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Zahedi A, Lynn SJ, Sommer W. Cognitive simulation along with neural adaptation explain effects of suggestions: a novel theoretical framework. Front Psychol 2024; 15:1388347. [PMID: 38966744 PMCID: PMC11223671 DOI: 10.3389/fpsyg.2024.1388347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 04/30/2024] [Indexed: 07/06/2024] Open
Abstract
Hypnosis is an effective intervention with proven efficacy that is employed in clinical settings and for investigating various cognitive processes. Despite their practical success, no consensus exists regarding the mechanisms underlying well-established hypnotic phenomena. Here, we suggest a new framework called the Simulation-Adaptation Theory of Hypnosis (SATH). SATH expands the predictive coding framework by focusing on (a) redundancy elimination in generative models using intrinsically generated prediction errors, (b) adaptation due to amplified or prolonged neural activity, and (c) using internally generated predictions as a venue for learning new associations. The core of our treatise is that simulating proprioceptive, interoceptive, and exteroceptive signals, along with the top-down attenuation of the precision of sensory prediction errors due to neural adaptation, can explain objective and subjective hypnotic phenomena. Based on these postulations, we offer mechanistic explanations for critical categories of direct verbal suggestions, including (1) direct-ideomotor, (2) challenge-ideomotor, (3) perceptual, and (4) cognitive suggestions. Notably, we argue that besides explaining objective responses, SATH accounts for the subjective effects of suggestions, i.e., the change in the sense of agency and reality. Finally, we discuss individual differences in hypnotizability and how SATH accommodates them. We believe that SATH is exhaustive and parsimonious in its scope, can explain a wide range of hypnotic phenomena without contradiction, and provides a host of testable predictions for future research.
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Affiliation(s)
- Anoushiravan Zahedi
- Department of Psychology, University of Münster, Münster, Germany
- Department of Psychology, Humboldt-Universitaet zu Berlin, Berlin, Germany
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Steven Jay Lynn
- Department of Psychology, Binghamton University, Binghamton, NY, United States
| | - Werner Sommer
- Department of Psychology, Humboldt-Universitaet zu Berlin, Berlin, Germany
- Department of Psychology, Zhejiang Normal University, Jinhua, China
- Department of Physics and Life Science Imaging Center, Hong Kong Baptist University, Kowloon, Hong Kong SAR, China
- Faculty of Education, National University of Malaysia, Kuala Lumpur, Malaysia
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2
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Santo-Angles A, Temudo A, Babushkin V, Sreenivasan KK. Effective connectivity of working memory performance: a DCM study of MEG data. Front Hum Neurosci 2024; 18:1339728. [PMID: 38501039 PMCID: PMC10944968 DOI: 10.3389/fnhum.2024.1339728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 02/12/2024] [Indexed: 03/20/2024] Open
Abstract
Visual working memory (WM) engages several nodes of a large-scale network that includes frontal, parietal, and visual regions; however, little is understood about how these regions interact to support WM behavior. In particular, it is unclear whether network dynamics during WM maintenance primarily represent feedforward or feedback connections. This question has important implications for current debates about the relative roles of frontoparietal and visual regions in WM maintenance. In the current study, we investigated the network activity supporting WM using MEG data acquired while healthy subjects performed a multi-item delayed estimation WM task. We used computational modeling of behavior to discriminate correct responses (high accuracy trials) from two different types of incorrect responses (low accuracy and swap trials), and dynamic causal modeling of MEG data to measure effective connectivity. We observed behaviorally dependent changes in effective connectivity in a brain network comprising frontoparietal and early visual areas. In comparison with high accuracy trials, frontoparietal and frontooccipital networks showed disrupted signals depending on type of behavioral error. Low accuracy trials showed disrupted feedback signals during early portions of WM maintenance and disrupted feedforward signals during later portions of maintenance delay, while swap errors showed disrupted feedback signals during the whole delay period. These results support a distributed model of WM that emphasizes the role of visual regions in WM storage and where changes in large scale network configurations can have important consequences for memory-guided behavior.
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Affiliation(s)
- Aniol Santo-Angles
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
- Center for Brain and Health, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Ainsley Temudo
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Vahan Babushkin
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Kartik K. Sreenivasan
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
- Center for Brain and Health, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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Sarasso P, Ronga I, Piovesan F, Barbieri P, Del Fante E, De Luca D, Bechis L, Osello A, Sacco K. Shared attention in virtual immersive reality enhances electrophysiological correlates of implicit sensory learning. Sci Rep 2024; 14:3767. [PMID: 38355691 PMCID: PMC10866920 DOI: 10.1038/s41598-024-53937-w] [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: 04/20/2023] [Accepted: 02/06/2024] [Indexed: 02/16/2024] Open
Abstract
Shared attention effects on learning and memory demonstrate that experiences are amplified when we are not alone. Virtual reality poses new challenges to the study of co-presence. Above all, is coattending together with someone else's avatar in an immersive VR setting comparable with shared experiences at a neural processing level? In the present study we investigate shared attention effects in VR for the first time. We recorded mismatch negativities (MMN) during an auditory roving paradigm, a well-known index of implicit perceptual learning. EEG responses to deviant and standard sounds were registered while subjects were alone (Solo condition) or together (Other condition) with a virtual avatar (Virtual scenario) or physically present confederate (Physical scenario). We found an overall main effect of co-presence on MMN revealed by a point-by-point 2 × 2 ANOVA, thereby replicating previous studies on physical co-presence. Additionally, we found no significant interaction between the scenario (Physical vs. Virtual) and co-presence (Solo vs. Other). Our results indicate that virtual immersive co-presence mimics physical co-presence.
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Affiliation(s)
- Pietro Sarasso
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy
| | - Irene Ronga
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy.
| | - Francesca Piovesan
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy
| | - Paolo Barbieri
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy
| | - Elena Del Fante
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy
| | - Daniela De Luca
- VR@POLITO, Department of Structural, Geotechnical and Building Engineering (DISEG), Polytechnic University of Turin, Turin, Italy
| | - Ludovico Bechis
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy
| | - Anna Osello
- VR@POLITO, Department of Structural, Geotechnical and Building Engineering (DISEG), Polytechnic University of Turin, Turin, Italy
| | - Katiuscia Sacco
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Dipartimento di Psicologia, Università degli Studi di Torino, Via Verdi, 10, 10124, Turin, Italy
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4
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Kobayashi K, Shiba Y, Honda S, Nakajima S, Fujii S, Mimura M, Noda Y. Short-Term Effect of Auditory Stimulation on Neural Activities: A Scoping Review of Longitudinal Electroencephalography and Magnetoencephalography Studies. Brain Sci 2024; 14:131. [PMID: 38391706 PMCID: PMC10887208 DOI: 10.3390/brainsci14020131] [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: 12/03/2023] [Revised: 12/24/2023] [Accepted: 01/24/2024] [Indexed: 02/24/2024] Open
Abstract
Explored through EEG/MEG, auditory stimuli function as a suitable research probe to reveal various neural activities, including event-related potentials, brain oscillations and functional connectivity. Accumulating evidence in this field stems from studies investigating neuroplasticity induced by long-term auditory training, specifically cross-sectional studies comparing musicians and non-musicians as well as longitudinal studies with musicians. In contrast, studies that address the neural effects of short-term interventions whose duration lasts from minutes to hours are only beginning to be featured. Over the past decade, an increasing body of evidence has shown that short-term auditory interventions evoke rapid changes in neural activities, and oscillatory fluctuations can be observed even in the prestimulus period. In this scoping review, we divided the extracted neurophysiological studies into three groups to discuss neural activities with short-term auditory interventions: the pre-stimulus period, during stimulation, and a comparison of before and after stimulation. We show that oscillatory activities vary depending on the context of the stimuli and are greatly affected by the interplay of bottom-up and top-down modulational mechanisms, including attention. We conclude that the observed rapid changes in neural activitiesin the auditory cortex and the higher-order cognitive part of the brain are causally attributed to short-term auditory interventions.
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Affiliation(s)
- Kanon Kobayashi
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Yasushi Shiba
- Faculty of Medicine, University of Tokyo, Tokyo 113-8655, Japan
| | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Shinya Fujii
- Faculty of Environment and Information Studies, Keio University, Fujisawa 252-0816, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
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Luu P, Tucker DM, Friston K. From active affordance to active inference: vertical integration of cognition in the cerebral cortex through dual subcortical control systems. Cereb Cortex 2024; 34:bhad458. [PMID: 38044461 DOI: 10.1093/cercor/bhad458] [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: 07/17/2023] [Revised: 11/07/2023] [Accepted: 11/08/2023] [Indexed: 12/05/2023] Open
Abstract
In previous papers, we proposed that the dorsal attention system's top-down control is regulated by the dorsal division of the limbic system, providing a feedforward or impulsive form of control generating expectancies during active inference. In contrast, we proposed that the ventral attention system is regulated by the ventral limbic division, regulating feedback constraints and error-correction for active inference within the neocortical hierarchy. Here, we propose that these forms of cognitive control reflect vertical integration of subcortical arousal control systems that evolved for specific forms of behavior control. The feedforward impetus to action is regulated by phasic arousal, mediated by lemnothalamic projections from the reticular activating system of the lower brainstem, and then elaborated by the hippocampus and dorsal limbic division. In contrast, feedback constraint-based on environmental requirements-is regulated by the tonic activation furnished by collothalamic projections from the midbrain arousal control centers, and then sustained and elaborated by the amygdala, basal ganglia, and ventral limbic division. In an evolutionary-developmental analysis, understanding these differing forms of active affordance-for arousal and motor control within the subcortical vertebrate neuraxis-may help explain the evolution of active inference regulating the cognition of expectancy and error-correction within the mammalian 6-layered neocortex.
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Affiliation(s)
- Phan Luu
- Brain Electrophysiology Laboratory Company, Riverfront Research Park, 1776 Millrace Dr., Eugene, OR 97403, United States
- Department of Psychology, University of Oregon, Eugene, OR 97403, United States
| | - Don M Tucker
- Brain Electrophysiology Laboratory Company, Riverfront Research Park, 1776 Millrace Dr., Eugene, OR 97403, United States
- Department of Psychology, University of Oregon, Eugene, OR 97403, United States
| | - Karl Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3AR, United Kingdom
- VERSES AI Research Lab, Los Angeles, CA 90016, USA
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6
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Grundei M, Schmidt TT, Blankenburg F. A multimodal cortical network of sensory expectation violation revealed by fMRI. Hum Brain Mapp 2023; 44:5871-5891. [PMID: 37721377 PMCID: PMC10619418 DOI: 10.1002/hbm.26482] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 07/04/2023] [Accepted: 08/29/2023] [Indexed: 09/19/2023] Open
Abstract
The brain is subjected to multi-modal sensory information in an environment governed by statistical dependencies. Mismatch responses (MMRs), classically recorded with EEG, have provided valuable insights into the brain's processing of regularities and the generation of corresponding sensory predictions. Only few studies allow for comparisons of MMRs across multiple modalities in a simultaneous sensory stream and their corresponding cross-modal context sensitivity remains unknown. Here, we used a tri-modal version of the roving stimulus paradigm in fMRI to elicit MMRs in the auditory, somatosensory and visual modality. Participants (N = 29) were simultaneously presented with sequences of low and high intensity stimuli in each of the three senses while actively observing the tri-modal input stream and occasionally reporting the intensity of the previous stimulus in a prompted modality. The sequences were based on a probabilistic model, defining transition probabilities such that, for each modality, stimuli were more likely to repeat (p = .825) than change (p = .175) and stimulus intensities were equiprobable (p = .5). Moreover, each transition was conditional on the configuration of the other two modalities comprising global (cross-modal) predictive properties of the sequences. We identified a shared mismatch network of modality general inferior frontal and temporo-parietal areas as well as sensory areas, where the connectivity (psychophysiological interaction) between these regions was modulated during mismatch processing. Further, we found deviant responses within the network to be modulated by local stimulus repetition, which suggests highly comparable processing of expectation violation across modalities. Moreover, hierarchically higher regions of the mismatch network in the temporo-parietal area around the intraparietal sulcus were identified to signal cross-modal expectation violation. With the consistency of MMRs across audition, somatosensation and vision, our study provides insights into a shared cortical network of uni- and multi-modal expectation violation in response to sequence regularities.
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Affiliation(s)
- Miro Grundei
- Neurocomputation and Neuroimaging UnitFreie Universität BerlinBerlinGermany
- Berlin School of Mind and BrainHumboldt Universität zu BerlinBerlinGermany
| | | | - Felix Blankenburg
- Neurocomputation and Neuroimaging UnitFreie Universität BerlinBerlinGermany
- Berlin School of Mind and BrainHumboldt Universität zu BerlinBerlinGermany
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7
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Katsanevaki C, Bastos AM, Cagnan H, Bosman CA, Friston KJ, Fries P. Attentional effects on local V1 microcircuits explain selective V1-V4 communication. Neuroimage 2023; 281:120375. [PMID: 37714390 DOI: 10.1016/j.neuroimage.2023.120375] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/10/2023] [Accepted: 09/11/2023] [Indexed: 09/17/2023] Open
Abstract
Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.
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Affiliation(s)
- Christini Katsanevaki
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany.
| | - André M Bastos
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; Department of Psychology and Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37240, USA
| | - Hayriye Cagnan
- The Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK; Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
| | - Conrado A Bosman
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen 6525 EN, the Netherlands; Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam 1098 XH, the Netherlands
| | - Karl J Friston
- The Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany; Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen 6525 EN, the Netherlands
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8
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Malaia EA, Borneman SC, Borneman JD, Krebs J, Wilbur RB. Prediction underlying comprehension of human motion: an analysis of Deaf signer and non-signer EEG in response to visual stimuli. Front Neurosci 2023; 17:1218510. [PMID: 37901437 PMCID: PMC10602904 DOI: 10.3389/fnins.2023.1218510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 09/27/2023] [Indexed: 10/31/2023] Open
Abstract
Introduction Sensory inference and top-down predictive processing, reflected in human neural activity, play a critical role in higher-order cognitive processes, such as language comprehension. However, the neurobiological bases of predictive processing in higher-order cognitive processes are not well-understood. Methods This study used electroencephalography (EEG) to track participants' cortical dynamics in response to Austrian Sign Language and reversed sign language videos, measuring neural coherence to optical flow in the visual signal. We then used machine learning to assess entropy-based relevance of specific frequencies and regions of interest to brain state classification accuracy. Results EEG features highly relevant for classification were distributed across language processing-related regions in Deaf signers (frontal cortex and left hemisphere), while in non-signers such features were concentrated in visual and spatial processing regions. Discussion The results highlight functional significance of predictive processing time windows for sign language comprehension and biological motion processing, and the role of long-term experience (learning) in minimizing prediction error.
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Affiliation(s)
- Evie A. Malaia
- Department of Communicative Disorders, University of Alabama, Tuscaloosa, AL, United States
| | - Sean C. Borneman
- Department of Communicative Disorders, University of Alabama, Tuscaloosa, AL, United States
| | - Joshua D. Borneman
- Department of Linguistics, Purdue University, West Lafayette, IN, United States
| | - Julia Krebs
- Linguistics Department, University of Salzburg, Salzburg, Austria
- Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria
| | - Ronnie B. Wilbur
- Department of Linguistics, Purdue University, West Lafayette, IN, United States
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, United States
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Cappotto D, Luo D, Lai HW, Peng F, Melloni L, Schnupp JWH, Auksztulewicz R. "What" and "when" predictions modulate auditory processing in a mutually congruent manner. Front Neurosci 2023; 17:1180066. [PMID: 37781257 PMCID: PMC10540699 DOI: 10.3389/fnins.2023.1180066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 08/04/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli and their timing, both of which are known to interactively modulate sensory processing. In real-world stimulus streams such as music, regularities can occur at multiple levels, both in terms of contents (e.g., predictions relating to individual notes vs. their more complex groups) and timing (e.g., pertaining to timing between intervals vs. the overall beat of a musical phrase). However, it is unknown whether the brain integrates predictions in a manner that is mutually congruent (e.g., if "beat" timing predictions selectively interact with "what" predictions falling on pulses which define the beat), and whether integrating predictions in different timing conditions relies on dissociable neural correlates. Methods To address these questions, our study manipulated "what" and "when" predictions at different levels - (local) interval-defining and (global) beat-defining - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N = 20) performing a repetition detection task. Results Our results reveal that temporal predictions based on beat or interval timing modulated mismatch responses to violations of "what" predictions happening at the predicted time points, and that these modulations were shared between types of temporal predictions in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" predictions selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network. Discussion Taken together, these results suggest that the brain integrates different predictions with a high degree of mutual congruence, but in a shared and distributed cortical network. This finding contrasts with recent studies indicating separable mechanisms for beat-based and memory-based predictive processing.
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Affiliation(s)
- Drew Cappotto
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
- Ear Institute, University College London, London, United Kingdom
| | - Dan Luo
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Hiu Wai Lai
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Fei Peng
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Lucia Melloni
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | | | - Ryszard Auksztulewicz
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
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10
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Lorenzi RM, Geminiani A, Zerlaut Y, De Grazia M, Destexhe A, Gandini Wheeler-Kingshott CAM, Palesi F, Casellato C, D'Angelo E. A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics. PLoS Comput Biol 2023; 19:e1011434. [PMID: 37656758 PMCID: PMC10501640 DOI: 10.1371/journal.pcbi.1011434] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 09/14/2023] [Accepted: 08/15/2023] [Indexed: 09/03/2023] Open
Abstract
Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits. While MFs have been generated for the isocortex, they are still missing for other parts of the brain. Here we have designed and simulated a multi-layer MF of the cerebellar microcircuit (including Granule Cells, Golgi Cells, Molecular Layer Interneurons, and Purkinje Cells) and validated it against experimental data and the corresponding spiking neural network (SNN) microcircuit model. The cerebellar MF was built using a system of equations, where properties of neuronal populations and topological parameters are embedded in inter-dependent transfer functions. The model time constant was optimised using local field potentials recorded experimentally from acute mouse cerebellar slices as a template. The MF reproduced the average dynamics of different neuronal populations in response to various input patterns and predicted the modulation of the Purkinje Cells firing depending on cortical plasticity, which drives learning in associative tasks, and the level of feedforward inhibition. The cerebellar MF provides a computationally efficient tool for future investigations of the causal relationship between microscopic neuronal properties and ensemble brain activity in virtual brain models addressing both physiological and pathological conditions.
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Affiliation(s)
| | - Alice Geminiani
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Yann Zerlaut
- Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | | | | | - Claudia A M Gandini Wheeler-Kingshott
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, UCL, London, United Kingdom
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Claudia Casellato
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Egidio D'Angelo
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
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11
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Rosenblum L, Kreß A, Arikan BE, Straube B, Bremmer F. Neural correlates of visual and tactile path integration and their task related modulation. Sci Rep 2023; 13:9913. [PMID: 37337037 DOI: 10.1038/s41598-023-36797-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 06/09/2023] [Indexed: 06/21/2023] Open
Abstract
Self-motion induces sensory signals that allow to determine travel distance (path integration). For veridical path integration, one must distinguish self-generated from externally induced sensory signals. Predictive coding has been suggested to attenuate self-induced sensory responses, while task relevance can reverse the attenuating effect of prediction. But how is self-motion processing affected by prediction and task demands, and do effects generalize across senses? In this fMRI study, we investigated visual and tactile self-motion processing and its modulation by task demands. Visual stimuli simulated forward self-motion across a ground plane. Tactile self-motion stimuli were delivered by airflow across the subjects' forehead. In one task, subjects replicated a previously observed distance (Reproduction/Active; high behavioral demand) of passive self-displacement (Reproduction/Passive). In a second task, subjects travelled a self-chosen distance (Self/Active; low behavioral demand) which was recorded and played back to them (Self/Passive). For both tasks and sensory modalities, Active as compared to Passive trials showed enhancement in early visual areas and suppression in higher order areas of the inferior parietal lobule (IPL). Contrasting high and low demanding active trials yielded supramodal enhancement in the anterior insula. Suppression in the IPL suggests this area to be a comparator of sensory self-motion signals and predictions thereof.
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Affiliation(s)
- Lisa Rosenblum
- Department Neurophysics, Philipps-Universität Marburg, Karl-Von-Frisch-Straße 8a, 35043, Marburg, Germany.
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Giessen, Germany.
| | - Alexander Kreß
- Department Neurophysics, Philipps-Universität Marburg, Karl-Von-Frisch-Straße 8a, 35043, Marburg, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Giessen, Germany
| | - B Ezgi Arikan
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Giessen, Germany
- Department of Psychology, Justus-Liebig-Universität Giessen, Giessen, Germany
| | - Benjamin Straube
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Giessen, Germany
- Translational Neuroimaging Marburg, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Frank Bremmer
- Department Neurophysics, Philipps-Universität Marburg, Karl-Von-Frisch-Straße 8a, 35043, Marburg, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Giessen, Germany
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12
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Lao-Rodríguez AB, Przewrocki K, Pérez-González D, Alishbayli A, Yilmaz E, Malmierca MS, Englitz B. Neuronal responses to omitted tones in the auditory brain: A neuronal correlate for predictive coding. SCIENCE ADVANCES 2023; 9:eabq8657. [PMID: 37315139 DOI: 10.1126/sciadv.abq8657] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 05/09/2023] [Indexed: 06/16/2023]
Abstract
Prediction provides key advantages for survival, and cognitive studies have demonstrated that the brain computes multilevel predictions. Evidence for predictions remains elusive at the neuronal level because of the complexity of separating neural activity into predictions and stimulus responses. We overcome this challenge by recording from single neurons from cortical and subcortical auditory regions in anesthetized and awake preparations, during unexpected stimulus omissions interspersed in a regular sequence of tones. We find a subset of neurons that responds reliably to omitted tones. In awake animals, omission responses are similar to anesthetized animals, but larger and more frequent, indicating that the arousal and attentional state levels affect the degree to which predictions are neuronally represented. Omission-sensitive neurons also responded to frequency deviants, with their omission responses getting emphasized in the awake state. Because omission responses occur in the absence of sensory input, they provide solid and empirical evidence for the implementation of a predictive process.
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Affiliation(s)
- Ana B Lao-Rodríguez
- Cognitive and Auditory Neuroscience Laboratory (CANELAB), Institute of Neuroscience of Castilla y León, University of Salamanca, Salamanca, Spain
- Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Karol Przewrocki
- Computational Neuroscience Lab, Department of Neurophysiology, Donders Centre of Neuroscience, Nijmegen, Netherlands
| | - David Pérez-González
- Cognitive and Auditory Neuroscience Laboratory (CANELAB), Institute of Neuroscience of Castilla y León, University of Salamanca, Salamanca, Spain
- Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- Department of Basic Psychology, Psychobiology and Methodology of Behavioral Sciences, University of Salamanca, Salamanca, Spain
| | - Artoghrul Alishbayli
- Computational Neuroscience Lab, Department of Neurophysiology, Donders Centre of Neuroscience, Nijmegen, Netherlands
| | - Evrim Yilmaz
- Computational Neuroscience Lab, Department of Neurophysiology, Donders Centre of Neuroscience, Nijmegen, Netherlands
| | - Manuel S Malmierca
- Cognitive and Auditory Neuroscience Laboratory (CANELAB), Institute of Neuroscience of Castilla y León, University of Salamanca, Salamanca, Spain
- Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- Department of Cell Biology and Pathology, University of Salamanca, Salamanca, Spain
| | - Bernhard Englitz
- Computational Neuroscience Lab, Department of Neurophysiology, Donders Centre of Neuroscience, Nijmegen, Netherlands
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13
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Male AG, O’Shea RP. Attention is required for canonical brain signature of prediction error despite early encoding of the stimuli. PLoS Biol 2023; 21:e3001866. [PMID: 37339145 PMCID: PMC10281583 DOI: 10.1371/journal.pbio.3001866] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 05/11/2023] [Indexed: 06/22/2023] Open
Abstract
Prediction error is a basic component of predictive-coding theory of brain processing. According to the theory, each stage of brain processing of sensory information generates a model of the current sensory input; subsequent input is compared against the model and only if there is a mismatch, a prediction error, is further processing performed. Recently, Smout and colleagues found that a signature of prediction error, the visual (v) mismatch negativity (MMN), for a fundamental property of visual input-its orientation-was absent without endogenous attention on the stimuli. This is remarkable because the weight of evidence for MMNs from audition and vision is that they occur without endogenous attention. To resolve this discrepancy, we conducted an experiment addressing 2 alternative explanations for Smout and colleagues' finding: that it was from a lack of reproducibility or that participants' visual systems did not encode the stimuli when attention was on something else. We conducted a similar experiment to that of Smout and colleagues. We showed 21 participants sequences of identically oriented Gabor patches, standards, and, unpredictably, otherwise identical, Gabor patches differing in orientation by ±15°, ±30°, and ±60°, deviants. To test whether participants encoded the orientation of the standards, we varied the number of standards preceding a deviant, allowing us to search for a decrease in activity with the number of repetitions of standards-repetition suppression. We diverted participants' attention from the oriented stimuli with a central, letter-detection task. We reproduced Smout and colleagues' finding of no vMMN without endogenous attention, strengthening their finding. We found that our participants showed repetition suppression: They did encode the stimuli preattentively. We also found early processing of deviants. We discuss various explanations why the earlier processing did not extend into the vMMN time window, including low precision of prediction.
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Affiliation(s)
- Alie G. Male
- Discipline of Psychology, College of Science, Health, Engineering and Education, Murdoch University, Perth, Australia
- Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, United States of America
| | - Robert P. O’Shea
- Discipline of Psychology, College of Science, Health, Engineering and Education, Murdoch University, Perth, Australia
- Wilhelm Wundt Institute for Psychology, University of Leipzig, Leipzig, Germany
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14
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Auksztulewicz R, Rajendran VG, Peng F, Schnupp JWH, Harper NS. Omission responses in local field potentials in rat auditory cortex. BMC Biol 2023; 21:130. [PMID: 37254137 DOI: 10.1186/s12915-023-01592-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 04/11/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Non-invasive recordings of gross neural activity in humans often show responses to omitted stimuli in steady trains of identical stimuli. This has been taken as evidence for the neural coding of prediction or prediction error. However, evidence for such omission responses from invasive recordings of cellular-scale responses in animal models is scarce. Here, we sought to characterise omission responses using extracellular recordings in the auditory cortex of anaesthetised rats. We profiled omission responses across local field potentials (LFP), analogue multiunit activity (AMUA), and single/multi-unit spiking activity, using stimuli that were fixed-rate trains of acoustic noise bursts where 5% of bursts were randomly omitted. RESULTS Significant omission responses were observed in LFP and AMUA signals, but not in spiking activity. These omission responses had a lower amplitude and longer latency than burst-evoked sensory responses, and omission response amplitude increased as a function of the number of preceding bursts. CONCLUSIONS Together, our findings show that omission responses are most robustly observed in LFP and AMUA signals (relative to spiking activity). This has implications for models of cortical processing that require many neurons to encode prediction errors in their spike output.
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Affiliation(s)
- Ryszard Auksztulewicz
- Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany.
- Dept of Neuroscience, City University of Hong Kong, Hong Kong, Hong Kong S.A.R..
| | | | - Fei Peng
- Dept of Neuroscience, City University of Hong Kong, Hong Kong, Hong Kong S.A.R
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15
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Kwasa J, Peterson HM, Karrobi K, Jones L, Parker T, Nickerson N, Wood S. Demographic reporting and phenotypic exclusion in fNIRS. Front Neurosci 2023; 17:1086208. [PMID: 37229429 PMCID: PMC10203458 DOI: 10.3389/fnins.2023.1086208] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 04/05/2023] [Indexed: 05/27/2023] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) promises to be a leading non-invasive neuroimaging method due to its portability and low cost. However, concerns are rising over its inclusivity of all skin tones and hair types (Parker and Ricard, 2022, Webb et al., 2022). Functional NIRS relies on direct contact of light-emitting optodes to the scalp, which can be blocked more by longer, darker, and especially curlier hair. Additionally, NIR light can be attenuated by melanin, which is accounted for in neither fNIRS hardware nor analysis methods. Recent work has shown that overlooking these considerations in other modalities like EEG leads to the disproportionate exclusion of individuals with these phenotypes-especially Black people-in both clinical and research literature (Choy, 2020; Bradford et al., 2022; Louis et al., 2023). In this article, we sought to determine if (Jöbsis, 1977) biomedical optics developers and researchers report fNIRS performance variability between skin tones and hair textures, (2a) fNIRS neuroscience practitioners report phenotypic and demographic details in their articles, and thus, (2b) is a similar pattern of participant exclusion found in EEG also present in the fNIRS literature. We present a literature review of top Biomedical Optics and Human Neuroscience journals, showing that demographic and phenotypic reporting is unpopular in both fNIRS development and neuroscience applications. We conclude with a list of recommendations to the fNIRS community including examples of Black researchers addressing these issues head-on, inclusive best practices for fNIRS researchers, and recommendations to funding and regulatory bodies to achieve an inclusive neuroscience enterprise in fNIRS and beyond.
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Affiliation(s)
- Jasmine Kwasa
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Hannah M. Peterson
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, United States
| | - Kavon Karrobi
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Lietsel Jones
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United States
| | - Termara Parker
- Interdepartmental Neuroscience Program, School of Medicine, Yale University, New Haven, CT, United States
| | - Nia Nickerson
- Combined Program in Education and Psychology, University of Michigan, Ann Arbor, MI, United States
| | - Sossena Wood
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
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16
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Xie Z, Brodbeck C, Chandrasekaran B. Cortical Tracking of Continuous Speech Under Bimodal Divided Attention. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2023; 4:318-343. [PMID: 37229509 PMCID: PMC10205152 DOI: 10.1162/nol_a_00100] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/11/2023] [Indexed: 05/27/2023]
Abstract
Speech processing often occurs amid competing inputs from other modalities, for example, listening to the radio while driving. We examined the extent to which dividing attention between auditory and visual modalities (bimodal divided attention) impacts neural processing of natural continuous speech from acoustic to linguistic levels of representation. We recorded electroencephalographic (EEG) responses when human participants performed a challenging primary visual task, imposing low or high cognitive load while listening to audiobook stories as a secondary task. The two dual-task conditions were contrasted with an auditory single-task condition in which participants attended to stories while ignoring visual stimuli. Behaviorally, the high load dual-task condition was associated with lower speech comprehension accuracy relative to the other two conditions. We fitted multivariate temporal response function encoding models to predict EEG responses from acoustic and linguistic speech features at different representation levels, including auditory spectrograms and information-theoretic models of sublexical-, word-form-, and sentence-level representations. Neural tracking of most acoustic and linguistic features remained unchanged with increasing dual-task load, despite unambiguous behavioral and neural evidence of the high load dual-task condition being more demanding. Compared to the auditory single-task condition, dual-task conditions selectively reduced neural tracking of only some acoustic and linguistic features, mainly at latencies >200 ms, while earlier latencies were surprisingly unaffected. These findings indicate that behavioral effects of bimodal divided attention on continuous speech processing occur not because of impaired early sensory representations but likely at later cognitive processing stages. Crossmodal attention-related mechanisms may not be uniform across different speech processing levels.
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Affiliation(s)
- Zilong Xie
- School of Communication Science and Disorders, Florida State University, Tallahassee, FL, USA
| | - Christian Brodbeck
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
| | - Bharath Chandrasekaran
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, USA
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17
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Todd J, Howard Z, Auksztulewicz R, Salisbury D. Computational Modeling of Oddball Sequence Processing Exposes Common and Differential Auditory Network Changes in First-Episode Schizophrenia-Spectrum Disorders and Schizophrenia. Schizophr Bull 2023; 49:407-416. [PMID: 36318221 PMCID: PMC10016421 DOI: 10.1093/schbul/sbac153] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND HYPOTHESIS Differences in sound relevance filtering in schizophrenia are proposed to represent a key index of biological changes in brain function in the illness. This study featured a computational modeling approach to test the hypothesis that processing differences might already be evident in first-episode, becoming more pronounced in the established illness. STUDY DESIGN Auditory event-related potentials to a typical oddball sequence (rare pitch deviations amongst regular sounds) were recorded from 90 persons with schizophrenia-spectrum disorders (40 first-episode schizophrenia-spectrum, 50 established illness) and age-matched healthy controls. The data were analyzed using dynamic causal modeling to identify the changes in effective connectivity that best explained group differences. STUDY RESULTS Group differences were linked to intrinsic (within brain region) connectivity changes. In activity-dependent measures these were restricted to the left auditory cortex in first-episode schizophrenia-spectrum but were more widespread in the established illness. Modeling suggested that both established illness and first-episode schizophrenia-spectrum groups expressed significantly lower inhibition of inhibitory interneuron activity and altered gain on superficial pyramidal cells with the data indicative of differences in both putative N-methyl-d-aspartate glutamate receptor activity-dependent plasticity and classic neuromodulation. CONCLUSIONS The study provides further support for the notion that examining the ability to alter responsiveness to structured sound sequences in schizophrenia and first-episode schizophrenia-spectrum could be informative to uncovering the nature and progression of changes in brain function during the illness. Furthermore, modeling suggested that limited differences present at first-episode schizophrenia-spectrum may become more expansive with illness progression.
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Affiliation(s)
- Juanita Todd
- School of Psychological Sciences, University of Newcastle, Australia.,Hunter Medical Research Foundation, Newcastle, Australia
| | - Zachary Howard
- School of Psychological Science, University of Western, Australia
| | - Ryszard Auksztulewicz
- European Neuroscience Institute, A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Göttingen, Germany
| | - Dean Salisbury
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA
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18
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Event-Related Potentials Index Prediction Error Signalling During Perceptual Processing of Emotional Facial Expressions. Brain Topogr 2023; 36:419-432. [PMID: 36917320 PMCID: PMC10164013 DOI: 10.1007/s10548-023-00951-2] [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: 02/25/2022] [Accepted: 02/22/2023] [Indexed: 03/15/2023]
Abstract
Humans use socially relevant stimuli to guide perceptual processing of the surrounding environment, with emotional stimuli receiving preferential attention due to their social importance. Predictive coding theory asserts this cognitive process occurs efficiently by combining predictions about what is to be perceived with incoming sensory information, generating prediction errors that are then used to update future predictions. Recent evidence has identified differing neural activity that demonstrates how spatial and feature-based attention may interact with prediction, yet how emotion-guided attention may influence this relationship remains unknown. In the present study, participants viewed a display of two faces in which attention, prediction, and emotion were manipulated, and responded to a face expressing a specific emotion (anger or happiness). The N170 was found to be enhanced by unpredictable as opposed to predictable stimuli, indicating that it indexes general prediction error signalling processes. The N300 amplitudes were also enhanced by unpredictable stimuli, but they were also affected by the attentional status of angry but not happy faces, suggesting that there are differences in prediction error processes indexed by the N170 and N300. Overall, the findings suggest that the N170 and N300 both index violations of expectation for spatial manipulations of stimuli in accordance with prediction error responding processes.
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19
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Expectation violations enhance neuronal encoding of sensory information in mouse primary visual cortex. Nat Commun 2023; 14:1196. [PMID: 36864037 PMCID: PMC9981605 DOI: 10.1038/s41467-023-36608-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 02/08/2023] [Indexed: 03/04/2023] Open
Abstract
The response of cortical neurons to sensory stimuli is shaped both by past events (adaptation) and the expectation of future events (prediction). Here we employed a visual stimulus paradigm with different levels of predictability to characterise how expectation influences orientation selectivity in the primary visual cortex (V1) of male mice. We recorded neuronal activity using two-photon calcium imaging (GCaMP6f) while animals viewed sequences of grating stimuli which either varied randomly in their orientations or rotated predictably with occasional transitions to an unexpected orientation. For single neurons and the population, there was significant enhancement in the gain of orientation-selective responses to unexpected gratings. This gain-enhancement for unexpected stimuli was prominent in both awake and anaesthetised mice. We implemented a computational model to demonstrate how trial-to-trial variability in neuronal responses were best characterised when adaptation and expectation effects were combined.
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20
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McParlin Z, Cerritelli F, Manzotti A, Friston KJ, Esteves JE. Therapeutic touch and therapeutic alliance in pediatric care and neonatology: An active inference framework. Front Pediatr 2023; 11:961075. [PMID: 36923275 PMCID: PMC10009260 DOI: 10.3389/fped.2023.961075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 02/07/2023] [Indexed: 03/03/2023] Open
Abstract
Therapeutic affective touch has been recognized as essential for survival, nurturing supportive interpersonal interactions, accelerating recovery-including reducing hospitalisations, and promoting overall health and building robust therapeutic alliances. Through the lens of active inference, we present an integrative model, combining therapeutic touch and communication, to achieve biobehavioural synchrony. This model speaks to how the brain develops a generative model required for recovery, developing successful therapeutic alliances, and regulating allostasis within paediatric manual therapy. We apply active inference to explain the neurophysiological and behavioural mechanisms that underwrite the development and maintenance of synchronous relationships through touch. This paper foregrounds the crucial role of therapeutic touch in developing a solid therapeutic alliance, the clinical effectiveness of paediatric care, and triadic synchrony between health care practitioner, caregiver, and infant in a variety of clinical situations. We start by providing a brief overview of the significance and clinical role of touch in the development of social interactions in infants; facilitating a positive therapeutic alliance and restoring homeostasis through touch to allow a more efficient process of allostatic regulation. Moreover, we explain the role of CT tactile afferents in achieving positive clinical outcomes and updating prior beliefs. We then discuss how touch is implemented in treatment sessions to promote cooperative interactions in the clinic and facilitate theory of mind. This underwrites biobehavioural synchrony, epistemic trust, empathy, and the resolution of uncertainty. The ensuing framework is underpinned by a critical application of the active inference framework to the fields of pediatrics and neonatology.
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Affiliation(s)
- Zoe McParlin
- Foundation COME Collaboration, Clinical-Based Human Research Department, Pescara, Italy
| | - Francesco Cerritelli
- Division of Neonatology, “V. Buzzi” Children's Hospital, ASST-FBF-Sacco, Milan, Italy
| | - Andrea Manzotti
- Foundation COME Collaboration, Clinical-Based Human Research Department, Pescara, Italy
- Division of Neonatology, “V. Buzzi” Children's Hospital, ASST-FBF-Sacco, Milan, Italy
- Research Department, SOMA, Istituto Osteopatia Milano, Milan, Italy
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, Queen Square, London, United Kingdom
| | - Jorge E Esteves
- Foundation COME Collaboration, Clinical-Based Human Research Department, Pescara, Italy
- Malta ICOM Educational, Malta, Finland
- Research Department, University College of Osteopathy, Research Department, London, United Kingdom
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21
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Luo D, Liu J, Auksztulewicz R, Wing Yip TK, Kanold PO, Schnupp JW. Hierarchical Deviant Processing in Auditory Cortex of Awake Mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524413. [PMID: 36711896 PMCID: PMC9882249 DOI: 10.1101/2023.01.18.524413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Detecting patterns, and noticing unexpected pattern changes, in the environment is a vital aspect of sensory processing. Adaptation and prediction error responses are two components of neural processing related to these tasks, and previous studies in the auditory system in rodents show that these two components are partially dissociable in terms of the topography and latency of neural responses to sensory deviants. However, many previous studies have focused on repetitions of single stimuli, such as pure tones, which have limited ecological validity. In this study, we tested whether the auditory cortical activity shows adaptation to repetition of more complex sound patterns (bisyllabic pairs). Specifically, we compared neural responses to violations of sequences based on single stimulus probability only, against responses to more complex violations based on stimulus order. We employed an auditory oddball paradigm and monitored the auditory cortex (ACtx) activity of awake mice (N=8) using wide-field calcium imaging. We found that cortical responses were sensitive both to single stimulus probabilities and to more global stimulus patterns, as mismatch signals were elicited following both substitution deviants and transposition deviants. Notably, A2 area elicited larger mismatch signaling to those deviants than primary ACtx (A1), which suggests a hierarchical gradient of prediction error signaling in the auditory cortex. Such a hierarchical gradient was observed for late but not early peaks of calcium transients to deviants, suggesting that the late part of the deviant response may reflect prediction error signaling in response to more complex sensory pattern violations.
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22
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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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23
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Sarasso P, Ronga I, Del Fante E, Barbieri P, Lozzi I, Rosaia N, Cicerale A, Neppi-Modona M, Sacco K. Physical but not virtual presence of others potentiates implicit and explicit learning. Sci Rep 2022; 12:21205. [PMID: 36481679 PMCID: PMC9732282 DOI: 10.1038/s41598-022-25273-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 11/28/2022] [Indexed: 12/13/2022] Open
Abstract
E-learning activities are becoming more and more common. Whilst it is well known that the physical presence of others motivates individuals to engage in perceptual and learning tasks, systematic investigations comparing the effects of physical and virtual co-presence of others on knowledge acquisition are still scarce. Here we investigate the effects of physical and virtual co-presence of others on explicit and implicit learning. In Experiment 1 (discovery sample), retrieval accuracy in a spatial memory task and EEG indexes (mismatch negativity-MMN) of implicit perceptual learning were recorded when participants were alone or in presence of another individual. In Experiment 2 (replicating sample), we added a "virtual" condition, where the same tasks were performed during a video-conference call. In both experiments, MMN was demonstrated to encode for perceptual learning as revealed by the significant correlation with Bayesian Surprise (a consolidated information-theoretic index of Bayesian learning). Furthermore, In Experiments 1 and 2 physical co-presence systematically ameliorated memorization performances and increased MMN indexes related to implicit learning. These positive effects were absent in the virtual condition, thus suggesting that only physical, but not virtual co-presence is effective in potentiating learning dynamics.
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Affiliation(s)
- Pietro Sarasso
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Irene Ronga
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Elena Del Fante
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Paolo Barbieri
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Irene Lozzi
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Nicola Rosaia
- grid.38142.3c000000041936754XDepartment of Economics, Harvard University, Cambridge, MA USA
| | - Alessandro Cicerale
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Marco Neppi-Modona
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
| | - Katiuscia Sacco
- grid.7605.40000 0001 2336 6580BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Via Verdi, 10, 10124 Turin, Italy
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24
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Niedernhuber M, Raimondo F, Sitt JD, Bekinschtein TA. Sensory Target Detection at Local and Global Timescales Reveals a Hierarchy of Supramodal Dynamics in the Human Cortex. J Neurosci 2022; 42:8729-8741. [PMID: 36223999 PMCID: PMC9671580 DOI: 10.1523/jneurosci.0658-22.2022] [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: 04/04/2022] [Revised: 06/24/2022] [Accepted: 07/20/2022] [Indexed: 11/21/2022] Open
Abstract
To ensure survival in a dynamic environment, the human neocortex monitors input streams from different sensory organs for important sensory events. Which principles govern whether different senses share common or modality-specific brain networks for sensory target detection? We examined whether complex targets evoke sustained supramodal activity while simple targets rely on modality-specific networks with short-lived supramodal contributions. In a series of hierarchical multisensory target detection studies (n = 77, of either sex) using EEG, we applied a temporal cross-decoding approach to dissociate supramodal and modality-specific cortical dynamics elicited by rule-based global and feature-based local sensory deviations within and between the visual, somatosensory, and auditory modality. Our data show that each sense implements a cortical hierarchy orchestrating supramodal target detection responses, which operate at local and global timescales in successive processing stages. Across different sensory modalities, simple feature-based sensory deviations presented in temporal vicinity to a monotonous input stream triggered a mismatch negativity-like local signal which decayed quickly and early, whereas complex rule-based targets tracked across time evoked a P3b-like global neural response which generalized across a late time window. Converging results from temporal cross-modality decoding analyses across different datasets, we reveal that global neural responses are sustained in a supramodal higher-order network, whereas local neural responses canonically thought to rely on modality-specific regions evolve into short-lived supramodal activity. Together, our findings demonstrate that cortical organization largely follows a gradient in which short-lived modality-specific as well as supramodal processes dominate local responses, whereas higher-order processes encode temporally extended abstract supramodal information fed forward from modality-specific cortices.SIGNIFICANCE STATEMENT Each sense supports a cortical hierarchy of processes tracking deviant sensory events at multiple timescales. Conflicting evidence produced a lively debate around which of these processes are supramodal. Here, we manipulated the temporal complexity of auditory, tactile, and visual targets to determine whether cortical local and global ERP responses to sensory targets share cortical dynamics between the senses. Using temporal cross-decoding, we found that temporally complex targets elicit a supramodal sustained response. Conversely, local responses to temporally confined targets typically considered modality-specific rely on early short-lived supramodal activation. Our finding provides evidence for a supramodal gradient supporting sensory target detection in the cortex, with implications for multiple fields in which these responses are studied (e.g., predictive coding, consciousness, and attention).
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Affiliation(s)
- Maria Niedernhuber
- Cambridge Consciousness and Cognition Lab, Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom
- Body, Self, and Plasticity Lab, Department of Psychology, University of Zurich, Zurich, 8050, Switzerland
| | - Federico Raimondo
- Brain and Spine Institute, Pitiè Salpêtrière Hospital, Paris, 75013, France
- National Institute of Health and Medical Research, Paris, 75013, France
- Institute of Neuroscience and Medicine, Brain & Behaviour, Research Centre Jülich, Jülich, 52425, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany
| | - Jacobo D. Sitt
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, APHP, Hôpital de la Pitié Salpêtrière, Paris, 75013, France
| | - Tristan A. Bekinschtein
- Cambridge Consciousness and Cognition Lab, Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom
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25
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Insa S, Felix L, Peters A, Maximilian B, Thomas S. Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation. Neuroimage 2022; 262:119530. [DOI: 10.1016/j.neuroimage.2022.119530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 06/07/2022] [Accepted: 08/01/2022] [Indexed: 10/31/2022] Open
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26
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Sarasso P, Francesetti G, Roubal J, Gecele M, Ronga I, Neppi-Modona M, Sacco K. Beauty and Uncertainty as Transformative Factors: A Free Energy Principle Account of Aesthetic Diagnosis and Intervention in Gestalt Psychotherapy. Front Hum Neurosci 2022; 16:906188. [PMID: 35911596 PMCID: PMC9325967 DOI: 10.3389/fnhum.2022.906188] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Drawing from field theory, Gestalt therapy conceives psychological suffering and psychotherapy as two intentional field phenomena, where unprocessed and chaotic experiences seek the opportunity to emerge and be assimilated through the contact between the patient and the therapist (i.e., the intentionality of contacting). This therapeutic approach is based on the therapist’s aesthetic experience of his/her embodied presence in the flow of the healing process because (1) the perception of beauty can provide the therapist with feedback on the assimilation of unprocessed experiences; (2) the therapist’s attentional focus on intrinsic aesthetic diagnostic criteria can facilitate the modification of rigid psychopathological fields by supporting the openness to novel experiences. The aim of the present manuscript is to review recent evidence from psychophysiology, neuroaesthetic research, and neurocomputational models of cognition, such as the free energy principle (FEP), which support the notion of the therapeutic potential of aesthetic sensibility in Gestalt psychotherapy. Drawing from neuroimaging data, psychophysiology and recent neurocognitive accounts of aesthetic perception, we propose a novel interpretation of the sense of beauty as a self-generated reward motivating us to assimilate an ever-greater spectrum of sensory and affective states in our predictive representation of ourselves and the world and supporting the intentionality of contact. Expecting beauty, in the psychotherapeutic encounter, can help therapists tolerate uncertainty avoiding impulsive behaviours and to stay tuned to the process of change.
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Affiliation(s)
- Pietro Sarasso
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
- *Correspondence: Pietro Sarasso,
| | - Gianni Francesetti
- International Institute for Gestalt Therapy and Psychopathology, Turin Center for Gestalt Therapy, Turin, Italy
| | - Jan Roubal
- Psychotherapy Training Gestalt Studia, Training in Psychotherapy Integration, Center for Psychotherapy Research in Brno, Masaryk University, Brno, Czechia
| | - Michela Gecele
- International Institute for Gestalt Therapy and Psychopathology, Turin Center for Gestalt Therapy, Turin, Italy
| | - Irene Ronga
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
| | - Marco Neppi-Modona
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
| | - Katiuscia Sacco
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, Turin, Italy
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27
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McParlin Z, Cerritelli F, Rossettini G, Friston KJ, Esteves JE. Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Biobehavioural Synchrony in Musculoskeletal Care. Front Behav Neurosci 2022; 16:897247. [PMID: 35846789 PMCID: PMC9280207 DOI: 10.3389/fnbeh.2022.897247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/24/2022] [Indexed: 12/05/2022] Open
Abstract
Touch is recognised as crucial for survival, fostering cooperative communication, accelerating recovery, reducing hospital stays, and promoting overall wellness and the therapeutic alliance. In this hypothesis and theory paper, we present an entwined model that combines touch for alignment and active inference to explain how the brain develops "priors" necessary for the health care provider to engage with the patient effectively. We appeal to active inference to explain the empirically integrative neurophysiological and behavioural mechanisms that underwrite synchronous relationships through touch. Specifically, we offer a formal framework for understanding - and explaining - the role of therapeutic touch and hands-on care in developing a therapeutic alliance and synchrony between health care providers and their patients in musculoskeletal care. We first review the crucial importance of therapeutic touch and its clinical role in facilitating the formation of a solid therapeutic alliance and in regulating allostasis. We then consider how touch is used clinically - to promote cooperative communication, demonstrate empathy, overcome uncertainty, and infer the mental states of others - through the lens of active inference. We conclude that touch plays a crucial role in achieving successful clinical outcomes and adapting previous priors to create intertwined beliefs. The ensuing framework may help healthcare providers in the field of musculoskeletal care to use hands-on care to strengthen the therapeutic alliance, minimise prediction errors (a.k.a., free energy), and thereby promote recovery from physical and psychological impairments.
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Affiliation(s)
- Zoe McParlin
- Clinical-Based Human Research Department, Foundation COME Collaboration, Pescara, Italy
| | - Francesco Cerritelli
- Clinical-Based Human Research Department, Foundation COME Collaboration, Pescara, Italy
| | | | - Karl J. Friston
- Institute of Neurology, Wellcome Centre for Human Neuroimaging, London, United Kingdom
| | - Jorge E. Esteves
- Clinical-Based Human Research Department, Foundation COME Collaboration, Pescara, Italy
- Malta ICOM Educational, Gzira, Malta
- University College of Osteopathy, London, United Kingdom
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28
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Lecaignard F, Bertrand R, Brunner P, Caclin A, Schalk G, Mattout J. Dynamics of Oddball Sound Processing: Trial-by-Trial Modeling of ECoG Signals. Front Hum Neurosci 2022; 15:794654. [PMID: 35221952 PMCID: PMC8866734 DOI: 10.3389/fnhum.2021.794654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 12/07/2021] [Indexed: 11/21/2022] Open
Abstract
Recent computational models of perception conceptualize auditory oddball responses as signatures of a (Bayesian) learning process, in line with the influential view of the mismatch negativity (MMN) as a prediction error signal. Novel MMN experimental paradigms have put an emphasis on neurophysiological effects of manipulating regularity and predictability in sound sequences. This raises the question of the contextual adaptation of the learning process itself, which on the computational side speaks to the mechanisms of gain-modulated (or precision-weighted) prediction error. In this study using electrocorticographic (ECoG) signals, we manipulated the predictability of oddball sound sequences with two objectives: (i) Uncovering the computational process underlying trial-by-trial variations of the cortical responses. The fluctuations between trials, generally ignored by approaches based on averaged evoked responses, should reflect the learning involved. We used a general linear model (GLM) and Bayesian Model Reduction (BMR) to assess the respective contributions of experimental manipulations and learning mechanisms under probabilistic assumptions. (ii) To validate and expand on previous findings regarding the effect of changes in predictability using simultaneous EEG-MEG recordings. Our trial-by-trial analysis revealed only a few stimulus-responsive sensors but the measured effects appear to be consistent over subjects in both time and space. In time, they occur at the typical latency of the MMN (between 100 and 250 ms post-stimulus). In space, we found a dissociation between time-independent effects in more anterior temporal locations and time-dependent (learning) effects in more posterior locations. However, we could not observe any clear and reliable effect of our manipulation of predictability modulation onto the above learning process. Overall, these findings clearly demonstrate the potential of trial-to-trial modeling to unravel perceptual learning processes and their neurophysiological counterparts.
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Affiliation(s)
- Françoise Lecaignard
- Lyon Neuroscience Research Center, CRNL, INSERM, U1028, CNRS, UMR 5292, Lyon, France
- University Lyon 1, Lyon, France
| | - Raphaëlle Bertrand
- Lyon Neuroscience Research Center, CRNL, INSERM, U1028, CNRS, UMR 5292, Lyon, France
- University Lyon 1, Lyon, France
| | - Peter Brunner
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States
- Department of Neurology, Albany Medical College, Albany, NY, United States
- National Center for Adaptive Neurotechnologies, Albany, NY, United States
| | - Anne Caclin
- Lyon Neuroscience Research Center, CRNL, INSERM, U1028, CNRS, UMR 5292, Lyon, France
- University Lyon 1, Lyon, France
| | - Gerwin Schalk
- National Center for Adaptive Neurotechnologies, Albany, NY, United States
| | - Jérémie Mattout
- Lyon Neuroscience Research Center, CRNL, INSERM, U1028, CNRS, UMR 5292, Lyon, France
- University Lyon 1, Lyon, France
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29
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Quiroga-Martinez DR, Hansen NC, Højlund A, Pearce M, Brattico E, Holmes E, Friston K, Vuust P. Musicianship and melodic predictability enhance neural gain in auditory cortex during pitch deviance detection. Hum Brain Mapp 2021; 42:5595-5608. [PMID: 34459062 PMCID: PMC8559476 DOI: 10.1002/hbm.25638] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 07/22/2021] [Accepted: 08/07/2021] [Indexed: 11/10/2022] Open
Abstract
When listening to music, pitch deviations are more salient and elicit stronger prediction error responses when the melodic context is predictable and when the listener is a musician. Yet, the neuronal dynamics and changes in connectivity underlying such effects remain unclear. Here, we employed dynamic causal modeling (DCM) to investigate whether the magnetic mismatch negativity response (MMNm)-and its modulation by context predictability and musical expertise-are associated with enhanced neural gain of auditory areas, as a plausible mechanism for encoding precision-weighted prediction errors. Using Bayesian model comparison, we asked whether models with intrinsic connections within primary auditory cortex (A1) and superior temporal gyrus (STG)-typically related to gain control-or extrinsic connections between A1 and STG-typically related to propagation of prediction and error signals-better explained magnetoencephalography responses. We found that, compared to regular sounds, out-of-tune pitch deviations were associated with lower intrinsic (inhibitory) connectivity in A1 and STG, and lower backward (inhibitory) connectivity from STG to A1, consistent with disinhibition and enhanced neural gain in these auditory areas. More predictable melodies were associated with disinhibition in right A1, while musicianship was associated with disinhibition in left A1 and reduced connectivity from STG to left A1. These results indicate that musicianship and melodic predictability, as well as pitch deviations themselves, enhance neural gain in auditory cortex during deviance detection. Our findings are consistent with predictive processing theories suggesting that precise and informative error signals are selected by the brain for subsequent hierarchical processing.
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Affiliation(s)
- David R Quiroga-Martinez
- Center for Music in the Brain, Aarhus University & Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
| | - Niels Christian Hansen
- Center for Music in the Brain, Aarhus University & Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark.,Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark
| | - Andreas Højlund
- Center for Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Marcus Pearce
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Elvira Brattico
- Center for Music in the Brain, Aarhus University & Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark.,Department of Education, Psychology and Communication, University of Bari Aldo Moro, Bari, Italy
| | - Emma Holmes
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Karl Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Peter Vuust
- Center for Music in the Brain, Aarhus University & Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
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30
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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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31
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Precision control for a flexible body representation. Neurosci Biobehav Rev 2021; 134:104401. [PMID: 34736884 DOI: 10.1016/j.neubiorev.2021.10.023] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 11/24/2022]
Abstract
Adaptive body representation requires the continuous integration of multisensory inputs within a flexible 'body model' in the brain. The present review evaluates the idea that this flexibility is augmented by the contextual modulation of sensory processing 'top-down'; which can be described as precision control within predictive coding formulations of Bayesian inference. Specifically, I focus on the proposal that an attenuation of proprioception may facilitate the integration of conflicting visual and proprioceptive bodily cues. Firstly, I review empirical work suggesting that the processing of visual vs proprioceptive body position information can be contextualised 'top-down'; for instance, by adopting specific attentional task sets. Building up on this, I review research showing a similar contextualisation of visual vs proprioceptive information processing in the rubber hand illusion and in visuomotor adaptation. Together, the reviewed literature suggests that proprioception, despite its indisputable importance for body perception and action control, can be attenuated top-down (through precision control) to facilitate the contextual adaptation of the brain's body model to novel visual feedback.
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32
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SanMiguel I, Costa-Faidella J, Lugo ZR, Vilella E, Escera C. Standard Tone Stability as a Manipulation of Precision in the Oddball Paradigm: Modulation of Prediction Error Responses to Fixed-Probability Deviants. Front Hum Neurosci 2021; 15:734200. [PMID: 34650417 PMCID: PMC8505747 DOI: 10.3389/fnhum.2021.734200] [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: 06/30/2021] [Accepted: 09/09/2021] [Indexed: 11/13/2022] Open
Abstract
Electrophysiological sensory deviance detection signals, such as the mismatch negativity (MMN), have been interpreted from the predictive coding framework as manifestations of prediction error (PE). From a frequentist perspective of the classic oddball paradigm, deviant stimuli are unexpected because of their low probability. However, the amount of PE elicited by a stimulus can be dissociated from its probability of occurrence: when the observer cannot make confident predictions, any event holds little surprise value, no matter how improbable. Here we tested the hypothesis that the magnitude of the neural response elicited to an improbable sound (D) would scale with the precision of the prediction derived from the repetition of another sound (S), by manipulating repetition stability. We recorded the Electroencephalogram (EEG) from 20 participants while passively listening to 4 types of isochronous pure tone sequences differing in the probability of the S tone (880 Hz) while holding constant the probability of the D tone [1,046 Hz; p(D) = 1/11]: Oddball [p(S) = 10/11]; High confidence (7/11); Low confidence (4/11); and Random (1/11). Tones of 9 different frequencies were equiprobably presented as fillers [p(S) + p(D) + p(F) = 1]. Using a mass-univariate non-parametric, cluster-based correlation analysis controlling for multiple comparisons, we found that the amplitude of the deviant-elicited ERP became more negative with increasing S probability, in a time-electrode window consistent with the MMN (ca. 120–200 ms; frontal), suggesting that the strength of a PE elicited to an improbable event indeed increases with the precision of the predictive model.
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Affiliation(s)
- Iria SanMiguel
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Jordi Costa-Faidella
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Zulay R Lugo
- Hospital Universitari Institut Pere Mata, Universitat Rovira i Virgili (URV), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Elisabet Vilella
- Hospital Universitari Institut Pere Mata, Universitat Rovira i Virgili (URV), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.,Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Madrid, Spain
| | - Carles Escera
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
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33
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Friston K, Moran RJ, Nagai Y, Taniguchi T, Gomi H, Tenenbaum J. World model learning and inference. Neural Netw 2021; 144:573-590. [PMID: 34634605 DOI: 10.1016/j.neunet.2021.09.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 07/28/2021] [Accepted: 09/09/2021] [Indexed: 11/19/2022]
Abstract
Understanding information processing in the brain-and creating general-purpose artificial intelligence-are long-standing aspirations of scientists and engineers worldwide. The distinctive features of human intelligence are high-level cognition and control in various interactions with the world including the self, which are not defined in advance and are vary over time. The challenge of building human-like intelligent machines, as well as progress in brain science and behavioural analyses, robotics, and their associated theoretical formalisations, speaks to the importance of the world-model learning and inference. In this article, after briefly surveying the history and challenges of internal model learning and probabilistic learning, we introduce the free energy principle, which provides a useful framework within which to consider neuronal computation and probabilistic world models. Next, we showcase examples of human behaviour and cognition explained under that principle. We then describe symbol emergence in the context of probabilistic modelling, as a topic at the frontiers of cognitive robotics. Lastly, we review recent progress in creating human-like intelligence by using novel probabilistic programming languages. The striking consensus that emerges from these studies is that probabilistic descriptions of learning and inference are powerful and effective ways to create human-like artificial intelligent machines and to understand intelligence in the context of how humans interact with their world.
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Affiliation(s)
- Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London (UCL), WC1N 3BG, UK.
| | - Rosalyn J Moran
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK.
| | - Yukie Nagai
- International Research Center for Neurointelligence (IRCN), The University of Tokyo, Tokyo, Japan.
| | - Tadahiro Taniguchi
- College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan.
| | - Hiroaki Gomi
- NTT Communication Science Labs., Nippon Telegraph and Telephone, Kanawaga, Japan.
| | - Josh Tenenbaum
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA; The Center for Brains, Minds and Machines, MIT, Cambridge, MA, USA.
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34
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Jafarian A, Zeidman P, Wykes RC, Walker M, Friston KJ. Adiabatic dynamic causal modelling. Neuroimage 2021; 238:118243. [PMID: 34116151 PMCID: PMC8350149 DOI: 10.1016/j.neuroimage.2021.118243] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 06/03/2021] [Accepted: 06/04/2021] [Indexed: 01/07/2023] Open
Abstract
This technical note introduces adiabatic dynamic causal modelling, a method for inferring slow changes in biophysical parameters that control fluctuations of fast neuronal states. The application domain we have in mind is inferring slow changes in variables (e.g., extracellular ion concentrations or synaptic efficacy) that underlie phase transitions in brain activity (e.g., paroxysmal seizure activity). The scheme is efficient and yet retains a biophysical interpretation, in virtue of being based on established neural mass models that are equipped with a slow dynamic on the parameters (such as synaptic rate constants or effective connectivity). In brief, we use an adiabatic approximation to summarise fast fluctuations in hidden neuronal states (and their expression in sensors) in terms of their second order statistics; namely, their complex cross spectra. This allows one to specify and compare models of slowly changing parameters (using Bayesian model reduction) that generate a sequence of empirical cross spectra of electrophysiological recordings. Crucially, we use the slow fluctuations in the spectral power of neuronal activity as empirical priors on changes in synaptic parameters. This introduces a circular causality, in which synaptic parameters underwrite fast neuronal activity that, in turn, induces activity-dependent plasticity in synaptic parameters. In this foundational paper, we describe the underlying model, establish its face validity using simulations and provide an illustrative application to a chemoconvulsant animal model of seizure activity.
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Affiliation(s)
- Amirhossein Jafarian
- Cambridge Centre for Frontotemporal Dementia and Related Disorders, Department of Clinical Neurosciences, University of Cambridge, UK; The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UK.
| | - Peter Zeidman
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UK
| | - Rob C Wykes
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, UK; Nanomedicine Lab, University of Manchester, UK
| | - Matthew Walker
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, UK
| | - Karl J Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UK
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35
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Li J, Hong B, Nolte G, Engel AK, Zhang D. Preparatory delta phase response is correlated with naturalistic speech comprehension performance. Cogn Neurodyn 2021; 16:337-352. [PMID: 35401861 PMCID: PMC8934811 DOI: 10.1007/s11571-021-09711-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 07/09/2021] [Accepted: 08/12/2021] [Indexed: 01/07/2023] Open
Abstract
While human speech comprehension is thought to be an active process that involves top-down predictions, it remains unclear how predictive information is used to prepare for the processing of upcoming speech information. We aimed to identify the neural signatures of the preparatory processing of upcoming speech. Participants selectively attended to one of two competing naturalistic, narrative speech streams, and a temporal response function (TRF) method was applied to derive event-related-like neural responses from electroencephalographic data. The phase responses to the attended speech at the delta band (1-4 Hz) were correlated with the comprehension performance of individual participants, with a latency of - 200-0 ms relative to the onset of speech amplitude envelope fluctuations over the fronto-central and left-lateralized parietal electrodes. The phase responses to the attended speech at the alpha band also correlated with comprehension performance but with a latency of 650-980 ms post-onset over the fronto-central electrodes. Distinct neural signatures were found for the attentional modulation, taking the form of TRF-based amplitude responses at a latency of 240-320 ms post-onset over the left-lateralized fronto-central and occipital electrodes. Our findings reveal how the brain gets prepared to process an upcoming speech in a continuous, naturalistic speech context.
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Affiliation(s)
- Jiawei Li
- Department of Psychology, School of Social Sciences, Tsinghua University, Room 334, Mingzhai Building, Beijing, China
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
| | - Bo Hong
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg Eppendorf, Hamburg, Germany
| | - Andreas K. Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg Eppendorf, Hamburg, Germany
| | - Dan Zhang
- Department of Psychology, School of Social Sciences, Tsinghua University, Room 334, Mingzhai Building, Beijing, China
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
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36
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Antunes FM, Malmierca MS. Corticothalamic Pathways in Auditory Processing: Recent Advances and Insights From Other Sensory Systems. Front Neural Circuits 2021; 15:721186. [PMID: 34489648 PMCID: PMC8418311 DOI: 10.3389/fncir.2021.721186] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 07/28/2021] [Indexed: 11/24/2022] Open
Abstract
The corticothalamic (CT) pathways emanate from either Layer 5 (L5) or 6 (L6) of the neocortex and largely outnumber the ascending, thalamocortical pathways. The CT pathways provide the anatomical foundations for an intricate, bidirectional communication between thalamus and cortex. They act as dynamic circuits of information transfer with the ability to modulate or even drive the response properties of target neurons at each synaptic node of the circuit. L6 CT feedback pathways enable the cortex to shape the nature of its driving inputs, by directly modulating the sensory message arriving at the thalamus. L5 CT pathways can drive the postsynaptic neurons and initiate a transthalamic corticocortical circuit by which cortical areas communicate with each other. For this reason, L5 CT pathways place the thalamus at the heart of information transfer through the cortical hierarchy. Recent evidence goes even further to suggest that the thalamus via CT pathways regulates functional connectivity within and across cortical regions, and might be engaged in cognition, behavior, and perceptual inference. As descending pathways that enable reciprocal and context-dependent communication between thalamus and cortex, we venture that CT projections are particularly interesting in the context of hierarchical perceptual inference formulations such as those contemplated in predictive processing schemes, which so far heavily rely on cortical implementations. We discuss recent proposals suggesting that the thalamus, and particularly higher order thalamus via transthalamic pathways, could coordinate and contextualize hierarchical inference in cortical hierarchies. We will explore these ideas with a focus on the auditory system.
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Affiliation(s)
- Flora M. Antunes
- Cognitive and Auditory Neuroscience Laboratory (CANELAB), Institute of Neuroscience of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
- Institute for Biomedical Research of Salamanca, University of Salamanca, Salamanca, Spain
| | - Manuel S. Malmierca
- Cognitive and Auditory Neuroscience Laboratory (CANELAB), Institute of Neuroscience of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
- Institute for Biomedical Research of Salamanca, University of Salamanca, Salamanca, Spain
- Department of Cell Biology and Pathology, School of Medicine, University of Salamanca, Salamanca, Spain
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37
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Tivadar RI, Knight RT, Tzovara A. Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing. Front Hum Neurosci 2021; 15:702520. [PMID: 34489663 PMCID: PMC8416526 DOI: 10.3389/fnhum.2021.702520] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/12/2021] [Indexed: 01/22/2023] Open
Abstract
The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.
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Affiliation(s)
| | - Robert T. Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Athina Tzovara
- Institute of Computer Science, University of Bern, Bern, Switzerland
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Sleep-Wake Epilepsy Center | NeuroTec, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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38
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Dzafic I, Larsen KM, Darke H, Pertile H, Carter O, Sundram S, Garrido MI. Stronger Top-Down and Weaker Bottom-Up Frontotemporal Connections During Sensory Learning Are Associated With Severity of Psychotic Phenomena. Schizophr Bull 2021; 47:1039-1047. [PMID: 33404057 PMCID: PMC8266649 DOI: 10.1093/schbul/sbaa188] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Recent theories in computational psychiatry propose that unusual perceptual experiences and delusional beliefs may emerge as a consequence of aberrant inference and disruptions in sensory learning. The current study investigates these theories and examines the alterations that are specific to schizophrenia spectrum disorders vs those that occur as psychotic phenomena intensify, regardless of diagnosis. We recruited 66 participants: 22 schizophrenia spectrum inpatients, 22 nonpsychotic inpatients, and 22 nonclinical controls. Participants completed the reversal oddball task with volatility manipulated. We recorded neural responses with electroencephalography and measured behavioral errors to inferences on sound probabilities. Furthermore, we explored neural dynamics using dynamic causal modeling (DCM). Attenuated prediction errors (PEs) were specifically observed in the schizophrenia spectrum, with reductions in mismatch negativity in stable, and P300 in volatile, contexts. Conversely, aberrations in connectivity were observed across all participants as psychotic phenomena increased. DCM revealed that impaired sensory learning behavior was associated with decreased intrinsic connectivity in the left primary auditory cortex and right inferior frontal gyrus (IFG); connectivity in the latter was also reduced with greater severity of psychotic experiences. Moreover, people who experienced more hallucinations and psychotic-like symptoms had decreased bottom-up and increased top-down frontotemporal connectivity, respectively. The findings provide evidence that reduced PEs are specific to the schizophrenia spectrum, but deficits in brain connectivity are aligned on the psychosis continuum. Along the continuum, psychotic experiences were related to an aberrant interplay between top-down, bottom-up, and intrinsic connectivity in the IFG during sensory uncertainty. These findings provide novel insights into psychosis neurocomputational pathophysiology.
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Affiliation(s)
- Ilvana Dzafic
- Department of Medicine, Dentistry & Health Sciences, Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Kit M Larsen
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia.,Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.,Child and Adolescent Mental Health Centre, Mental Health Services Capital Region Copenhagen, University of Copenhagen, Copenhagen, Denmark
| | - Hayley Darke
- Department of Medicine, Dentistry & Health Sciences, Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia.,Department of Psychiatry, School of Clinical Sciences, Monash University, Melbourne, VIC, Australia
| | - Holly Pertile
- Department of Psychiatry, School of Clinical Sciences, Monash University, Melbourne, VIC, Australia.,Monash Medical Centre, Monash Health, Clayton, VIC, Australia
| | - Olivia Carter
- Department of Medicine, Dentistry & Health Sciences, Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Suresh Sundram
- Department of Psychiatry, School of Clinical Sciences, Monash University, Melbourne, VIC, Australia.,Monash Medical Centre, Monash Health, Clayton, VIC, Australia
| | - Marta I Garrido
- Department of Medicine, Dentistry & Health Sciences, Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
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Li G, Liu Y, Zheng Y, Wu Y, Li D, Liang X, Chen Y, Cui Y, Yap PT, Qiu S, Zhang H, Shen D. Multiscale neural modeling of resting-state fMRI reveals executive-limbic malfunction as a core mechanism in major depressive disorder. Neuroimage Clin 2021; 31:102758. [PMID: 34284335 PMCID: PMC8313604 DOI: 10.1016/j.nicl.2021.102758] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 06/30/2021] [Accepted: 07/03/2021] [Indexed: 11/15/2022]
Abstract
Major depressive disorder (MDD) represents a grand challenge to human health and society, but the underlying pathophysiological mechanisms remain elusive. Previous neuroimaging studies have suggested that MDD is associated with abnormal interactions and dynamics in two major neural systems including the default mode - salience (DMN-SAL) network and the executive - limbic (EXE-LIM) network, but it is not clear which network plays a central role and which network plays a subordinate role in MDD pathophysiology. To address this question, we refined a newly developed Multiscale Neural Model Inversion (MNMI) framework and applied it to test whether MDD is more affected by impaired circuit interactions in the DMN-SAL network or the EXE-LIM network. The model estimates the directed connection strengths between different neural populations both within and between brain regions based on resting-state fMRI data collected from normal healthy subjects and patients with MDD. Results show that MDD is primarily characterized by abnormal circuit interactions in the EXE-LIM network rather than the DMN-SAL network. Specifically, we observe reduced frontoparietal effective connectivity that potentially contributes to hypoactivity in the dorsolateral prefrontal cortex (dlPFC), and decreased intrinsic inhibition combined with increased excitation from the superior parietal cortex (SPC) that potentially lead to amygdala hyperactivity, together resulting in activation imbalance in the PFC-amygdala circuit that pervades in MDD. Moreover, the model reveals reduced PFC-to-hippocampus excitation but decreased SPC-to-thalamus inhibition in MDD population that potentially lead to hypoactivity in the hippocampus and hyperactivity in the thalamus, consistent with previous experimental data. Overall, our findings provide strong support for the long-standing limbic-cortical dysregulation model in major depression but also offer novel insights into the multiscale pathophysiology of this debilitating disease.
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Affiliation(s)
- Guoshi Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yujie Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA; The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Yanting Zheng
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA; The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Ye Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Danian Li
- Cerebropathy Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Xinyu Liang
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Yaoping Chen
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ying Cui
- Cerebropathy Center, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Pew-Thian Yap
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
| | - Han Zhang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
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40
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Limanowski J, Friston K. Attentional Modulation of Vision Versus Proprioception During Action. Cereb Cortex 2021; 30:1637-1648. [PMID: 31670769 PMCID: PMC7132949 DOI: 10.1093/cercor/bhz192] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 07/10/2019] [Accepted: 07/27/2019] [Indexed: 01/29/2023] Open
Abstract
To control our actions efficiently, our brain represents our body based on a combination of visual and proprioceptive cues, weighted according to how (un)reliable—how precise—each respective modality is in a given context. However, perceptual experiments in other modalities suggest that the weights assigned to sensory cues are also modulated “top-down” by attention. Here, we asked whether during action, attention can likewise modulate the weights (i.e., precision) assigned to visual versus proprioceptive information about body position. Participants controlled a virtual hand (VH) via a data glove, matching either the VH or their (unseen) real hand (RH) movements to a target, and thus adopting a ``visual'' or ``proprioceptive'' attentional set, under varying levels of visuo-proprioceptive congruence and visibility. Functional magnetic resonance imaging (fMRI) revealed increased activation of the multisensory superior parietal lobe (SPL) during the VH task and increased activation of the secondary somatosensory cortex (S2) during the RH task. Dynamic causal modeling (DCM) showed that these activity changes were the result of selective, diametrical gain modulations in the primary visual cortex (V1) and the S2. These results suggest that endogenous attention can balance the gain of visual versus proprioceptive brain areas, thus contextualizing their influence on multisensory areas representing the body for action.
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Affiliation(s)
- Jakub Limanowski
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
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41
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Schöbi D, Homberg F, Frässle S, Endepols H, Moran RJ, Friston KJ, Tittgemeyer M, Heinzle J, Stephan KE. Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses. Neuroimage 2021; 237:118096. [PMID: 33940149 DOI: 10.1016/j.neuroimage.2021.118096] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 04/12/2021] [Accepted: 04/19/2021] [Indexed: 01/09/2023] Open
Abstract
Drugs affecting neuromodulation, for example by dopamine or acetylcholine, take centre stage among therapeutic strategies in psychiatry. These neuromodulators can change both neuronal gain and synaptic plasticity and therefore affect electrophysiological measures. An important goal for clinical diagnostics is to exploit this effect in the reverse direction, i.e., to infer the status of specific neuromodulatory systems from electrophysiological measures. In this study, we provide proof-of-concept that the functional status of cholinergic (specifically muscarinic) receptors can be inferred from electrophysiological data using generative (dynamic causal) models. To this end, we used epidural EEG recordings over two auditory cortical regions during a mismatch negativity (MMN) paradigm in rats. All animals were treated, across sessions, with muscarinic receptor agonists and antagonists at different doses. Together with a placebo condition, this resulted in five levels of muscarinic receptor status. Using a dynamic causal model - embodying a small network of coupled cortical microcircuits - we estimated synaptic parameters and their change across pharmacological conditions. The ensuing parameter estimates associated with (the neuromodulation of) synaptic efficacy showed both graded muscarinic effects and predictive validity between agonistic and antagonistic pharmacological conditions. This finding illustrates the potential utility of generative models of electrophysiological data as computational assays of muscarinic function. In application to EEG data of patients from heterogeneous spectrum diseases, e.g. schizophrenia, such models might help identify subgroups of patients that respond differentially to cholinergic treatments. SIGNIFICANCE STATEMENT: In psychiatry, the vast majority of pharmacological treatments affect actions of neuromodulatory transmitters, e.g. dopamine or acetylcholine. As treatment is largely trial-and-error based, one of the goals for computational psychiatry is to construct mathematical models that can serve as "computational assays" and infer the status of specific neuromodulatory systems in individual patients. This translational neuromodeling strategy has great promise for electrophysiological data in particular but requires careful validation. The present study demonstrates that the functional status of cholinergic (muscarinic) receptors can be inferred from electrophysiological data using dynamic causal models of neural circuits. While accuracy needs to be enhanced and our results must be replicated in larger samples, our current results provide proof-of-concept for computational assays of muscarinic function using EEG.
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Affiliation(s)
- Dario Schöbi
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, 8032, Zurich, Switzerland
| | - Fabienne Homberg
- Boston Scientific Medizintechnik GmbH, Daniel-Goldbach-Strasse 17-27, 40880 Ratingen, Germany
| | - Stefan Frässle
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, 8032, Zurich, Switzerland
| | - Heike Endepols
- Preclinical Imaging Group, Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50923 Cologne, Germany
| | - Rosalyn J Moran
- Department of Neuroimaging, Institute for Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London Se5 8AF, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N, 3AR, UK
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Gleueler Strasse 50, 50931 Cologne, Germany; Cluster of Excellence in Cellular Stress and Aging associated Disease (CECAD), 50931 Cologne, Germany
| | - Jakob Heinzle
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, 8032, Zurich, Switzerland.
| | - Klaas Enno Stephan
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, 8032, Zurich, Switzerland; Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N, 3AR, UK; Max Planck Institute for Metabolism Research, Gleueler Strasse 50, 50931 Cologne, Germany
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42
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Jiang J, Benhamou E, Waters S, Johnson JCS, Volkmer A, Weil RS, Marshall CR, Warren JD, Hardy CJD. Processing of Degraded Speech in Brain Disorders. Brain Sci 2021; 11:394. [PMID: 33804653 PMCID: PMC8003678 DOI: 10.3390/brainsci11030394] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 03/15/2021] [Accepted: 03/18/2021] [Indexed: 11/30/2022] Open
Abstract
The speech we hear every day is typically "degraded" by competing sounds and the idiosyncratic vocal characteristics of individual speakers. While the comprehension of "degraded" speech is normally automatic, it depends on dynamic and adaptive processing across distributed neural networks. This presents the brain with an immense computational challenge, making degraded speech processing vulnerable to a range of brain disorders. Therefore, it is likely to be a sensitive marker of neural circuit dysfunction and an index of retained neural plasticity. Considering experimental methods for studying degraded speech and factors that affect its processing in healthy individuals, we review the evidence for altered degraded speech processing in major neurodegenerative diseases, traumatic brain injury and stroke. We develop a predictive coding framework for understanding deficits of degraded speech processing in these disorders, focussing on the "language-led dementias"-the primary progressive aphasias. We conclude by considering prospects for using degraded speech as a probe of language network pathophysiology, a diagnostic tool and a target for therapeutic intervention.
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Affiliation(s)
- Jessica Jiang
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
| | - Elia Benhamou
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
| | - Sheena Waters
- Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London EC1M 6BQ, UK;
| | - Jeremy C. S. Johnson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
| | - Anna Volkmer
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP, UK;
| | - Rimona S. Weil
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
| | - Charles R. Marshall
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
- Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London EC1M 6BQ, UK;
| | - Jason D. Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
| | - Chris J. D. Hardy
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; (J.J.); (E.B.); (J.C.S.J.); (R.S.W.); (C.R.M.); (J.D.W.)
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43
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Hsu YF, Hämäläinen JA. Both contextual regularity and selective attention affect the reduction of precision-weighted prediction errors but in distinct manners. Psychophysiology 2020; 58:e13753. [PMID: 33340115 DOI: 10.1111/psyp.13753] [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: 04/08/2020] [Revised: 12/02/2020] [Accepted: 12/02/2020] [Indexed: 10/22/2022]
Abstract
Predictive coding model of perception postulates that the primary objective of the brain is to infer the causes of sensory inputs by reducing prediction errors (i.e., the discrepancy between expected and actual information). Moreover, prediction errors are weighted by their precision (i.e., inverse variance), which quantifies the degree of certainty about the variables. There is accumulating evidence that the reduction of precision-weighted prediction errors can be affected by contextual regularity (as an external factor) and selective attention (as an internal factor). However, it is unclear whether the two factors function together or separately. Here we used electroencephalography (EEG) to examine the putative interaction of contextual regularity and selective attention on this reduction process. Participants were presented with pairs of regular and irregular quartets in attended and unattended conditions. We found that contextual regularity and selective attention independently modulated the N1/MMN where the repetition effect was absent. On the P2, the two factors respectively interacted with the repetition effect without interacting with each other. The results showed that contextual regularity and selective attention likely affect the reduction of precision-weighted prediction errors in distinct manners. While contextual regularity finetunes our efficiency at reducing precision-weighted prediction errors, selective attention seems to modulate the reduction process following the Matthew effect of accumulated advantage.
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Affiliation(s)
- Yi-Fang Hsu
- Department of Educational Psychology and Counselling, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Jarmo A Hämäläinen
- Jyväskylä Centre for Interdisciplinary Brain Research, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
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44
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Stefanics G, Heinzle J, Czigler I, Valentini E, Stephan KE. Timing of repetition suppression of event-related potentials to unattended objects. Eur J Neurosci 2020; 52:4432-4441. [PMID: 29802671 PMCID: PMC7818225 DOI: 10.1111/ejn.13972] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 04/03/2018] [Accepted: 05/16/2018] [Indexed: 12/11/2022]
Abstract
Current theories of object perception emphasize the automatic nature of perceptual inference. Repetition suppression (RS), the successive decrease of brain responses to repeated stimuli, is thought to reflect the optimization of perceptual inference through neural plasticity. While functional imaging studies revealed brain regions that show suppressed responses to the repeated presentation of an object, little is known about the intra-trial time course of repetition effects to everyday objects. Here, we used event-related potentials (ERPs) to task-irrelevant line-drawn objects, while participants engaged in a distractor task. We quantified changes in ERPs over repetitions using three general linear models that modeled RS by an exponential, linear, or categorical "change detection" function in each subject. Our aim was to select the model with highest evidence and determine the within-trial time-course and scalp distribution of repetition effects using that model. Model comparison revealed the superiority of the exponential model indicating that repetition effects are observable for trials beyond the first repetition. Model parameter estimates revealed a sequence of RS effects in three time windows (86-140, 322-360, and 400-446 ms) and with occipital, temporoparietal, and frontotemporal distribution, respectively. An interval of repetition enhancement (RE) was also observed (320-340 ms) over occipitotemporal sensors. Our results show that automatic processing of task-irrelevant objects involves multiple intervals of RS with distinct scalp topographies. These sequential intervals of RS and RE might reflect the short-term plasticity required for optimization of perceptual inference and the associated changes in prediction errors and predictions, respectively, over stimulus repetitions during automatic object processing.
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Affiliation(s)
- Gabor Stefanics
- Translational Neuromodeling Unit (TNU)Institute for Biomedical EngineeringUniversity of Zurich & ETH ZurichZurichSwitzerland
- Laboratory for Social and Neural Systems ResearchDepartment of EconomicsUniversity of ZurichZurichSwitzerland
| | - Jakob Heinzle
- Translational Neuromodeling Unit (TNU)Institute for Biomedical EngineeringUniversity of Zurich & ETH ZurichZurichSwitzerland
| | - István Czigler
- Institute of Cognitive Neuroscience and PsychologyResearch Center for Natural SciencesHungarian Academy of SciencesBudapestHungary
| | | | - Klaas E. Stephan
- Translational Neuromodeling Unit (TNU)Institute for Biomedical EngineeringUniversity of Zurich & ETH ZurichZurichSwitzerland
- Wellcome Trust Centre for NeuroimagingUniversity College LondonLondonUK
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Limanowski J, Litvak V, Friston K. Cortical beta oscillations reflect the contextual gating of visual action feedback. Neuroimage 2020; 222:117267. [PMID: 32818621 PMCID: PMC7779369 DOI: 10.1016/j.neuroimage.2020.117267] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 08/08/2020] [Accepted: 08/12/2020] [Indexed: 11/26/2022] Open
Abstract
We decouple seen and felt hand postures during action via virtual reality. Vision of the hand is either task-relevant or a distractor. Task-relevance of vision is reflected by in- or decreases of occipital beta power. DCM suggests underlying changes in cortical (visual) excitability. Occipital beta may indicate the contextual gating of visual action feedback.
In sensorimotor integration, the brain needs to decide how its predictions should accommodate novel evidence by ‘gating’ sensory data depending on the current context. Here, we examined the oscillatory correlates of this process by recording magnetoencephalography (MEG) data during a new task requiring action under intersensory conflict. We used virtual reality to decouple visual (virtual) and proprioceptive (real) hand postures during a task in which the phase of grasping movements tracked a target (in either modality). Thus, we rendered visual information either task-relevant or a (to-be-ignored) distractor. Under visuo-proprioceptive incongruence, occipital beta power decreased (relative to congruence) when vision was task-relevant but increased when it had to be ignored. Dynamic causal modeling (DCM) revealed that this interaction was best explained by diametrical, task-dependent changes in visual gain. These results suggest a crucial role for beta oscillations in the contextual gating (i.e., gain or precision control) of visual vs proprioceptive action feedback, depending on current behavioral demands.
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Affiliation(s)
- Jakub Limanowski
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, United Kingdom; Centre for Tactile Internet with Human-in-the-Loop, Technische Universität Dresden, Dresden, Germany.
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, United Kingdom
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, United Kingdom
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Aman L, Picken S, Andreou LV, Chait M. Sensitivity to temporal structure facilitates perceptual analysis of complex auditory scenes. Hear Res 2020; 400:108111. [PMID: 33333425 PMCID: PMC7812374 DOI: 10.1016/j.heares.2020.108111] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 10/13/2020] [Accepted: 11/06/2020] [Indexed: 11/17/2022]
Abstract
Perception relies on sensitivity to predictable structure in the environment. We used artificial acoustic scenes to investigate this in the auditory modality. Listeners track the temporal structure of multiple concurrent acoustic streams. Sensitivity to predictable structure supports auditory scene analysis, even when scenes are complex. Benefit of regularity observed even when listeners are unaware of the predictable structure.
The notion that sensitivity to the statistical structure of the environment is pivotal to perception has recently garnered considerable attention. Here we investigated this issue in the context of hearing. Building on previous work (Sohoglu and Chait, 2016a; elife), stimuli were artificial ‘soundscapes’ populated by multiple (up to 14) simultaneous streams (‘auditory objects’) comprised of tone-pip sequences, each with a distinct frequency and pattern of amplitude modulation. Sequences were either temporally regular or random. We show that listeners’ ability to detect abrupt appearance or disappearance of a stream is facilitated when scene streams were characterized by a temporally regular fluctuation pattern. The regularity of the changing stream as well as that of the background (non-changing) streams contribute independently to this effect. Remarkably, listeners benefit from regularity even when they are not consciously aware of it. These findings establish that perception of complex acoustic scenes relies on the availability of detailed representations of the regularities automatically extracted from multiple concurrent streams.
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Affiliation(s)
- Lucie Aman
- Ear Institute, University College London, 332 Gray's Inn Road, London WC1X 8EE, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Samantha Picken
- Ear Institute, University College London, 332 Gray's Inn Road, London WC1X 8EE, UK
| | - Lefkothea-Vasiliki Andreou
- Ear Institute, University College London, 332 Gray's Inn Road, London WC1X 8EE, UK; Vocational Lyceum of Zakynthos, Ministry of Education, Research and Religious Affairs, Zakynthos, Greece
| | - Maria Chait
- Ear Institute, University College London, 332 Gray's Inn Road, London WC1X 8EE, UK.
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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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Lumaca M, Dietz MJ, Hansen NC, Quiroga-Martinez DR, Vuust P. Perceptual learning of tone patterns changes the effective connectivity between Heschl's gyrus and planum temporale. Hum Brain Mapp 2020; 42:941-952. [PMID: 33146455 PMCID: PMC7856650 DOI: 10.1002/hbm.25269] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 10/06/2020] [Accepted: 10/15/2020] [Indexed: 11/11/2022] Open
Abstract
Learning of complex auditory sequences such as music can be thought of as optimizing an internal model of regularities through unpredicted events (or “prediction errors”). We used dynamic causal modeling (DCM) and parametric empirical Bayes on functional magnetic resonance imaging (fMRI) data to identify modulation of effective brain connectivity that takes place during perceptual learning of complex tone patterns. Our approach differs from previous studies in two aspects. First, we used a complex oddball paradigm based on tone patterns as opposed to simple deviant tones. Second, the use of fMRI allowed us to identify cortical regions with high spatial accuracy. These regions served as empirical regions‐of‐interest for the analysis of effective connectivity. Deviant patterns induced an increased blood oxygenation level‐dependent response, compared to standards, in early auditory (Heschl's gyrus [HG]) and association auditory areas (planum temporale [PT]) bilaterally. Within this network, we found a left‐lateralized increase in feedforward connectivity from HG to PT during deviant responses and an increase in excitation within left HG. In contrast to previous findings, we did not find frontal activity, nor did we find modulations of backward connections in response to oddball sounds. Our results suggest that complex auditory prediction errors are encoded by changes in feedforward and intrinsic connections, confined to superior temporal gyrus.
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Affiliation(s)
- Massimo Lumaca
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
| | - Martin J Dietz
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Niels Chr Hansen
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark.,Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark
| | - David R Quiroga-Martinez
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
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Holmes E, Zeidman P, Friston KJ, Griffiths TD. Difficulties with Speech-in-Noise Perception Related to Fundamental Grouping Processes in Auditory Cortex. Cereb Cortex 2020; 31:1582-1596. [PMID: 33136138 PMCID: PMC7869094 DOI: 10.1093/cercor/bhaa311] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/04/2020] [Accepted: 09/22/2020] [Indexed: 01/05/2023] Open
Abstract
In our everyday lives, we are often required to follow a conversation when background noise is present (“speech-in-noise” [SPIN] perception). SPIN perception varies widely—and people who are worse at SPIN perception are also worse at fundamental auditory grouping, as assessed by figure-ground tasks. Here, we examined the cortical processes that link difficulties with SPIN perception to difficulties with figure-ground perception using functional magnetic resonance imaging. We found strong evidence that the earliest stages of the auditory cortical hierarchy (left core and belt areas) are similarly disinhibited when SPIN and figure-ground tasks are more difficult (i.e., at target-to-masker ratios corresponding to 60% rather than 90% performance)—consistent with increased cortical gain at lower levels of the auditory hierarchy. Overall, our results reveal a common neural substrate for these basic (figure-ground) and naturally relevant (SPIN) tasks—which provides a common computational basis for the link between SPIN perception and fundamental auditory grouping.
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Affiliation(s)
- Emma Holmes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK
| | - Peter Zeidman
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK
| | - Timothy D Griffiths
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK.,Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
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Banellis L, Sokoliuk R, Wild CJ, Bowman H, Cruse D. Event-related potentials reflect prediction errors and pop-out during comprehension of degraded speech. Neurosci Conscious 2020; 2020:niaa022. [PMID: 33133640 PMCID: PMC7585676 DOI: 10.1093/nc/niaa022] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 07/08/2020] [Accepted: 08/06/2020] [Indexed: 11/20/2022] Open
Abstract
Comprehension of degraded speech requires higher-order expectations informed by prior knowledge. Accurate top-down expectations of incoming degraded speech cause a subjective semantic 'pop-out' or conscious breakthrough experience. Indeed, the same stimulus can be perceived as meaningless when no expectations are made in advance. We investigated the event-related potential (ERP) correlates of these top-down expectations, their error signals and the subjective pop-out experience in healthy participants. We manipulated expectations in a word-pair priming degraded (noise-vocoded) speech task and investigated the role of top-down expectation with a between-groups attention manipulation. Consistent with the role of expectations in comprehension, repetition priming significantly enhanced perceptual intelligibility of the noise-vocoded degraded targets for attentive participants. An early ERP was larger for mismatched (i.e. unexpected) targets than matched targets, indicative of an initial error signal not reliant on top-down expectations. Subsequently, a P3a-like ERP was larger to matched targets than mismatched targets only for attending participants-i.e. a pop-out effect-while a later ERP was larger for mismatched targets and did not significantly interact with attention. Rather than relying on complex post hoc interactions between prediction error and precision to explain this apredictive pattern, we consider our data to be consistent with prediction error minimization accounts for early stages of processing followed by Global Neuronal Workspace-like breakthrough and processing in service of task goals.
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Affiliation(s)
- Leah Banellis
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
| | - Rodika Sokoliuk
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
| | - Conor J Wild
- Brain and Mind Institute, University of Western Ontario, London, ON N6A 3K7, Canada
| | - Howard Bowman
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
- School of Computing, University of Kent, Canterbury, Kent CT2 7NF, UK
| | - Damian Cruse
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
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