveal the presence of unconscious movements that are not goal-directed, but rather aim at resolving multisensory conflicts; for example, by aligning the position of a person’s arm with that of an embodied avatar. This second, conflict-resolution imperative of movement control did not emerge in classical studies of motor adaptation and online corrections, which did not allow movements to reduce the conflicts; and has been largely ignored so far in formal theories. Here, we propose a model of movement control grounded in the theory of active inference that integrates intentional and conflict-resolution imperatives. We present three simulations showing that the active inference model is able to characterize movements guided by the intention to achieve an external goal, by the necessity to resolve multisensory conflict, or both. Furthermore, our simulations reveal a fundamental difference between the (active) inference underlying intentional and conflict-resolution imperatives by showing that it is driven by two different (model and sensory) kinds of prediction errors. Finally, our simulations show that when movement is only guided by conflict resolution, the model incorrectly infers that is velocity is zero, as if it was not moving. This result suggests a novel speculative explanation for the fact that people are unaware of their subtle compensatory movements to avoid multisensory conflict. Furthermore, it can potentially help shed light on deficits of motor awareness that arise in psychopathological conditions.
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Affiliation(s)
- Antonella Maselli
- Institute of Cognitive Sciences and Technology, National Research Council (CNR), Rome, Italy
| | - Pablo Lanillos
- Donders Institute for Brain, Cognition and Behaviour, Artificial Intelligence Department, Radboud University, Nijmegen, The Netherlands
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technology, National Research Council (CNR), Rome, Italy
- * E-mail:
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Tschantz A, Barca L, Maisto D, Buckley CL, Seth AK, Pezzulo G. Simulating homeostatic, allostatic and goal-directed forms of interoceptive control using active inference. Biol Psychol 2022; 169:108266. [DOI: 10.1016/j.biopsycho.2022.108266] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 01/06/2022] [Accepted: 01/14/2022] [Indexed: 12/28/2022]
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Abstract
While machine learning techniques have been transformative in solving a range of problems, an important challenge is to understand why they arrive at the decisions they output. Some have argued that this necessitates augmenting machine intelligence with understanding such that, when queried, a machine is able to explain its behaviour (i.e., explainable AI). In this article, we address the issue of machine understanding from the perspective of active inference. This paradigm enables decision making based upon a model of how data are generated. The generative model contains those variables required to explain sensory data, and its inversion may be seen as an attempt to explain the causes of these data. Here we are interested in explanations of one's own actions. This implies a deep generative model that includes a model of the world, used to infer policies, and a higher-level model that attempts to predict which policies will be selected based upon a space of hypothetical (i.e., counterfactual) explanations-and which can subsequently be used to provide (retrospective) explanations about the policies pursued. We illustrate the construct validity of this notion of understanding in relation to human understanding by highlighting the similarities in computational architecture and the consequences of its dysfunction.
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Affiliation(s)
- Thomas Parr
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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Abstract
Introduction: Several arguments suggest that motivated reasoning (occurring when beliefs are not solely shaped by accuracy, but also by other motives such as promoting self-esteem or self-protection) is important in delusions. However, classical theories of delusion disregard the role of motivated reasoning. Thus, this role remains poorly understood.Methods: To explore the role of motivated reasoning in delusions, here we propose a computational model of delusion based on a Bayesian decision framework. This proposes that beliefs are not only evaluated based on their accuracy (as in classical theories), but also based on the cost (in terms of reward and punishment) of rejecting them.Results: The model proposes that, when the values at stake are high (as often it is the case in the context of delusion), a belief might be endorsed because rejecting it is evaluated as too costly, even if the belief is less accurate. This process might contribute to the genesis of delusions.Conclusions: Our account offers an interpretation of how motivated reasoning might shape delusions. This can inspire research on the affective and motivational processes supporting delusions in clinical conditions such as in psychosis, neurological disorders, and delusional disorder.
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Affiliation(s)
- Francesco Rigoli
- Department of Psychology, City, University of London, Northampton Square, London, UK
| | - Cristina Martinelli
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Psychology, Kingston University, Surrey, UK
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy
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Mannella F, Maggiore F, Baltieri M, Pezzulo G. Active inference through whiskers. Neural Netw 2021; 144:428-437. [PMID: 34563752 DOI: 10.1016/j.neunet.2021.08.037] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 08/29/2021] [Accepted: 08/31/2021] [Indexed: 10/20/2022]
Abstract
Rodents use whisking to probe actively their environment and to locate objects in space, hence providing a paradigmatic biological example of active sensing. Numerous studies show that the control of whisking has anticipatory aspects. For example, rodents target their whisker protraction to the distance at which they expect objects, rather than just reacting fast to contacts with unexpected objects. Here we characterize the anticipatory control of whisking in rodents as an active inference process. In this perspective, the rodent is endowed with a prior belief that it will touch something at the end of the whisker protraction, and it continuously modulates its whisking amplitude to minimize (proprioceptive and somatosensory) prediction errors arising from an unexpected whisker-object contact, or from a lack of an expected contact. We will use the model to qualitatively reproduce key empirical findings about the ways rodents modulate their whisker amplitude during exploration and the scanning of (expected or unexpected) objects. Furthermore, we will discuss how the components of active inference model can in principle map to the neurobiological circuits of rodent whisking.
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Affiliation(s)
- Francesco Mannella
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Federico Maggiore
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Manuel Baltieri
- Laboratory for Neural Computation and Adaptation, RIKEN Centre for Brain Science, Wako-shi, Japan.
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
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Pezzulo G, Zorzi M, Corbetta M. The secret life of predictive brains: what's spontaneous activity for? Trends Cogn Sci 2021; 25:730-743. [PMID: 34144895 PMCID: PMC8363551 DOI: 10.1016/j.tics.2021.05.007] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 05/14/2021] [Accepted: 05/19/2021] [Indexed: 01/23/2023]
Abstract
Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between 'generic priors' of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Roma, Italy.
| | - Marco Zorzi
- Department of General Psychology and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; IRCCS San Camillo Hospital, Venice, Italy
| | - Maurizio Corbetta
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Venetian Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Padova, Italy
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Maisto D, Barca L, Van den Bergh O, Pezzulo G. Perception and misperception of bodily symptoms from an active inference perspective: Modelling the case of panic disorder. Psychol Rev 2021; 128:690-710. [PMID: 34081507 DOI: 10.1037/rev0000290] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We advance a novel computational model that characterizes formally the ways we perceive or misperceive bodily symptoms, in the context of panic attacks. The computational model is grounded within the formal framework of Active Inference, which considers top-down prediction and attention dynamics as key to perceptual inference and action selection. In a series of simulations, we use the computational model to reproduce key facets of adaptive and maladaptive symptom perception: the ways we infer our bodily state by integrating prior information and somatic afferents; the ways we decide whether or not to attend to somatic channels; the ways we use the symptom inference to make decisions about taking or not taking a medicine; and the ways all the above processes can go awry, determining symptom misperception and ensuing maladaptive behaviors, such as hypervigilance or excessive medicine use. While recent existing theoretical treatments of psychopathological conditions focus on prediction-based perception (predictive coding), our computational model goes beyond them, in at least two ways. First, it includes action and attention selection dynamics that are disregarded in previous conceptualizations but are crucial to fully understand the phenomenology of bodily symptom perception and misperception. Second, it is a fully implemented model that generates specific (and personalized) quantitative predictions, thus going beyond previous qualitative frameworks. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
| | - Laura Barca
- Institute of Cognitive Sciences and Technologies
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35
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Yu ANC, Iodice P, Pezzulo G, Barca L. Bodily Information and Top-Down Affective Priming Jointly Affect the Processing of Fearful Faces. Front Psychol 2021; 12:625986. [PMID: 34149514 PMCID: PMC8206275 DOI: 10.3389/fpsyg.2021.625986] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 04/20/2021] [Indexed: 12/12/2022] Open
Abstract
According to embodied theories, the processing of emotions such as happiness or fear is grounded in emotion-specific perceptual, bodily, and physiological processes. Under these views, perceiving an emotional stimulus (e.g., a fearful face) re-enacts interoceptive and bodily states congruent with that emotion (e.g., increases heart rate); and in turn, interoceptive and bodily changes (e.g., increases of heart rate) influence the processing of congruent emotional content. A previous study by Pezzulo et al. (2018) provided evidence for this embodied congruence, reporting that experimentally increasing heart rate with physical exercise facilitated the processing of facial expressions congruent with that interoception (fear), but not those conveying incongruent states (disgust or neutrality). Here, we investigated whether the above (bottom-up) interoceptive manipulation and the (top-down) priming of affective content may jointly influence the processing of happy and fearful faces. The fact that happiness and fear are both associated with high heart rate but have different (positive and negative) valence permits testing the hypothesis that their processing might be facilitated by the same interoceptive manipulation (the increase of heart rate) but two opposite (positive and negative) affective primes. To test this hypothesis, we asked participants to perform a gender-categorization task of happy, fearful, and neutral faces, which were preceded by positive, negative, and neutral primes. Participants performed the same task in two sessions (after rest, with normal heart rate, or exercise, with faster heart rate) and we recorded their response times and mouse movements during the choices. We replicated the finding that when participants were in the exercise condition, they processed fearful faces faster than when they were in the rest condition. However, we did not find the same reduction in response time for happy (or neutral) faces. Furthermore, we found that when participants were in the exercise condition, they processed fearful faces faster in the presence of negative compared to positive or neutral primes; but we found no equivalent facilitation of positive (or neutral) primes during the processing of happy (or neutral) faces. While the asymmetries between the processing of fearful and happy faces require further investigation, our findings promisingly indicate that the processing of fearful faces is jointly influenced by both bottom-up interoceptive states and top-down affective primes that are congruent with the emotion.
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Affiliation(s)
- Alessandra Nicoletta Cruz Yu
- Department of Psychological Science, Pomona College, Lincoln Hall, Claremont, CA, United States.,Institute of Cognitive Neuroscience, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Pierpaolo Iodice
- Centre d'Etude des Transformations des Activités Physiques et Sportives (CETAPS), EA 3832, Faculty of Sports Sciences, University of Rouen, Mont Saint Aignan, France
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Laura Barca
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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36
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Donnarumma F, Pezzulo G. Moral decisions in the age of COVID-19: Your choices really matter. Soc Sci Humanit Open 2021; 4:100149. [PMID: 34927057 PMCID: PMC8665354 DOI: 10.1016/j.ssaho.2021.100149] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 03/27/2021] [Accepted: 04/01/2021] [Indexed: 12/21/2022]
Abstract
The moral decisions we make during this period, such as deciding whether to comply with quarantine rules, have unprecedented societal effects. We simulate the "escape from Milan" that occurred on March 7th-8th 2020, when many travelers moved from a high-risk zone (Milan) to southern regions of Italy (Campania and Lazio) immediately after an imminent lockdown was announced. Our simulations show that fewer than 50 active cases might have caused the sudden spread of the virus observed afterwards in these regions. The surprising influence of the actions of few individuals on societal dynamics challenges our cognitive expectations - as in normal conditions, collective dynamics are rather robust to the decisions of few "cheaters". This situation therefore requires novel educational strategies that increase our awareness and understanding of the unprecedented effects of our individual moral decisions.
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Affiliation(s)
- Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino Della Battaglia 44, 00185, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino Della Battaglia 44, 00185, Rome, Italy
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37
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Ciria A, Schillaci G, Pezzulo G, Hafner VV, Lara B. Predictive Processing in Cognitive Robotics: A Review. Neural Comput 2021; 33:1402-1432. [PMID: 34496394 DOI: 10.1162/neco_a_01383] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 12/31/2020] [Indexed: 11/04/2022]
Abstract
Predictive processing has become an influential framework in cognitive sciences. This framework turns the traditional view of perception upside down, claiming that the main flow of information processing is realized in a top-down, hierarchical manner. Furthermore, it aims at unifying perception, cognition, and action as a single inferential process. However, in the related literature, the predictive processing framework and its associated schemes, such as predictive coding, active inference, perceptual inference, and free-energy principle, tend to be used interchangeably. In the field of cognitive robotics, there is no clear-cut distinction on which schemes have been implemented and under which assumptions. In this letter, working definitions are set with the main aim of analyzing the state of the art in cognitive robotics research working under the predictive processing framework as well as some related nonrobotic models. The analysis suggests that, first, research in both cognitive robotics implementations and nonrobotic models needs to be extended to the study of how multiple exteroceptive modalities can be integrated into prediction error minimization schemes. Second, a relevant distinction found here is that cognitive robotics implementations tend to emphasize the learning of a generative model, while in nonrobotics models, it is almost absent. Third, despite the relevance for active inference, few cognitive robotics implementations examine the issues around control and whether it should result from the substitution of inverse models with proprioceptive predictions. Finally, limited attention has been placed on precision weighting and the tracking of prediction error dynamics. These mechanisms should help to explore more complex behaviors and tasks in cognitive robotics research under the predictive processing framework.
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Affiliation(s)
- Alejandra Ciria
- Facultad de Psicología, Universidad Nacional Autónoma de México, Mexico City, CP 04510, Mexico
| | - Guido Schillaci
- BioRobotics Institute, Scuola Superiore Sant'Anna, 34 56025 Pontedera, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, 44 00185 Rome, Italy
| | - Verena V Hafner
- Adaptive Systems Group, Department of Computer Science, Humboldt-Universität zu Berlin, D-12489, Germany
| | - Bruno Lara
- Laboratorio de Robótica Cognitiva, Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos, Cuernavaca CP 62209, Mexico
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38
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Pezzulo G, LaPalme J, Durant F, Levin M. Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190765. [PMID: 33550952 PMCID: PMC7935058 DOI: 10.1098/rstb.2019.0765] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/06/2020] [Indexed: 02/06/2023] Open
Abstract
Nervous systems' computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states-in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Joshua LaPalme
- Allen Discovery Center, Tufts University, Medford, MA, USA
| | - Fallon Durant
- Allen Discovery Center, Tufts University, Medford, MA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA
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Duvelle É, Grieves RM, Liu A, Jedidi-Ayoub S, Holeniewska J, Harris A, Nyberg N, Donnarumma F, Lefort JM, Jeffery KJ, Summerfield C, Pezzulo G, Spiers HJ. Hippocampal place cells encode global location but not connectivity in a complex space. Curr Biol 2021; 31:1221-1233.e9. [PMID: 33581073 PMCID: PMC7988036 DOI: 10.1016/j.cub.2021.01.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/22/2020] [Accepted: 01/05/2021] [Indexed: 11/20/2022]
Abstract
Flexible navigation relies on a cognitive map of space, thought to be implemented by hippocampal place cells: neurons that exhibit location-specific firing. In connected environments, optimal navigation requires keeping track of one's location and of the available connections between subspaces. We examined whether the dorsal CA1 place cells of rats encode environmental connectivity in four geometrically identical boxes arranged in a square. Rats moved between boxes by pushing saloon-type doors that could be locked in one or both directions. Although rats demonstrated knowledge of environmental connectivity, their place cells did not respond to connectivity changes, nor did they represent doorways differently from other locations. Place cells coded location in a global reference frame, with a different map for each box and minimal repetitive fields despite the repetitive geometry. These results suggest that CA1 place cells provide a spatial map that does not explicitly include connectivity.
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Affiliation(s)
- Éléonore Duvelle
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Roddy M Grieves
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Anyi Liu
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Selim Jedidi-Ayoub
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Joanna Holeniewska
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Adam Harris
- Department of Experimental Psychology, University of Oxford, OX2 6BW Oxford, UK
| | - Nils Nyberg
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino d. Battaglia 44, 00185 Rome, Italy
| | - Julie M Lefort
- University College London, Department of Cell and Developmental Biology, London, UK
| | - Kate J Jeffery
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | | | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino d. Battaglia 44, 00185 Rome, Italy
| | - Hugo J Spiers
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK.
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Pezzulo G, Roche L, Saint-Bauzel L. Haptic communication optimises joint decisions and affords implicit confidence sharing. Sci Rep 2021; 11:1051. [PMID: 33441715 PMCID: PMC7807057 DOI: 10.1038/s41598-020-80041-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 11/13/2020] [Indexed: 11/21/2022] Open
Abstract
Group decisions can outperform the choices of the best individual group members. Previous research suggested that optimal group decisions require individuals to communicate explicitly (e.g., verbally) their confidence levels. Our study addresses the untested hypothesis that implicit communication using a sensorimotor channel—haptic coupling—may afford optimal group decisions, too. We report that haptically coupled dyads solve a perceptual discrimination task more accurately than their best individual members; and five times faster than dyads using explicit communication. Furthermore, our computational analyses indicate that the haptic channel affords implicit confidence sharing. We found that dyads take leadership over the choice and communicate their confidence in it by modulating both the timing and the force of their movements. Our findings may pave the way to negotiation technologies using fast sensorimotor communication to solve problems in groups.
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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.
| | - Lucas Roche
- Sorbonne Université - ISIR (Institute of Intelligent Systems and Robotics), 75005, Paris, France
| | - Ludovic Saint-Bauzel
- Sorbonne Université - ISIR (Institute of Intelligent Systems and Robotics), 75005, Paris, France
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Donnarumma F, Prevete R, Maisto D, Fuscone S, Irvine EM, van der Meer MAA, Kemere C, Pezzulo G. A framework to identify structured behavioral patterns within rodent spatial trajectories. Sci Rep 2021; 11:468. [PMID: 33432100 PMCID: PMC7801653 DOI: 10.1038/s41598-020-79744-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 11/10/2020] [Indexed: 11/09/2022] Open
Abstract
Animal behavior is highly structured. Yet, structured behavioral patterns-or "statistical ethograms"-are not immediately apparent from the full spatiotemporal data that behavioral scientists usually collect. Here, we introduce a framework to quantitatively characterize rodent behavior during spatial (e.g., maze) navigation, in terms of movement building blocks or motor primitives. The hypothesis that we pursue is that rodent behavior is characterized by a small number of motor primitives, which are combined over time to produce open-ended movements. We assume motor primitives to be organized in terms of two sparsity principles: each movement is controlled using a limited subset of motor primitives (sparse superposition) and each primitive is active only for time-limited, time-contiguous portions of movements (sparse activity). We formalize this hypothesis using a sparse dictionary learning method, which we use to extract motor primitives from rodent position and velocity data collected during spatial navigation, and successively to reconstruct past trajectories and predict novel ones. Three main results validate our approach. First, rodent behavioral trajectories are robustly reconstructed from incomplete data, performing better than approaches based on standard dimensionality reduction methods, such as principal component analysis, or single sparsity. Second, the motor primitives extracted during one experimental session generalize and afford the accurate reconstruction of rodent behavior across successive experimental sessions in the same or in modified mazes. Third, in our approach the number of motor primitives associated with each maze correlates with independent measures of maze complexity, hence showing that our formalism is sensitive to essential aspects of task structure. The framework introduced here can be used by behavioral scientists and neuroscientists as an aid for behavioral and neural data analysis. Indeed, the extracted motor primitives enable the quantitative characterization of the complexity and similarity between different mazes and behavioral patterns across multiple trials (i.e., habit formation). We provide example uses of this computational framework, showing how it can be used to identify behavioural effects of maze complexity, analyze stereotyped behavior, classify behavioral choices and predict place and grid cell displacement in novel environments.
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Affiliation(s)
- Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via San Martino della Battaglia 44, 00185, Rome, Italy
| | - Roberto Prevete
- Department of Electric Engineering and Information Technologies (DIETI), Università degli Studi di Napoli Federico II, Naples, Italy
| | - Domenico Maisto
- Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), Via Pietro Castellino 111, 80131, Naples, Italy
| | | | - Emily M Irvine
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | | | - Caleb Kemere
- Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via San Martino della Battaglia 44, 00185, Rome, Italy.
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Pezzulo G. Disorders of morphogenesis as disorders of inference: Comment on "Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems" by Michael Levin et al. Phys Life Rev 2020; 33:112-114. [PMID: 32591312 DOI: 10.1016/j.plrev.2020.06.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 06/12/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino della Battaglia 44, 00185 Rome, Italy.
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Maranesi M, Bruni S, Livi A, Donnarumma F, Pezzulo G, Bonini L. Author Correction: Differential neural dynamics underlying pragmatic and semantic affordance processing in macaque ventral premotor cortex. Sci Rep 2020; 10:5365. [PMID: 32193451 PMCID: PMC7081309 DOI: 10.1038/s41598-020-62216-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Monica Maranesi
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy.
| | - Stefania Bruni
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy.,Center for Neural Science, New York University, New York, NY, United States of America
| | - Alessandro Livi
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy.,Department of Neuroscience, Washington University, St. Louis, Missouri, USA
| | - Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino della Battaglia 44, 00185, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino della Battaglia 44, 00185, Rome, Italy
| | - Luca Bonini
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy
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Abstract
A popular distinction in the human and animal learning literature is between deliberate (or willed) and habitual (or automatic) modes of control. Extensive evidence indicates that, after sufficient learning, living organisms develop behavioural habits that permit them saving computational resources. Furthermore, humans and other animals are able to transfer control from deliberate to habitual modes (and vice versa), trading off efficiently flexibility and parsimony - an ability that is currently unparalleled by artificial control systems. Here, we discuss a computational implementation of habit formation, and the transfer of control from deliberate to habitual modes (and vice versa) within Active Inference: a computational framework that merges aspects of cybernetic theory and of Bayesian inference. To model habit formation, we endow an Active Inference agent with a mechanism to "cache" (or memorize) policy probabilities from previous trials, and reuse them to skip - in part or in full - the inferential steps of deliberative processing. We exploit the fact that the relative quality of policies, conditioned upon hidden states, is constant over trials; provided that contingencies and prior preferences do not change. This means the only quantity that can change policy selection is the prior distribution over the initial state - where this prior is based upon the posterior beliefs from previous trials. Thus, an agent that caches the quality (or the probability) of policies can safely reuse cached values to save on cognitive and computational resources - unless contingencies change. Our simulations illustrate the computational benefits, but also the limits, of three caching schemes under Active Inference. They suggest that key aspects of habitual behaviour - such as perseveration - can be explained in terms of caching policy probabilities. Furthermore, they suggest that there may be many kinds (or stages) of habitual behaviour, each associated with a different caching scheme; for example, caching associated or not associated with contextual estimation. These schemes are more or less impervious to contextual and contingency changes.
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Affiliation(s)
- D Maisto
- Institute for High Performance Computing and Networking, National Research Council, Via P. Castellino, 111, Naples 80131, Italy
| | - K Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK
| | - G Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via San Martino della Battaglia 44, Rome 00185, Italy
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Maranesi M, Bruni S, Livi A, Donnarumma F, Pezzulo G, Bonini L. Differential neural dynamics underling pragmatic and semantic affordance processing in macaque ventral premotor cortex. Sci Rep 2019; 9:11700. [PMID: 31406219 PMCID: PMC6691108 DOI: 10.1038/s41598-019-48216-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 07/29/2019] [Indexed: 12/14/2022] Open
Abstract
Premotor neurons play a fundamental role in transforming physical properties of observed objects, such as size and shape, into motor plans for grasping them, hence contributing to “pragmatic” affordance processing. Premotor neurons can also contribute to “semantic” affordance processing, as they can discharge differently even to pragmatically identical objects depending on their behavioural relevance for the observer (i.e. edible or inedible objects). Here, we compared the response of monkey ventral premotor area F5 neurons tested during pragmatic (PT) or semantic (ST) visuomotor tasks. Object presentation responses in ST showed shorter latency and lower object selectivity than in PT. Furthermore, we found a difference between a transient representation of semantic affordances and a sustained representation of pragmatic affordances at both the single neuron and population level. Indeed, responses in ST returned to baseline within 0.5 s whereas in PT they showed the typical sustained visual-to-motor activity during Go trials. In contrast, during No-go trials, the time course of pragmatic and semantic information processing was similar. These findings suggest that premotor cortex generates different dynamics depending on pragmatic and semantic information provided by the context in which the to-be-grasped object is presented.
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Affiliation(s)
- Monica Maranesi
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy.
| | - Stefania Bruni
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy.,Center for Neural Science, New York University, New York, NY, United States of America
| | - Alessandro Livi
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy.,Department of Neuroscience, Washington University, St. Louis, Missouri, USA
| | - Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino della Battaglia 44, 00185, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino della Battaglia 44, 00185, Rome, Italy
| | - Luca Bonini
- Department of Medicine and Surgery, University of Parma, via Volturno 39, 43125, Parma, Italy
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Iodice P, Porciello G, Bufalari I, Barca L, Pezzulo G. An interoceptive illusion of effort induced by false heart-rate feedback. Proc Natl Acad Sci U S A 2019; 116:13897-13902. [PMID: 31235576 PMCID: PMC6628799 DOI: 10.1073/pnas.1821032116] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Interoception, or the sense of the internal state of the body, is key to the adaptive regulation of our physiological needs. Recent theories contextualize interception within a predictive coding framework, according to which the brain both estimates and controls homeostatic and physiological variables, such as hunger, thirst, and effort levels, by orchestrating sensory, proprioceptive, and interoceptive signals from inside the body. This framework suggests that providing false interoceptive feedback may induce misperceptions of physiological variables, or "interoceptive illusions." Here we ask whether it is possible to produce an illusory perception of effort by giving participants false acoustic feedback about their heart-rate frequency during an effortful cycling task. We found that participants reported higher levels of perceived effort when their heart-rate feedback was faster compared with when they cycled at the same level of intensity with a veridical feedback. However, participants did not report lower effort when their heart-rate feedback was slower, which is reassuring, given that failing to notice one's own effort is dangerous in ecologically valid conditions. Our results demonstrate that false cardiac feedback can produce interoceptive illusions. Furthermore, our results pave the way for novel experimental manipulations that use illusions to study interoceptive processing.
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Affiliation(s)
- Pierpaolo Iodice
- Centre d'Etudes des Transformations des Activités Physiques et Sportives, University of Normandy, 76821 Mont Saint Aignan, France
| | - Giuseppina Porciello
- Dipartimento di Psicologia, Sapienza, Università degli studi di Roma, 00185, Rome, Italy
- Laboratorio di Neuroscienze Sociali, Fondazione Santa Lucia, 00142, Rome, Italy
| | - Ilaria Bufalari
- Laboratorio di Neuroscienze Sociali, Fondazione Santa Lucia, 00142, Rome, Italy
- Dipartimento di di Psicologia dei Processi di Sviluppo e Socializzazione, Sapienza, Università degli studi di Roma, 00185, Rome, Italy
| | - Laura Barca
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185, Rome, Italy
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Borghi AM, Barca L, Binkofski F, Castelfranchi C, Pezzulo G, Tummolini L. Words as social tools: Language, sociality and inner grounding in abstract concepts. Phys Life Rev 2019; 29:120-153. [DOI: 10.1016/j.plrev.2018.12.001] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Revised: 12/05/2018] [Accepted: 12/05/2018] [Indexed: 11/24/2022]
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50
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Borghi AM, Barca L, Binkofski F, Castelfranchi C, Pezzulo G, Tummolini L. Words as social tools: Flexibility, situatedness, language and sociality in abstract concepts. Phys Life Rev 2019; 29:178-184. [DOI: 10.1016/j.plrev.2019.06.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 06/25/2019] [Indexed: 10/26/2022]
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