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Di Paolo LD, White B, Guénin-Carlut A, Constant A, Clark A. Active inference goes to school: the importance of active learning in the age of large language models. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230148. [PMID: 39155715 DOI: 10.1098/rstb.2023.0148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/16/2023] [Accepted: 01/23/2024] [Indexed: 08/20/2024] Open
Abstract
Human learning essentially involves embodied interactions with the material world. But our worlds now include increasing numbers of powerful and (apparently) disembodied generative artificial intelligence (AI). In what follows we ask how best to understand these new (somewhat 'alien', because of their disembodied nature) resources and how to incorporate them in our educational practices. We focus on methodologies that encourage exploration and embodied interactions with 'prepared' material environments, such as the carefully organized settings of Montessori education. Using the active inference framework, we approach our questions by thinking about human learning as epistemic foraging and prediction error minimization. We end by arguing that generative AI should figure naturally as new elements in prepared learning environments by facilitating sequences of precise prediction error enabling trajectories of self-correction. In these ways, we anticipate new synergies between (apparently) disembodied and (essentially) embodied forms of intelligence. This article is part of the theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.
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Affiliation(s)
- Laura Desirèe Di Paolo
- Department of Engineering and Informatics, The University of Sussex , Brighton, UK
- School of Psychology, Children & Technology Lab, The University of Sussex , Falmer (Brighton), UK
| | - Ben White
- Department of Philosophy, The University of Sussex , Sussex, UK
| | - Avel Guénin-Carlut
- Department of Engineering and Informatics, The University of Sussex , Brighton, UK
| | - Axel Constant
- Department of Engineering and Informatics, The University of Sussex , Brighton, UK
| | - Andy Clark
- Department of Engineering and Informatics, The University of Sussex , Brighton, UK
- Department of Philosophy, The University of Sussex , Sussex, UK
- Department of Philosophy, Macquarie University , Sydney, New South Wales, Australia
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2
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Heng JG, Zhang J, Bonetti L, Lim WPH, Vuust P, Agres K, Chen SHA. Understanding music and aging through the lens of Bayesian inference. Neurosci Biobehav Rev 2024; 163:105768. [PMID: 38908730 DOI: 10.1016/j.neubiorev.2024.105768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 06/05/2024] [Accepted: 06/10/2024] [Indexed: 06/24/2024]
Abstract
Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.
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Affiliation(s)
- Jiamin Gladys Heng
- School of Computer Science and Engineering, Nanyang Technological University, Singapore.
| | - Jiayi Zhang
- Interdisciplinary Graduate Program, Nanyang Technological University, Singapore; School of Social Sciences, Nanyang Technological University, Singapore; Centre for Research and Development in Learning, Nanyang Technological University, Singapore
| | - Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus, Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom; Department of Psychology, University of Bologna, Italy
| | | | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus, Aalborg, Denmark
| | - Kat Agres
- Centre for Music and Health, National University of Singapore, Singapore; Yong Siew Toh Conservatory of Music, National University of Singapore, Singapore
| | - Shen-Hsing Annabel Chen
- School of Social Sciences, Nanyang Technological University, Singapore; Centre for Research and Development in Learning, Nanyang Technological University, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; National Institute of Education, Nanyang Technological University, Singapore.
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3
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Marvan T, Phillips WA. Cellular mechanisms of cooperative context-sensitive predictive inference. CURRENT RESEARCH IN NEUROBIOLOGY 2024; 6:100129. [PMID: 38665363 PMCID: PMC11043869 DOI: 10.1016/j.crneur.2024.100129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 02/14/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
We argue that prediction success maximization is a basic objective of cognition and cortex, that it is compatible with but distinct from prediction error minimization, that neither objective requires subtractive coding, that there is clear neurobiological evidence for the amplification of predicted signals, and that we are unconvinced by evidence proposed in support of subtractive coding. We outline recent discoveries showing that pyramidal cells on which our cognitive capabilities depend usually transmit information about input to their basal dendrites and amplify that transmission when input to their distal apical dendrites provides a context that agrees with the feedforward basal input in that both are depolarizing, i.e., both are excitatory rather than inhibitory. Though these intracellular discoveries require a level of technical expertise that is beyond the current abilities of most neuroscience labs, they are not controversial and acclaimed as groundbreaking. We note that this cellular cooperative context-sensitivity greatly enhances the cognitive capabilities of the mammalian neocortex, and that much remains to be discovered concerning its evolution, development, and pathology.
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Affiliation(s)
- Tomáš Marvan
- Institute of Philosophy, Czech Academy of Sciences (CAS), Czech Republic
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4
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Fouragnan EF, Hosking B, Cheung Y, Prakash B, Rushworth M, Sel A. Timing along the cardiac cycle modulates neural signals of reward-based learning. Nat Commun 2024; 15:2976. [PMID: 38582905 PMCID: PMC10998831 DOI: 10.1038/s41467-024-46921-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 03/14/2024] [Indexed: 04/08/2024] Open
Abstract
Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations - absolute and signed prediction errors. We combined machine learning techniques with electroencephalography with both simple, direct indices of task performance and computational model-derived indices of learning. Our results demonstrate that just as people are more sensitive to low magnitude, near-threshold sensory stimuli in certain cardiac phases, so are they more sensitive to low magnitude absolute prediction errors in the same cycles. However, this occurs even when the low magnitude prediction errors are associated with clearly suprathreshold sensory events. In addition, participants exhibiting stronger differences in their prediction error representations between cardiac cycles exhibited higher learning rates and greater task accuracy.
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Affiliation(s)
- Elsa F Fouragnan
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK.
- Brain Research Imaging Centre (BRIC), Faculty of Health, University of Plymouth, Plymouth, PL6 8BU, UK.
- School of Psychology, Faculty of Health, University of Plymouth, Plymouth, PL4 8AA, UK.
| | - Billy Hosking
- Brain Research Imaging Centre (BRIC), Faculty of Health, University of Plymouth, Plymouth, PL6 8BU, UK
- School of Psychology, Faculty of Health, University of Plymouth, Plymouth, PL4 8AA, UK
| | - Yin Cheung
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
| | - Brooke Prakash
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
| | - Matthew Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
| | - Alejandra Sel
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
- Centre for Brain Science, Department of Psychology, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK
- Essex ESNEFT Psychological Research Unit for Behaviour, Health and Wellbeing, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK
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5
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Miller M, White B, Scrivner C. Surfing uncertainty with screams: predictive processing, error dynamics and horror films. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220425. [PMID: 38104602 PMCID: PMC10725765 DOI: 10.1098/rstb.2022.0425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 10/08/2023] [Indexed: 12/19/2023] Open
Abstract
Despite tremendous efforts in psychology, neuroscience and media and cultural studies, it is still something of a mystery why humans are attracted to fictional content that is horrifying, disgusting or otherwise aversive. While the psychological benefits of horror films, stories, video games, etc. has recently been demonstrated empirically, current theories emphasizing the negative and positive consequences of this engagement often contradict one another. Here, we suggest the predictive processing framework may provide a unifying account of horror content engagement that provides clear and testable hypotheses, and explains why a 'sweet spot' of fear and fun exists in horror entertainment. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.
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Affiliation(s)
- Mark Miller
- Centre for Consciousness and Contemplative Studies, Monash University, Clayton, Victoria 3800, Australia
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada M5R 0A3
| | - Ben White
- School of Media, Arts and Humanities, University of Sussex, Brighton, BN1 9RH, UK
| | - Coltan Scrivner
- Recreational Fear Lab, Aarhus University, 8000 Aarhus, Denmark
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6
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Friston K, Da Costa L, Sakthivadivel DAR, Heins C, Pavliotis GA, Ramstead M, Parr T. Path integrals, particular kinds, and strange things. Phys Life Rev 2023; 47:35-62. [PMID: 37703703 DOI: 10.1016/j.plrev.2023.08.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 08/22/2023] [Indexed: 09/15/2023]
Abstract
This paper describes a path integral formulation of the free energy principle. The ensuing account expresses the paths or trajectories that a particle takes as it evolves over time. The main results are a method or principle of least action that can be used to emulate the behaviour of particles in open exchange with their external milieu. Particles are defined by a particular partition, in which internal states are individuated from external states by active and sensory blanket states. The variational principle at hand allows one to interpret internal dynamics-of certain kinds of particles-as inferring external states that are hidden behind blanket states. We consider different kinds of particles, and to what extent they can be imbued with an elementary form of inference or sentience. Specifically, we consider the distinction between dissipative and conservative particles, inert and active particles and, finally, ordinary and strange particles. Strange particles can be described as inferring their own actions, endowing them with apparent autonomy or agency. In short-of the kinds of particles afforded by a particular partition-strange kinds may be apt for describing sentient behaviour.
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Affiliation(s)
- Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK; VERSES Research Lab, Los Angeles, CA, USA.
| | - Lancelot Da Costa
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK; Department of Mathematics, Imperial College London, London SW7 2AZ, UK; VERSES Research Lab, Los Angeles, CA, USA.
| | - Dalton A R Sakthivadivel
- VERSES Research Lab, Los Angeles, CA, USA; Department of Mathematics, Stony Brook University, Stony Brook, NY, USA; Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY, USA.
| | - Conor Heins
- VERSES Research Lab, Los Angeles, CA, USA; Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz D-78457, Germany; Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz D-78457, Germany.
| | | | - Maxwell Ramstead
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK; VERSES Research Lab, Los Angeles, CA, USA.
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK.
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7
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Ghaneirad E, Borgolte A, Sinke C, Čuš A, Bleich S, Szycik GR. The effect of multisensory semantic congruency on unisensory object recognition in schizophrenia. Front Psychiatry 2023; 14:1246879. [PMID: 38025441 PMCID: PMC10646423 DOI: 10.3389/fpsyt.2023.1246879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Multisensory, as opposed to unisensory processing of stimuli, has been found to enhance the performance (e.g., reaction time, accuracy, and discrimination) of healthy individuals across various tasks. However, this enhancement is not as pronounced in patients with schizophrenia (SZ), indicating impaired multisensory integration (MSI) in these individuals. To the best of our knowledge, no study has yet investigated the impact of MSI deficits in the context of working memory, a domain highly reliant on multisensory processing and substantially impaired in schizophrenia. To address this research gap, we employed two adopted versions of the continuous object recognition task to investigate the effect of single-trail multisensory encoding on subsequent object recognition in 21 schizophrenia patients and 21 healthy controls (HC). Participants were tasked with discriminating between initial and repeated presentations. For the initial presentations, half of the stimuli were audiovisual pairings, while the other half were presented unimodal. The task-relevant stimuli were then presented a second time in a unisensory manner (either auditory stimuli in the auditory task or visual stimuli in the visual task). To explore the impact of semantic context on multisensory encoding, half of the audiovisual pairings were selected to be semantically congruent, while the remaining pairs were not semantically related to each other. Consistent with prior studies, our findings demonstrated that the impact of single-trial multisensory presentation during encoding remains discernible during subsequent object recognition. This influence could be distinguished based on the semantic congruity between the auditory and visual stimuli presented during the encoding. This effect was more robust in the auditory task. In the auditory task, when congruent multisensory pairings were encoded, both participant groups demonstrated a multisensory facilitation effect. This effect resulted in improved accuracy and RT performance. Regarding incongruent audiovisual encoding, as expected, HC did not demonstrate an evident multisensory facilitation effect on memory performance. In contrast, SZs exhibited an atypically accelerated reaction time during the subsequent auditory object recognition. Based on the predictive coding model we propose that this observed deviations indicate a reduced semantic modulatory effect and anomalous predictive errors signaling, particularly in the context of conflicting cross-modal sensory inputs in SZ.
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Affiliation(s)
- Erfan Ghaneirad
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Anna Borgolte
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Christopher Sinke
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Division of Clinical Psychology and Sexual Medicine, Hannover Medical School, Hannover, Germany
| | - Anja Čuš
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Stefan Bleich
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
- Center for Systems Neuroscience, University of Veterinary Medicine, Hanover, Germany
| | - Gregor R. Szycik
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
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8
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Sprevak M, Smith R. An Introduction to Predictive Processing Models of Perception and Decision-Making. Top Cogn Sci 2023. [PMID: 37899002 DOI: 10.1111/tops.12704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 08/30/2023] [Accepted: 10/06/2023] [Indexed: 10/31/2023]
Abstract
The predictive processing framework includes a broad set of ideas, which might be articulated and developed in a variety of ways, concerning how the brain may leverage predictive models when implementing perception, cognition, decision-making, and motor control. This article provides an up-to-date introduction to the two most influential theories within this framework: predictive coding and active inference. The first half of the paper (Sections 2-5) reviews the evolution of predictive coding, from early ideas about efficient coding in the visual system to a more general model encompassing perception, cognition, and motor control. The theory is characterized in terms of the claims it makes at Marr's computational, algorithmic, and implementation levels of description, and the conceptual and mathematical connections between predictive coding, Bayesian inference, and variational free energy (a quantity jointly evaluating model accuracy and complexity) are explored. The second half of the paper (Sections 6-8) turns to recent theories of active inference. Like predictive coding, active inference models assume that perceptual and learning processes minimize variational free energy as a means of approximating Bayesian inference in a biologically plausible manner. However, these models focus primarily on planning and decision-making processes that predictive coding models were not developed to address. Under active inference, an agent evaluates potential plans (action sequences) based on their expected free energy (a quantity that combines anticipated reward and information gain). The agent is assumed to represent the world as a partially observable Markov decision process with discrete time and discrete states. Current research applications of active inference models are described, including a range of simulation work, as well as studies fitting models to empirical data. The paper concludes by considering future research directions that will be important for further development of both models.
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Affiliation(s)
- Mark Sprevak
- School of Philosophy, Psychology and Language Sciences, University of Edinburgh
| | - Ryan Smith
- Laureate Institute for Brain Research, Tulsa, Oklahoma
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9
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Brouillet D, Friston K. Relative fluency (unfelt vs felt) in active inference. Conscious Cogn 2023; 115:103579. [PMID: 37776599 DOI: 10.1016/j.concog.2023.103579] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 09/07/2023] [Accepted: 09/16/2023] [Indexed: 10/02/2023]
Abstract
For a growing number of researchers, it is now accepted that the brain is a predictive organ that predicts the content of the sensorium and crucially the precision of-or confidence in-its own predictions. In order to predict the precision of its predictions, the brain has to infer the reliability of its own beliefs. This means that our brains have to recognise the precision of their predictions or, at least, their accuracy. In this paper, we argue that fluency is product of this recognition process. In short, to recognise fluency is to infer that we have a precise 'grip' on the unfolding processes that generate our sensations. More specifically, we propose that it is changes in fluency - from unfelt to felt - that are both recognised and realised when updating predictions about precision. Unfelt fluency orients attention to unpredicted sensations, while felt fluency supervenes on-and contextualises-unfelt fluency; thereby rendering certain attentional processes, phenomenologically opaque. As such, fluency underwrites the precision we place in our predictions and therefore acts upon our perceptual inferences. Hence, the causes of conscious subjective inference have unconscious perceptual precursors.
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Affiliation(s)
- Denis Brouillet
- University Paul Valéry-Montpellier-France, EPSYLON, France; University Paris Nanterre, LICAE, France.
| | - Karl Friston
- Queen Square Institute of Neurology, University College, London, United Kingdom; Wellcome Centre for Human Neuroimaging, London, United Kingdom
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10
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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: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [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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11
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Pagnini F, Barbiani D, Cavalera C, Volpato E, Grosso F, Minazzi GA, Vailati Riboni F, Graziano F, Di Tella S, Manzoni GM, Silveri MC, Riva G, Phillips D. Placebo and Nocebo Effects as Bayesian-Brain Phenomena: The Overlooked Role of Likelihood and Attention. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2023; 18:1217-1229. [PMID: 36656800 DOI: 10.1177/17456916221141383] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
The Bayesian-brain framework applied to placebo responses and other mind-body interactions suggests that the effects on the body result from the interaction between priors, such as expectations and learning, and likelihood, such as somatosensorial information. Significant research in this area focuses on the role of the priors, but the relevance of the likelihood has been surprisingly overlooked. One way of manipulating the relevance of the likelihood is by paying attention to sensorial information. We suggest that attention can influence both precision and position (i.e., the relative distance from the priors) of the likelihood by focusing on specific components of the somatosensorial information. Two forms of attention seem particularly relevant in this framework: mindful attention and selective attention. Attention has the potential to be considered a "major player" in placebo/nocebo research, together with expectations and learning. In terms of application, relying on attentional strategies as "amplifiers" or "silencers" of sensorial information could lead to an active involvement of individuals in shaping their care process and health. In this contribution, we discuss the theoretical implications of these intuitions with the aim to provide a comprehensive framework that includes Bayesian brain, placebo/nocebo effects, and the role of attention in mind-body interactions.
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Affiliation(s)
| | - Diletta Barbiani
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona
| | - Cesare Cavalera
- Department of Psychology, Università Cattolica del Sacro Cuore
| | - Eleonora Volpato
- Department of Psychology, Università Cattolica del Sacro Cuore
- IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy
| | | | | | | | - Francesca Graziano
- Bicocca Bioinformatics Biostatistics and Bioimaging B4 Center, University of Milano-Bicocca
- School of Medicine and Surgery, University of Milano
| | - Sonia Di Tella
- Department of Psychology, Università Cattolica del Sacro Cuore
| | | | | | - Giuseppe Riva
- Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano IRCCS
- Humane Technology Lab., Catholic University of Milan
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12
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From fear of falling to choking under pressure: A predictive processing perspective of disrupted motor control under anxiety. Neurosci Biobehav Rev 2023; 148:105115. [PMID: 36906243 DOI: 10.1016/j.neubiorev.2023.105115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 03/11/2023]
Abstract
Under the Predictive Processing Framework, perception is guided by internal models that map the probabilistic relationship between sensory states and their causes. Predictive processing has contributed to a new understanding of both emotional states and motor control but is yet to be fully applied to their interaction during the breakdown of motor movements under heightened anxiety or threat. We bring together literature on anxiety and motor control to propose that predictive processing provides a unifying principle for understanding motor breakdowns as a disruption to the neuromodulatory control mechanisms that regulate the interactions of top-down predictions and bottom-up sensory signals. We illustrate this account using examples from disrupted balance and gait in populations who are anxious/fearful of falling, as well as 'choking' in elite sport. This approach can explain both rigid and inflexible movement strategies, as well as highly variable and imprecise action and conscious movement processing, and may also unite the apparently opposing self-focus and distraction approaches to choking. We generate predictions to guide future work and propose practical recommendations.
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13
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Friston K. Computational psychiatry: from synapses to sentience. Mol Psychiatry 2023; 28:256-268. [PMID: 36056173 PMCID: PMC7614021 DOI: 10.1038/s41380-022-01743-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 08/08/2022] [Accepted: 08/11/2022] [Indexed: 01/09/2023]
Abstract
This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.
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Affiliation(s)
- Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, WC1N 3AR, UK.
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14
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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] [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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15
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Anil Meera A, Novicky F, Parr T, Friston K, Lanillos P, Sajid N. Reclaiming saliency: Rhythmic precision-modulated action and perception. Front Neurorobot 2022; 16:896229. [PMID: 35966370 PMCID: PMC9368584 DOI: 10.3389/fnbot.2022.896229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Computational models of visual attention in artificial intelligence and robotics have been inspired by the concept of a saliency map. These models account for the mutual information between the (current) visual information and its estimated causes. However, they fail to consider the circular causality between perception and action. In other words, they do not consider where to sample next, given current beliefs. Here, we reclaim salience as an active inference process that relies on two basic principles: uncertainty minimization and rhythmic scheduling. For this, we make a distinction between attention and salience. Briefly, we associate attention with precision control, i.e., the confidence with which beliefs can be updated given sampled sensory data, and salience with uncertainty minimization that underwrites the selection of future sensory data. Using this, we propose a new account of attention based on rhythmic precision-modulation and discuss its potential in robotics, providing numerical experiments that showcase its advantages for state and noise estimation, system identification and action selection for informative path planning.
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Affiliation(s)
- Ajith Anil Meera
- Department of Cognitive Robotics, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Delft, Netherlands
- *Correspondence: Ajith Anil Meera
| | - Filip Novicky
- Department of Neurophysiology, Donders Institute for Brain Cognition and Behavior, Radboud University, Nijmegen, Netherlands
- Filip Novicky
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Pablo Lanillos
- Department of Artificial Intelligence, Donders Institute for Brain Cognition and Behavior, Radboud University, Nijmegen, Netherlands
| | - Noor Sajid
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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16
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Andersen BP. Autistic-Like Traits and Positive Schizotypy as Diametric Specializations of the Predictive Mind. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2022; 17:1653-1672. [PMID: 35816687 DOI: 10.1177/17456916221075252] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
According to the predictive-processing framework, only prediction errors (rather than all sensory inputs) are processed by an organism's perceptual system. Prediction errors can be weighted such that errors from more reliable sources will be more influential in updating prior beliefs. It has previously been argued that autism-spectrum conditions can be understood as resulting from a predictive-processing mechanism in which an inflexibly high weight is given to sensory-prediction errors that results in overfitting their predictive models to the world. Deficits in executive functioning, theory of mind, and central coherence are all argued to flow naturally from this core underlying mechanism. The diametric model of autism and psychosis suggests a simple extension of this hypothesis. If people on the autism spectrum give an inflexibly high weight to sensory input, could it be that people with a predisposition to psychosis (i.e., people high in positive schizotypy) give an inflexibly low weight to sensory input? In this article I argue that evidence strongly supports this hypothesis. An inflexibly low weight given to sensory input can explain such disparate features of positive schizotypy as increased exploratory behavior, apophenia, hyper theory of mind, hyperactive imagination, attentional differences, and having idiosyncratic worldviews.
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17
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From representations in predictive processing to degrees of representational features. Minds Mach (Dordr) 2022. [DOI: 10.1007/s11023-022-09599-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
AbstractWhilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual account of two features of structural representations: structural similarity and decoupling. We argue that structural similarity can be analysed in terms of two dimensions: number of preserved relations and state space granularity. Both dimensions can take on different values and hence render structural similarity gradual. We further argue that decoupling is gradual in two ways. First, we show that different brain areas are involved in decoupled cognitive processes to a greater or lesser degree depending on the cause (internal or external) of their activity. Second, and more importantly, we show that the degree of decoupling can be further regulated in some brain areas through precision weighting of prediction error. We lastly argue that gradation of decoupling (via precision weighting) and gradation of structural similarity (via state space granularity) are conducive to behavioural success.
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Stress and its sequelae: An active inference account of the etiological pathway from allostatic overload to depression. Neurosci Biobehav Rev 2022; 135:104590. [DOI: 10.1016/j.neubiorev.2022.104590] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 01/06/2022] [Accepted: 02/16/2022] [Indexed: 12/28/2022]
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Hong CCH, Fallon JH, Friston KJ. fMRI Evidence for Default Mode Network Deactivation Associated with Rapid Eye Movements in Sleep. Brain Sci 2021; 11:brainsci11111528. [PMID: 34827529 PMCID: PMC8615877 DOI: 10.3390/brainsci11111528] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/12/2021] [Accepted: 11/16/2021] [Indexed: 11/25/2022] Open
Abstract
System-specific brain responses—time-locked to rapid eye movements (REMs) in sleep—are characteristically widespread, with robust and clear activation in the primary visual cortex and other structures involved in multisensory integration. This pattern suggests that REMs underwrite hierarchical processing of visual information in a time-locked manner, where REMs index the generation and scanning of virtual-world models, through multisensory integration in dreaming—as in awake states. Default mode network (DMN) activity increases during rest and reduces during various tasks including visual perception. The implicit anticorrelation between the DMN and task-positive network (TPN)—that persists in REM sleep—prompted us to focus on DMN responses to temporally-precise REM events. We timed REMs during sleep from the video recordings and quantified the neural correlates of REMs—using functional MRI (fMRI)—in 24 independent studies of 11 healthy participants. A reanalysis of these data revealed that the cortical areas exempt from widespread REM-locked brain activation were restricted to the DMN. Furthermore, our analysis revealed a modest temporally-precise REM-locked decrease—phasic deactivation—in key DMN nodes, in a subset of independent studies. These results are consistent with hierarchical predictive coding; namely, permissive deactivation of DMN at the top of the hierarchy (leading to the widespread cortical activation at lower levels; especially the primary visual cortex). Additional findings indicate REM-locked cerebral vasodilation and suggest putative mechanisms for dream forgetting.
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Affiliation(s)
- Charles Chong-Hwa Hong
- Patuxent Institution, Correctional Mental Health Center—Jessup, Jessup, MD 20794, USA
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University, Baltimore, MD 21205, USA
- Correspondence: ; Tel.: +1-410-596-1956
| | - James H. Fallon
- Department of Anatomy and Neurobiology, University of California, Irvine, CA 92697, USA;
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA 92697, USA
| | - Karl J. Friston
- The Well Come Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK;
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Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex. J Neurosci 2021; 41:9374-9391. [PMID: 34645605 DOI: 10.1523/jneurosci.0367-21.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 09/15/2021] [Accepted: 09/20/2021] [Indexed: 11/21/2022] Open
Abstract
Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography was conducted in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFPs) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamic states, which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.SIGNIFICANCE STATEMENT This study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity-an auditory prediction error response-is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of nonoscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.
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21
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Krupnik V. Depression as a Failed Anxiety: The Continuum of Precision-Weighting Dysregulation in Affective Disorders. Front Psychol 2021; 12:657738. [PMID: 34366974 PMCID: PMC8339201 DOI: 10.3389/fpsyg.2021.657738] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 06/28/2021] [Indexed: 12/16/2022] Open
Abstract
Depressive, anxiety, and trauma-related disorders have many symptoms in common such as unstable mood, high anxiety, sleep disturbance, impaired concentration among others. This degeneracy creates ambiguity in classifying psychiatric disorders and raises the question of their categorical vs. dimensional nature. Consequently, such ambiguity presents a dilemma for choosing diagnosis-specific vs. trans-diagnostic therapies. In this paper, I build on a theory that considers affective disorders on the continuum of stress response from normative to traumatic. Using an integrative evolutionary-stress response-predictive processing (iESP) model, I arrange affective disorders on a continuum of precision-weighting dysregulation, where depressive, anxiety and trauma-induced disorders have a characteristic pattern of precision-weighting dysregulation. I specifically address the relationship between anxiety and depressive stress responses, exploring the role of anxiety in the dynamics of depressive stress response and the resulting high co-occurrence of anxiety and depression symptoms. Finally, I discuss the model's relevance for therapy of depression.
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Affiliation(s)
- Valery Krupnik
- Naval Hospital Camp Pendleton, Camp Pendleton, CA, United States
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22
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Ganglmayer K, Haupt M, Finke K, Paulus M. Adults, but not preschoolers or toddlers integrate situational constraints in their action anticipations: a developmental study on the flexibility of anticipatory gaze. Cogn Process 2021; 22:515-528. [PMID: 33763791 PMCID: PMC8324589 DOI: 10.1007/s10339-021-01015-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 01/16/2021] [Indexed: 10/29/2022]
Abstract
Recent theories stress the role of situational information in understanding others' behaviour. For example, the predictive coding framework assumes that people take contextual information into account when anticipating other's actions. Likewise, the teleological stance theory assumes an early developing ability to consider situational constraints in action prediction. The current study investigates, over a wide age range, whether humans flexibly integrate situational constraints in their action anticipations. By means of an eye-tracking experiment, 2-year-olds, 5-year-olds, younger and older adults (together N = 181) observed an agent repeatedly taking one of two paths to reach a goal. Then, this path became blocked, and for test trials only the other path was passable. Results demonstrated that in test trials younger and older adults anticipated that the agent would take the continuous path, indicating that they took the situational constraints into account. In contrast, 2- and 5-year-olds anticipated that the agent would take the blocked path, indicating that they still relied on the agent's previous observed behaviour and-contrary to claims by the teleological stance theory-did not take the situational constraints into account. The results highlight developmental changes in human's ability to include situational constraints in their visual anticipations. Overall, the study contributes to theories on predictive coding and the development of action understanding.
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Affiliation(s)
- Kerstin Ganglmayer
- Department Psychology, Developmental Psychology, Ludwig Maximilians-Universität München, Leopoldstr. 13, 80802, Munich, Germany.
| | - Marleen Haupt
- Department Psychology, General and Experimental Psychology, Ludwig-Maximilians-Universtität München, Munich, Germany
| | - Kathrin Finke
- Department Psychology, General and Experimental Psychology, Ludwig-Maximilians-Universtität München, Munich, Germany.,Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany
| | - Markus Paulus
- Department Psychology, Developmental Psychology, Ludwig Maximilians-Universität München, Leopoldstr. 13, 80802, Munich, Germany
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Affiliation(s)
- Karl J Friston
- Wellcome Centre for Human Neuroimaging and Queen Square Institute of Neurology, University College London; and National Hospital for Neurology and Neurosurgery, London
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24
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Hobson JA, Gott JA, Friston KJ. Minds and Brains, Sleep and Psychiatry. PSYCHIATRIC RESEARCH AND CLINICAL PRACTICE 2020; 3:12-28. [PMID: 35174319 PMCID: PMC8834904 DOI: 10.1176/appi.prcp.20200023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 10/14/2020] [Indexed: 11/30/2022] Open
Abstract
Objective This article offers a philosophical thesis for psychiatric disorders that rests upon some simple truths about the mind and brain. Specifically, it asks whether the dual aspect monism—that emerges from sleep research and theoretical neurobiology—can be applied to pathophysiology and psychopathology in psychiatry. Methods Our starting point is that the mind and brain are emergent aspects of the same (neuronal) dynamics; namely, the brain–mind. Our endpoint is that synaptic dysconnection syndromes inherit the same dual aspect; namely, aberrant inference or belief updating on the one hand, and a failure of neuromodulatory synaptic gain control on the other. We start with some basic considerations from sleep research that integrate the phenomenology of dreaming with the neurophysiology of sleep. Results We then leverage this treatment by treating the brain as an organ of inference. Our particular focus is on the role of precision (i.e., the representation of uncertainty) in belief updating and the accompanying synaptic mechanisms. Conclusions Finally, we suggest a dual aspect approach—based upon belief updating (i.e., mind processes) and its neurophysiological implementation (i.e., brain processes)—has a wide explanatory compass for psychiatry and various movement disorders. This approach identifies the kind of pathophysiology that underwrites psychopathology—and points to certain psychotherapeutic and psychopharmacological targets, which may stand in mechanistic relation to each other. The ‘mind’ emerges from Bayesian belief updating in the ‘brain’ Psychopathology can be read as aberrant belief updating. Aberrant belief updating follows from any neuromodulatory synaptopathy
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Affiliation(s)
- J. Allan Hobson
- Division of Sleep Medicine Harvard Medical School Boston Massachusetts
| | - Jarrod A. Gott
- Donders Institute for Brain, Cognition and Behaviour Radboud University Nijmegen
| | - Karl J. Friston
- The Wellcome Centre for Human Neuroimaging University College London London
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25
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Scott M, Chiu C. Temporal binding and agency under startle. Exp Brain Res 2020; 239:289-300. [PMID: 33165671 DOI: 10.1007/s00221-020-05972-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 10/24/2020] [Indexed: 11/30/2022]
Abstract
Forward models are a component of the motor system that predicts the sensory consequences of our actions. These models play several key roles in motor control and are hypothesized to underlie (among other things) the two phenomena under investigation in this experiment: The feeling of agency that we have over self-initiated actions (as opposed to reflexes), and "temporal binding", in which self-caused sensations are judged to have occurred earlier in time than they actually did. This experiment probes the connection between forward models and both of these phenomena using the "Startle" paradigm. In the Startle paradigm, a startlingly loud sound causes people to initiate a prepared action at a very short latency. It is hypothesized that the latency of a startle-initiated action is so short that normal cortical operations (including forward models) are circumvented. This experiment replicates the temporal-binding effect and simultaneously measures participants' sense of agency over their actions. The results show that both the temporal-binding effect and the sense of agency we have over our own actions is disrupted under the startle paradigm in line with the theory that these phenomena both rely on forward models. Furthermore, this experiment provides evidence in support of the claim that a startle-induced action is qualitatively different from other actions.
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26
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Barron HC, Auksztulewicz R, Friston K. Prediction and memory: A predictive coding account. Prog Neurobiol 2020; 192:101821. [PMID: 32446883 PMCID: PMC7305946 DOI: 10.1016/j.pneurobio.2020.101821] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 02/26/2020] [Accepted: 04/29/2020] [Indexed: 01/27/2023]
Abstract
The hippocampus is crucial for episodic memory, but it is also involved in online prediction. Evidence suggests that a unitary hippocampal code underlies both episodic memory and predictive processing, yet within a predictive coding framework the hippocampal-neocortical interactions that accompany these two phenomena are distinct and opposing. Namely, during episodic recall, the hippocampus is thought to exert an excitatory influence on the neocortex, to reinstate activity patterns across cortical circuits. This contrasts with empirical and theoretical work on predictive processing, where descending predictions suppress prediction errors to 'explain away' ascending inputs via cortical inhibition. In this hypothesis piece, we attempt to dissolve this previously overlooked dialectic. We consider how the hippocampus may facilitate both prediction and memory, respectively, by inhibiting neocortical prediction errors or increasing their gain. We propose that these distinct processing modes depend upon the neuromodulatory gain (or precision) ascribed to prediction error units. Within this framework, memory recall is cast as arising from fictive prediction errors that furnish training signals to optimise generative models of the world, in the absence of sensory data.
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Affiliation(s)
- Helen C Barron
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
| | - Ryszard Auksztulewicz
- Max Planck Institute for Empirical Aesthetics, Frankfurt Am Main, 60322, Germany; Department of Biomedical Sciences, City University of Hong Kong, Hong Kong
| | - Karl Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, WC1N 3BG, UK
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Kube T, Rozenkrantz L. When Beliefs Face Reality: An Integrative Review of Belief Updating in Mental Health and Illness. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2020; 16:247-274. [DOI: 10.1177/1745691620931496] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Belief updating is a relatively nascent field of research that examines how people adjust their beliefs in light of new evidence. So far, belief updating has been investigated in partly unrelated lines of research from different psychological disciplines. In this article, we aim to integrate these disparate lines of research. After presenting some prominent theoretical frameworks and experimental designs that have been used for the study of belief updating, we review how healthy people and people with mental disorders update their beliefs after receiving new information that supports or challenges their views. Available evidence suggests that both healthy people and people with particular mental disorders are prone to certain biases when updating their beliefs, although the nature of the respective biases varies considerably and depends on several factors. Anomalies in belief updating are discussed in terms of both new insights into the psychopathology of various mental disorders and societal implications, such as irreconcilable political and societal controversies due to the failure to take information into account that disconfirms one’s own view. We conclude by proposing a novel integrative model of belief updating and derive directions for future research.
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Affiliation(s)
- Tobias Kube
- Program in Placebo Studies, Harvard Medical School/Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Department of Psychology, Clinical Psychology and Psychotherapy, University of Koblenz-Landau
| | - Liron Rozenkrantz
- Program in Placebo Studies, Harvard Medical School/Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
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28
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Krupnik V. Trauma or Drama: A Predictive Processing Perspective on the Continuum of Stress. Front Psychol 2020; 11:1248. [PMID: 32714230 PMCID: PMC7344261 DOI: 10.3389/fpsyg.2020.01248] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 05/13/2020] [Indexed: 02/01/2023] Open
Abstract
The notion of psychological trauma has been liberally used both in clinical literature and general discourse. However, no consensus exists on its exact meaning and definition. Whereas traditionally trauma has been mostly associated with criterion A of acute and posttraumatic stress disorders (PTSDs) as defined in the Diagnostic and Statistical Manual of Mental Disorders, many researchers find this definition too constraining and not accounting for the complexity and many aspects of trauma. This touched off a quest for a broader more accommodating trauma concept, and a dimensional view of trauma with PTSD as its extreme manifestation has been suggested. The dimensional view also has its detractors arguing that "conceptual bracket creep" may undermine the category's utility. Both categorical and dimensional views mostly rely on trauma's clinical phenomenology and lack a unified theoretical basis. In an attempt to reconcile this contradiction, a hybrid categorical-dimensional model of trauma based on the general theory of stress has been recently proposed (Krupnik, 2019). Herein, I explore the categorical boundary of the trauma concept, as posited by the model, within the predictive processing framework (PPF). I integrate the PPF view with the theory of stress. In conclusion, I briefly discuss how the proposed model of trauma may guide clinical practice.
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Affiliation(s)
- Valery Krupnik
- Department of Mental Health, Naval Hospital Camp Pendleton, Camp Pendleton, CA, United States
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29
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Friston KJ, Wiese W, Hobson JA. Sentience and the Origins of Consciousness: From Cartesian Duality to Markovian Monism. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E516. [PMID: 33286288 PMCID: PMC7517007 DOI: 10.3390/e22050516] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 04/15/2020] [Accepted: 04/16/2020] [Indexed: 12/23/2022]
Abstract
This essay addresses Cartesian duality and how its implicit dialectic might be repaired using physics and information theory. Our agenda is to describe a key distinction in the physical sciences that may provide a foundation for the distinction between mind and matter, and between sentient and intentional systems. From this perspective, it becomes tenable to talk about the physics of sentience and 'forces' that underwrite our beliefs (in the sense of probability distributions represented by our internal states), which may ground our mental states and consciousness. We will refer to this view as Markovian monism, which entails two claims: (1) fundamentally, there is only one type of thing and only one type of irreducible property (hence monism). (2) All systems possessing a Markov blanket have properties that are relevant for understanding the mind and consciousness: if such systems have mental properties, then they have them partly by virtue of possessing a Markov blanket (hence Markovian). Markovian monism rests upon the information geometry of random dynamic systems. In brief, the information geometry induced in any system-whose internal states can be distinguished from external states-must acquire a dual aspect. This dual aspect concerns the (intrinsic) information geometry of the probabilistic evolution of internal states and a separate (extrinsic) information geometry of probabilistic beliefs about external states that are parameterised by internal states. We call these intrinsic (i.e., mechanical, or state-based) and extrinsic (i.e., Markovian, or belief-based) information geometries, respectively. Although these mathematical notions may sound complicated, they are fairly straightforward to handle, and may offer a means through which to frame the origins of consciousness.
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Affiliation(s)
- Karl J. Friston
- The Wellcome Centre for Human Neuroimaging, Institute of Neurology, Queen Square, London WC1N 3AR, UK
| | - Wanja Wiese
- Department of Philosophy, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 18, 55128 Mainz, Germany
| | - J. Allan Hobson
- Division of Sleep Medicine, Harvard Medical School, 74 Fenwood Road, Boston, MA 02115, USA
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30
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Demekas D, Parr T, Friston KJ. An Investigation of the Free Energy Principle for Emotion Recognition. Front Comput Neurosci 2020; 14:30. [PMID: 32390817 PMCID: PMC7189749 DOI: 10.3389/fncom.2020.00030] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 03/23/2020] [Indexed: 01/23/2023] Open
Abstract
This paper offers a prospectus of what might be achievable in the development of emotional recognition devices. It provides a conceptual overview of the free energy principle; including Markov blankets, active inference, and-in particular-a discussion of selfhood and theory of mind, followed by a brief explanation of how these concepts can explain both neural and cultural models of emotional inference. The underlying hypothesis is that emotion recognition and inference devices will evolve from state-of-the-art deep learning models into active inference schemes that go beyond marketing applications and become adjunct to psychiatric practice. Specifically, this paper proposes that a second wave of emotion recognition devices will be equipped with an emotional lexicon (or the ability to epistemically search for one), allowing the device to resolve uncertainty about emotional states by actively eliciting responses from the user and learning from these responses. Following this, a third wave of emotional devices will converge upon the user's generative model, resulting in the machine and human engaging in a reciprocal, prosocial emotional interaction, i.e., sharing a generative model of emotional states.
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Affiliation(s)
- Daphne Demekas
- Department of Mathematics, University College London, London, United Kingdom
| | - Thomas Parr
- Department of Mathematics, University College London, London, United Kingdom
| | - Karl J. Friston
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
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Mazor M, Friston KJ, Fleming SM. Distinct neural contributions to metacognition for detecting, but not discriminating visual stimuli. eLife 2020; 9:e53900. [PMID: 32310086 PMCID: PMC7170652 DOI: 10.7554/elife.53900] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 03/24/2020] [Indexed: 01/07/2023] Open
Abstract
Being confident in whether a stimulus is present or absent (a detection judgment) is qualitatively distinct from being confident in the identity of that stimulus (a discrimination judgment). In particular, in detection, evidence can only be available for the presence, not the absence, of a target object. This asymmetry suggests that higher-order cognitive and neural processes may be required for confidence in detection, and more specifically, in judgments about absence. In a within-subject, pre-registered and performance-matched fMRI design, we observed quadratic confidence effects in frontopolar cortex for detection but not discrimination. Furthermore, in the right temporoparietal junction, confidence effects were enhanced for judgments of target absence compared to judgments of target presence. We interpret these findings as reflecting qualitative differences between a neural basis for metacognitive evaluation of detection and discrimination, potentially in line with counterfactual or higher-order models of confidence formation in detection.
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Affiliation(s)
- Matan Mazor
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Stephen M Fleming
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
- Max Planck UCL Centre for Computational Psychiatry and Aging Research, University College LondonLondonUnited Kingdom
- Department of Experimental Psychology, University College LondonLondonUnited Kingdom
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Abstract
Eye Movement Desensitization and Reprocessing Therapy (EMDR) is an effective treatment for Post-traumatic Stress Disorder (PTSD). The Adaptive Information Processing Model (AIP) guides the development and practice of EMDR. The AIP postulates inadequately processed memory as the foundation of PTSD pathology. Predictive Processing postulates that the primary function of the brain is prediction that serves to anticipate the next moment of experience in order to resist the dissipative force of entropy thus facilitating continued survival. Memory is the primary substrate of prediction, and is optimized by an ongoing process of precision weighted prediction error minimization that refines prediction by updating the memories on which it is based. The Predictive Processing model of EMDR postulates that EMDR facilitates the predictive processing of traumatic memory by overcoming the bias against exploration and evidence accumulation. The EMDR protocol brings the traumatic memory into an active state of re-experiencing. Defensive responding and/or low sensory precision preclude evidence accumulation to test the predictions of the traumatic memory in the present. Sets of therapist guided eye movements repeatedly challenge the bias against evidence accumulation and compel sensory sampling of the benign present. Eye movements reset the theta rhythm organizing the flow of information through the brain, facilitating the deployment of both overt and covert attention, and the mnemonic search for associations. Sampling of sensation does not support the predictions of the traumatic memory resulting in prediction error that the brain then attempts to minimize. The net result is a restoration of the integrity of the rhythmic deployment of attention, a recalibration of sensory precision, and the updating (reconsolidation) of the traumatic memory. Thus one prediction of the model is a decrease in Attention Bias Variability, a core dysfunction in PTSD, following successful treatment with EMDR.
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Abstract
Predictive processing (e.g., predictive coding) is a predominant paradigm in cognitive neuroscience. This Primer considers the various levels of commitment neuroscientists have to the neuronal process theories that accompany the principles of predictive processing. Specifically, it reviews and contextualises a recent PLOS Biology study of alpha oscillations and travelling waves. We will see that alpha oscillations emerge naturally under the computational architectures implied by predictive coding-and may tell us something profound about recurrent message passing in brain hierarchies. Specifically, the bidirectional nature of forward and backward waves speaks to opportunities to understand attention and how it nuances bottom-up and top-down influences.
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Affiliation(s)
- Karl J. Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
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Dennison P. The Human Default Consciousness and Its Disruption: Insights From an EEG Study of Buddhist Jhāna Meditation. Front Hum Neurosci 2019; 13:178. [PMID: 31249516 PMCID: PMC6582244 DOI: 10.3389/fnhum.2019.00178] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 05/16/2019] [Indexed: 01/09/2023] Open
Abstract
The “neural correlates of consciousness” (NCC) is a familiar topic in neuroscience, overlapping with research on the brain’s “default mode network.” Task-based studies of NCC by their nature recruit one part of the cortical network to study another, and are therefore both limited and compromised in what they can reveal about consciousness itself. The form of consciousness explored in such research, we term the human default consciousness (DCs), our everyday waking consciousness. In contrast, studies of anesthesia, coma, deep sleep, or some extreme pathological states such as epilepsy, reveal very different cortical activity; all of which states are essentially involuntary, and generally regarded as “unconscious.” An exception to involuntary disruption of consciousness is Buddhist jhāna meditation, whose implicit aim is to intentionally withdraw from the default consciousness, to an inward-directed state of stillness referred to as jhāna consciousness, as a basis to develop insight. The default consciousness is sensorily-based, where information about, and our experience of, the outer world is evaluated against personal and organic needs and forms the basis of our ongoing self-experience. This view conforms both to Buddhist models, and to the emerging work on active inference and minimization of free energy in determining the network balance of the human default consciousness. This paper is a preliminary report on the first detailed EEG study of jhāna meditation, with findings radically different to studies of more familiar, less focused forms of meditation. While remaining highly alert and “present” in their subjective experience, a high proportion of subjects display “spindle” activity in their EEG, superficially similar to sleep spindles of stage 2 nREM sleep, while more-experienced subjects display high voltage slow-waves reminiscent, but significantly different, to the slow waves of deeper stage 4 nREM sleep, or even high-voltage delta coma. Some others show brief posterior spike-wave bursts, again similar, but with significant differences, to absence epilepsy. Some subjects also develop the ability to consciously evoke clonic seizure-like activity at will, under full control. We suggest that the remarkable nature of these observations reflects a profound disruption of the human DCs when the personal element is progressively withdrawn.
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Mamashli F, Khan S, Obleser J, Friederici AD, Maess B. Oscillatory dynamics of cortical functional connections in semantic prediction. Hum Brain Mapp 2019; 40:1856-1866. [PMID: 30537025 PMCID: PMC6865711 DOI: 10.1002/hbm.24495] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 11/20/2018] [Accepted: 11/28/2018] [Indexed: 01/22/2023] Open
Abstract
An event related potential, known as the N400, has been particularly useful in investigating language processing as it serves as a neural index for semantic prediction. There are numerous studies on the functional segregation of N400 neural sources; however, the oscillatory dynamics of functional connections among the relevant sources has remained elusive. In this study we acquired magnetoencephalography data during a classic N400 paradigm, where the semantic predictability of a fixed target noun was manipulated in simple German sentences. We conducted inter-regional functional connectivity (FC) and time-frequency analysis on known regions of the semantic network, encompassing bilateral temporal, and prefrontal cortices. Increased FC was found in less predicted (LP) nouns compared with highly predicted (HP) nouns in three connections: (a) right inferior frontal gyrus (IFG) and right middle temporal gyrus (MTG) from 0 to 300 ms mainly within the alpha band, (b) left lateral orbitofrontal (LOF) and right IFG around 400 ms within the beta band, and (c) left superior temporal gyrus (STG) and left LOF from 300 to 700 ms in the beta and low gamma bands. Furthermore, gamma spectral power (31-70 Hz) was stronger in HP nouns than in LP nouns in left anterior temporal cortices in earlier time windows (0-200 ms). Our findings support recent theories in language comprehension, suggesting fronto-temporal top-down connections are mainly mediated through beta oscillations while gamma band frequencies are involved in matching between prediction and input.
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Affiliation(s)
- Fahimeh Mamashli
- Department of RadiologyMassachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical SchoolBostonMassachusetts
| | - Sheraz Khan
- Department of RadiologyMassachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical SchoolBostonMassachusetts
| | - Jonas Obleser
- Department of PsychologyUniversity of LübeckLübeckGermany
| | - Angela D. Friederici
- Department of NeuropsychologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Burkhard Maess
- MEG and Cortical Networks Group, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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The role of the hippocampus in weighting expectations during inference under uncertainty. Cortex 2019; 115:1-14. [PMID: 30738997 PMCID: PMC6533111 DOI: 10.1016/j.cortex.2019.01.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2018] [Revised: 09/22/2018] [Accepted: 01/06/2019] [Indexed: 11/18/2022]
Abstract
Making inference under uncertainty requires an optimal weighting of prior expectations and observations. How this weighting is realized in the brain remains elusive. To investigate this, we recorded functional neuroimaging data while participants estimated a number based on noisy observations. Crucially, the prior expectation about the variability of observations (an expected variability) was manipulated. Consistent with normative models, when novel observations were characterized by higher expected or observed variability, participants' estimates relied more on expectations than novel observations and were characterized by higher stochasticity. Activity in hippocampus increased when novel evidence was characterized by higher expected or observed variability. Response in superior parietal cortex reflected a precision-weighted prediction error signal (i.e., the distance between observations and expectations) that was modulated by hippocampal activity. Our findings implicate the hippocampus during inference under uncertainty, suggesting a role in weighting prior representations over observations and in modulating responsivity of superior parietal cortex to prediction error.
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Heil L, Kwisthout J, van Pelt S, van Rooij I, Bekkering H. One wouldn't expect an expert bowler to hit only two pins: Hierarchical predictive processing of agent-caused events. Q J Exp Psychol (Hove) 2018; 71:2643-2654. [PMID: 29359640 PMCID: PMC6293453 DOI: 10.1177/1747021817752102] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Evidence is accumulating that our brains process incoming information using top-down
predictions. If lower level representations are correctly predicted by higher level
representations, this enhances processing. However, if they are incorrectly predicted,
additional processing is required at higher levels to “explain away” prediction errors.
Here, we explored the potential nature of the models generating such predictions. More
specifically, we investigated whether a predictive processing model with a hierarchical
structure and causal relations between its levels is able to account for the processing of
agent-caused events. In Experiment 1, participants watched animated movies of
“experienced” and “novice” bowlers. The results are in line with the idea that prediction
errors at a lower level of the hierarchy (i.e., the outcome of how many
pins fell down) slow down reporting of information at a higher level (i.e., which
agent was throwing the ball). Experiments 2 and 3 suggest that this
effect is specific to situations in which the predictor is causally related to the
outcome. Overall, the study supports the idea that a hierarchical predictive processing
model can account for the processing of observed action outcomes and that the predictions
involved are specific to cases where action outcomes can be predicted based on causal
knowledge.
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Affiliation(s)
- Lieke Heil
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Johan Kwisthout
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Stan van Pelt
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Iris van Rooij
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Harold Bekkering
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
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Bolis D, Schilbach L. Observing and participating in social interactions: Action perception and action control across the autistic spectrum. Dev Cogn Neurosci 2018; 29:168-175. [PMID: 28188104 PMCID: PMC6987847 DOI: 10.1016/j.dcn.2017.01.009] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 12/18/2016] [Accepted: 01/18/2017] [Indexed: 12/13/2022] Open
Abstract
Autism is a developmental condition, characterized by difficulties of social interaction and communication, as well as restricted interests and repetitive behaviors. Although several important conceptions have shed light on specific facets, there is still no consensus about a universal yet specific theory in terms of its underlying mechanisms. While some theories have exclusively focused on sensory aspects, others have emphasized social difficulties. However, sensory and social processes in autism might be interconnected to a higher degree than what has been traditionally thought. We propose that a mismatch in sensory abilities across individuals can lead to difficulties on a social, i.e. interpersonal level and vice versa. In this article, we, therefore, selectively review evidence indicating an interrelationship between perceptual and social difficulties in autism. Additionally, we link this body of research with studies, which investigate the mechanisms of action control in social contexts. By doing so, we highlight that autistic traits are also crucially related to differences in integration, anticipation and automatic responding to social cues, rather than a mere inability to register and learn from social cues. Importantly, such differences may only manifest themselves in sufficiently complex situations, such as real-life social interactions, where such processes are inextricably linked.
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Affiliation(s)
- Dimitris Bolis
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany.
| | - Leonhard Schilbach
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany; Department of Psychiatry, Ludwig Maximilian University, Munich, Germany; Graduate School of Systemic Neuroscience (GSN), Munich, Germany.
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40
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Zhou Y, Zeidman P, Wu S, Razi A, Chen C, Yang L, Zou J, Wang G, Wang H, Friston KJ. Altered intrinsic and extrinsic connectivity in schizophrenia. NEUROIMAGE-CLINICAL 2017; 17:704-716. [PMID: 29264112 PMCID: PMC5726753 DOI: 10.1016/j.nicl.2017.12.006] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 09/25/2017] [Accepted: 12/03/2017] [Indexed: 01/12/2023]
Abstract
Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia. A first use of hierarchical modeling of effective connectivity to characterize large-scale networks in schizophrenia. Intrinsic and extrinsic effective connectivity involving prefrontal regions were abnormal in schizophrenia. Diagnostic connections could predict the severity of clinical symptoms and cognition in schizophrenia.
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Affiliation(s)
- Yuan Zhou
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101,China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China; The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK.
| | - Peter Zeidman
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
| | - Shihao Wu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Adeel Razi
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK; Department of Electronic Engineering, NED University of Engineering and Technology, Karachi, Pakistan
| | - Cheng Chen
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Liuqing Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jilin Zou
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China; Hubei Provincial Key Laboratory of Developmentally Originated Disease, Wuhan 430071, China.
| | - Karl J Friston
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
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Barrett LF. The theory of constructed emotion: an active inference account of interoception and categorization. Soc Cogn Affect Neurosci 2017; 12:1-23. [PMID: 27798257 PMCID: PMC5390700 DOI: 10.1093/scan/nsw154] [Citation(s) in RCA: 291] [Impact Index Per Article: 41.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2016] [Accepted: 10/11/2016] [Indexed: 12/21/2022] Open
Abstract
The science of emotion has been using folk psychology categories derived from philosophy to search for the brain basis of emotion. The last two decades of neuroscience research have brought us to the brink of a paradigm shift in understanding the workings of the brain, however, setting the stage to revolutionize our understanding of what emotions are and how they work. In this article, we begin with the structure and function of the brain, and from there deduce what the biological basis of emotions might be. The answer is a brain-based, computational account called the theory of constructed emotion.
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Affiliation(s)
- Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, USA.,Athinoula, A. Martinos Center for Biomedical Imaging.,Psychiatric Neuroimaging Division, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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Friston KJ. Self-evidencing babies: Commentary on “Mentalizing homeostasis: The social origins of interoceptive inference” by Fotopoulou & Tsakiris. ACTA ACUST UNITED AC 2017. [DOI: 10.1080/15294145.2017.1295216] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Bolis D, Balsters J, Wenderoth N, Becchio C, Schilbach L. Beyond Autism: Introducing the Dialectical Misattunement Hypothesis and a Bayesian Account of Intersubjectivity. Psychopathology 2017; 50:355-372. [PMID: 29232684 DOI: 10.1159/000484353] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 10/17/2017] [Indexed: 12/11/2022]
Abstract
Drawing on sociocultural theories and Bayesian accounts of brain function, in this article we construe psychiatric conditions as disorders of social interaction to fully account for their complexity and dynamicity across levels of description and temporal scales. After an introduction of the theoretical underpinnings of our integrative approach, we take autism spectrum conditions (ASC) as a paradigm example and discuss how neurocognitive hypotheses can be translated into a Bayesian formulation, i.e., in terms of predictive processing and active inference. We then argue that consideration of individuals (even within a Bayesian framework) will not be enough for a comprehensive understanding of psychiatric conditions and consequently put forward the dialectical misattunement hypothesis, which views psychopathology not merely as disordered function within single brains but also as a dynamic interpersonal mismatch that encompasses various levels of description. Moving from a mere comparison of groups, i.e., "healthy" persons versus "patients," to a fine-grained analysis of social interactions within dyads and groups of individuals will open new avenues and may allow to avoid an overly neurocentric scope in psychiatric research as well as help to reduce social exclusion.
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Affiliation(s)
- Dimitris Bolis
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
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Barrett LF, Quigley KS, Hamilton P. An active inference theory of allostasis and interoception in depression. Philos Trans R Soc Lond B Biol Sci 2016; 371:20160011. [PMID: 28080969 PMCID: PMC5062100 DOI: 10.1098/rstb.2016.0011] [Citation(s) in RCA: 231] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/19/2016] [Indexed: 12/30/2022] Open
Abstract
In this paper, we integrate recent theoretical and empirical developments in predictive coding and active inference accounts of interoception (including the Embodied Predictive Interoception Coding model) with working hypotheses from the theory of constructed emotion to propose a biologically plausible unified theory of the mind that places metabolism and energy regulation (i.e. allostasis), as well as the sensory consequences of that regulation (i.e. interoception), at its core. We then consider the implications of this approach for understanding depression. We speculate that depression is a disorder of allostasis, whose myriad symptoms result from a 'locked in' brain that is relatively insensitive to its sensory context. We conclude with a brief discussion of the ways our approach might reveal new insights for the treatment of depression.This article is part of the themed issue 'Interoception beyond homeostasis: affect, cognition and mental health'.
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Affiliation(s)
- Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Karen S Quigley
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Paul Hamilton
- Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
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Seth AK, Friston KJ. Active interoceptive inference and the emotional brain. Philos Trans R Soc Lond B Biol Sci 2016; 371:rstb.2016.0007. [PMID: 28080966 PMCID: PMC5062097 DOI: 10.1098/rstb.2016.0007] [Citation(s) in RCA: 389] [Impact Index Per Article: 48.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2016] [Indexed: 01/14/2023] Open
Abstract
We review a recent shift in conceptions of interoception and its relationship to hierarchical inference in the brain. The notion of interoceptive inference means that bodily states are regulated by autonomic reflexes that are enslaved by descending predictions from deep generative models of our internal and external milieu. This re-conceptualization illuminates several issues in cognitive and clinical neuroscience with implications for experiences of selfhood and emotion. We first contextualize interoception in terms of active (Bayesian) inference in the brain, highlighting its enactivist (embodied) aspects. We then consider the key role of uncertainty or precision and how this might translate into neuromodulation. We next examine the implications for understanding the functional anatomy of the emotional brain, surveying recent observations on agranular cortex. Finally, we turn to theoretical issues, namely, the role of interoception in shaping a sense of embodied self and feelings. We will draw links between physiological homoeostasis and allostasis, early cybernetic ideas of predictive control and hierarchical generative models in predictive processing. The explanatory scope of interoceptive inference ranges from explanations for autism and depression, through to consciousness. We offer a brief survey of these exciting developments. This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’.
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Affiliation(s)
- Anil K Seth
- Sackler Centre for Consciousness Science, School of Engineering and Informatics, University of Sussex, Falmer, Brighton BN1 9QJ, UK
| | - Karl J Friston
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London WC1N 3BG, UK
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Friston K, Brown HR, Siemerkus J, Stephan KE. The dysconnection hypothesis (2016). Schizophr Res 2016; 176:83-94. [PMID: 27450778 PMCID: PMC5147460 DOI: 10.1016/j.schres.2016.07.014] [Citation(s) in RCA: 358] [Impact Index Per Article: 44.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 07/06/2016] [Accepted: 07/15/2016] [Indexed: 02/06/2023]
Abstract
Twenty years have passed since the dysconnection hypothesis was first proposed (Friston and Frith, 1995; Weinberger, 1993). In that time, neuroscience has witnessed tremendous advances: we now live in a world of non-invasive neuroanatomy, computational neuroimaging and the Bayesian brain. The genomics era has come and gone. Connectomics and large-scale neuroinformatics initiatives are emerging everywhere. So where is the dysconnection hypothesis now? This article considers how the notion of schizophrenia as a dysconnection syndrome has developed - and how it has been enriched by recent advances in clinical neuroscience. In particular, we examine the dysconnection hypothesis in the context of (i) theoretical neurobiology and computational psychiatry; (ii) the empirical insights afforded by neuroimaging and associated connectomics - and (iii) how bottom-up (molecular biology and genetics) and top-down (systems biology) perspectives are converging on the mechanisms and nature of dysconnections in schizophrenia.
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Affiliation(s)
- Karl Friston
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, UK.
| | - Harriet R. Brown
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, UK,Oxford Centre for Human Brain Activity, University of Oxford, UK
| | - Jakob Siemerkus
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland,Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland
| | - Klaas E. Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland
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Predictive processing simplified: The infotropic machine. Brain Cogn 2016; 112:13-24. [PMID: 27102775 DOI: 10.1016/j.bandc.2016.03.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2015] [Revised: 03/18/2016] [Accepted: 03/21/2016] [Indexed: 11/20/2022]
Abstract
On a traditional view of cognition, we see the agent acquiring stimuli, interpreting these in some way, and producing behavior in response. An increasingly popular alternative is the predictive processing framework. This sees the agent as continually generating predictions about the world, and responding productively to any errors made. Partly because of its heritage in the Bayesian brain theory, predictive processing has generally been seen as an inherently Bayesian process. The 'hierarchical prediction machine' which mediates it is envisaged to be a specifically Bayesian device. But as this paper shows, a specification for this machine can also be derived directly from information theory, using the metric of predictive payoff as an organizing concept. Hierarchical prediction machines can be built along purely information-theoretic lines, without referencing Bayesian theory in any way; this simplifies the account to some degree. The present paper describes what is involved and presents a series of working models. An experiment involving the conversion of a Braitenberg vehicle to use a controller of this type is also described.
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Kanai R, Komura Y, Shipp S, Friston K. Cerebral hierarchies: predictive processing, precision and the pulvinar. Philos Trans R Soc Lond B Biol Sci 2015; 370:rstb.2014.0169. [PMID: 25823866 PMCID: PMC4387510 DOI: 10.1098/rstb.2014.0169] [Citation(s) in RCA: 207] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
This paper considers neuronal architectures from a computational perspective and asks what aspects of neuroanatomy and neurophysiology can be disclosed by the nature of neuronal computations? In particular, we extend current formulations of the brain as an organ of inference—based upon hierarchical predictive coding—and consider how these inferences are orchestrated. In other words, what would the brain require to dynamically coordinate and contextualize its message passing to optimize its computational goals? The answer that emerges rests on the delicate (modulatory) gain control of neuronal populations that select and coordinate (prediction error) signals that ascend cortical hierarchies. This is important because it speaks to a hierarchical anatomy of extrinsic (between region) connections that form two distinct classes, namely a class of driving (first-order) connections that are concerned with encoding the content of neuronal representations and a class of modulatory (second-order) connections that establish context—in the form of the salience or precision ascribed to content. We explore the implications of this distinction from a formal perspective (using simulations of feature–ground segregation) and consider the neurobiological substrates of the ensuing precision-engineered dynamics, with a special focus on the pulvinar and attention.
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Affiliation(s)
- Ryota Kanai
- School of Psychology, Sackler Centre for Consciousness Science, University of Sussex, Brighton BN1 9QH, UK Precursory Research for Embryonic Science and Technology, Japan Science and Technology Agency, Saitama 332-0012, Japan
| | - Yutaka Komura
- School of Psychology, Sackler Centre for Consciousness Science, University of Sussex, Brighton BN1 9QH, UK Precursory Research for Embryonic Science and Technology, Japan Science and Technology Agency, Saitama 332-0012, Japan Systems Neuroscience, Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba 305-8568, Japan
| | | | - Karl Friston
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London WC1 3BG, UK
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Abstract
This paper considers communication in terms of inference about the behaviour of others (and our own behaviour). It is based on the premise that our sensations are largely generated by other agents like ourselves. This means, we are trying to infer how our sensations are caused by others, while they are trying to infer our behaviour: for example, in the dialogue between two speakers. We suggest that the infinite regress induced by modelling another agent - who is modelling you - can be finessed if you both possess the same model. In other words, the sensations caused by others and oneself are generated by the same process. This leads to a view of communication based upon a narrative that is shared by agents who are exchanging sensory signals. Crucially, this narrative transcends agency - and simply involves intermittently attending to and attenuating sensory input. Attending to sensations enables the shared narrative to predict the sensations generated by another (i.e. to listen), while attenuating sensory input enables one to articulate the narrative (i.e. to speak). This produces a reciprocal exchange of sensory signals that, formally, induces a generalised synchrony between internal (neuronal) brain states generating predictions in both agents. We develop the arguments behind this perspective, using an active (Bayesian) inference framework and offer some simulations (of birdsong) as proof of principle.
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Affiliation(s)
- Karl Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, United Kingdom.
| | - Christopher Frith
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, United Kingdom
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