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Del Fante E, Piovesan F, Sarasso P, Barbieri P, Villa MC, Sacco K, Ronga I. Virtual Social Interaction in a Multiplayer-Online Video Game Increases Implicit Learning: An EEG Study. CYBERPSYCHOLOGY, BEHAVIOR AND SOCIAL NETWORKING 2024. [PMID: 38905139 DOI: 10.1089/cyber.2023.0336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
It is well known that social interaction enhances learning processes, improving abilities such as attention and memorization. However, it is not clear whether similar advantages may be obtained even in virtual environments. Here, we investigate whether virtual interactions in a video game, similarly to real-life social interactions, may improve individuals' performance in a subsequent implicit learning task. Twenty-one healthy participants were asked to play a cooperative video game for 20 minutes in three different gaming modalities: alone (Single-Player); together with someone without verbal interactions (Multi-Player -); and with someone with verbal interactions (Multi-Player +). After each gaming session, participants were presented with an EEG paradigm directed to measure mismatch negativity (MMN) responses, a well-validated index of implicit learning. MMN responses were significantly larger following Multi-Player +, as compared with Single-Player, and Multi-Player - conditions. No significant difference was found between Single-Player, and Multi-Player - conditions. These results indicate that implicit learning processes are enhanced following communicative virtual interactions. Verbal interaction in a virtual environment seems necessary to elicit social copresence and its positive effects on learning performances. This finding may have important implications for the design of virtual rehabilitation protocols and distance learning programs.
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Affiliation(s)
- Elena Del Fante
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
- "Play Better" Association, Ome, Italy
| | - Francesca Piovesan
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
| | - Pietro Sarasso
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
| | - Paolo Barbieri
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
| | - Maria-Chiara Villa
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
| | - Katiuscia Sacco
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
| | - Irene Ronga
- BIP (BraIn Plasticity and behavior changes) Research Group, Department of Psychology, University of Turin, Torino, Italy
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2
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Brand K, Wise T, Hess AJ, Russell BR, Stephan KE, Harrison OK. Incorporating uncertainty within dynamic interoceptive learning. Front Psychol 2024; 15:1254564. [PMID: 38646115 PMCID: PMC11026658 DOI: 10.3389/fpsyg.2024.1254564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/18/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction Interoception, the perception of the internal state of the body, has been shown to be closely linked to emotions and mental health. Of particular interest are interoceptive learning processes that capture associations between environmental cues and body signals as a basis for making homeostatically relevant predictions about the future. One method of measuring respiratory interoceptive learning that has shown promising results is the Breathing Learning Task (BLT). While the original BLT required binary predictions regarding the presence or absence of an upcoming inspiratory resistance, here we extended this paradigm to capture continuous measures of prediction (un)certainty. Methods Sixteen healthy participants completed the continuous version of the BLT, where they were asked to predict the likelihood of breathing resistances on a continuous scale from 0.0 to 10.0. In order to explain participants' responses, a Rescorla-Wagner model of associative learning was combined with suitable observation models for continuous or binary predictions, respectively. For validation, we compared both models against corresponding null models and examined the correlation between observed and modeled predictions. The model was additionally extended to test whether learning rates differed according to stimuli valence. Finally, summary measures of prediction certainty as well as model estimates for learning rates were considered against interoceptive and mental health questionnaire measures. Results Our results demonstrated that the continuous model fits closely captured participant behavior using empirical data, and the binarised predictions showed excellent replicability compared to previously collected data. However, the model extension indicated that there were no significant differences between learning rates for negative (i.e. breathing resistance) and positive (i.e. no breathing resistance) stimuli. Finally, significant correlations were found between fatigue severity and both prediction certainty and learning rate, as well as between anxiety sensitivity and prediction certainty. Discussion These results demonstrate the utility of gathering enriched continuous prediction data in interoceptive learning tasks, and suggest that the updated BLT is a promising paradigm for future investigations into interoceptive learning and potential links to mental health.
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Affiliation(s)
- Katja Brand
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Toby Wise
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom
| | - Alexander J. Hess
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | | | - Klaas E. Stephan
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Max Planck Institute for Metabolism Research, Cologne, Germany
| | - Olivia K. Harrison
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Psychology, University of Otago, Dunedin, New Zealand
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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3
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Liu J, Liu Y, Jiang H, Zhao J, Ding X. Facial feedback manipulation influences the automatic detection of unexpected emotional body expressions. Neuropsychologia 2024; 195:108802. [PMID: 38266669 DOI: 10.1016/j.neuropsychologia.2024.108802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 12/31/2023] [Accepted: 01/16/2024] [Indexed: 01/26/2024]
Abstract
Unexpected or changing facial expressions are known to be able to engage more automatic processing than frequently occurring facial expressions, thereby inducing a neural differential wave response known as expression mismatch negativity (EMMN). Recent studies have shown that EMMN can be modulated by the observer's facial feedback (i.e., feedback from their own facial movements). A similar EMMN activity has been discovered for body expressions, but thus far only a few emotion types have been investigated. It is unknown whether the EMMNs evoked by body expressions can be influenced by facial feedback. To explore this question, we recorded EEG activity of 29 participants in the reverse oddball paradigm. Here two unexamined categories of body expressions were presented, happy and sad, placed in two paired stimulus sequences: in one the happy body was presented with a probability of 80% (standards) while the sad body was presented with a probability of 20% (deviants), and in the other the probabilities were reversed. The facial feedback was manipulated by different pen holding conditions (i.e., participants holding the pen with the teeth, lips, or nondominant hand). The nonparametric cluster permutation test revealed significant happy and sad body-related EMMN (bEMMN) activities. The happy-bEMMN were more negative than sad-bEMMN within the range of 100-150 ms. Additionally, the bEMMN amplitude of both emotions is modulated by the facial feedback conditions. These results expand the range of emotional types applicable to bEMMN and provide evidence for the validity of the facial feedback hypothesis across emotional carriers.
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Affiliation(s)
- Jianyi Liu
- School of Psychology, Shaanxi Normal University and Shaanxi Provincial Key Laboratory of Behavior and Cognitive Neuroscience, Xi'an, China
| | - Yang Liu
- School of Psychology, Northwest Normal University, Lanzhou, China
| | - Heng Jiang
- School of Psychology, Northwest Normal University, Lanzhou, China
| | - Jingjing Zhao
- School of Psychology, Shaanxi Normal University and Shaanxi Provincial Key Laboratory of Behavior and Cognitive Neuroscience, Xi'an, China.
| | - Xiaobin Ding
- School of Psychology, Northwest Normal University, Lanzhou, China.
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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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5
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Del Popolo Cristaldi F, Buodo G, Gambarota F, Oosterwijk S, Mento G. How previous experience shapes future affective subjective ratings: A follow-up study investigating implicit learning and cue ambiguity. PLoS One 2024; 19:e0297954. [PMID: 38335190 PMCID: PMC10857730 DOI: 10.1371/journal.pone.0297954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 01/11/2024] [Indexed: 02/12/2024] Open
Abstract
People use their previous experience to predict future affective events. Since we live in ever-changing environments, affective predictions must generalize from past contexts (from which they may be implicitly learned) to new, potentially ambiguous contexts. This study investigated how past (un)certain relationships influence subjective experience following new ambiguous cues, and whether past relationships can be learned implicitly. Two S1-S2 paradigms were employed as learning and test phases in two experiments. S1s were colored circles, S2s negative or neutral affective pictures. Participants (Experiment 1 N = 121, Experiment 2 N = 116) were assigned to the certain (CG) or uncertain group (UG), and they were presented with 100% (CG) or 50% (UG) S1-S2 congruency during an uninstructed (Experiment 1) or implicit (Experiment 2) learning phase. During the test phase both groups were presented with a new 75% S1-S2 paradigm, and ambiguous (Experiment 1) or unambiguous (Experiment 2) S1s. Participants were asked to rate the expected valence of upcoming S2s (expectancy ratings), or their experienced valence and arousal (valence and arousal ratings). In Experiment 1 ambiguous cues elicited less negative expectancy ratings, and less unpleasant valence ratings, independently of prior experience. In Experiment 2, both groups showed similar expectancies, predicting upcoming pictures' valence according to the 75% contingencies of the test phase. Overall, we found that in the presence of ambiguous cues subjective affective experience is dampened, and that implicit previous experience does not emerge at the subjective level by significantly shaping reported affective experience.
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Affiliation(s)
| | - Giulia Buodo
- Department of General Psychology, University of Padua, Padua, Italy
| | - Filippo Gambarota
- Department of Developmental Psychology and Socialization, University of Padua, Padua, Italy
| | - Suzanne Oosterwijk
- Department of Social Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition Centre (ABC), Amsterdam, The Netherlands
| | - Giovanni Mento
- Department of General Psychology, University of Padua, Padua, Italy
- Scientific Institute, IRCCS E. Medea, Conegliano, Treviso, Italy
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6
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Hodson R, Mehta M, Smith R. The empirical status of predictive coding and active inference. Neurosci Biobehav Rev 2024; 157:105473. [PMID: 38030100 DOI: 10.1016/j.neubiorev.2023.105473] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/27/2023] [Accepted: 11/16/2023] [Indexed: 12/01/2023]
Abstract
Research on predictive processing models has focused largely on two specific algorithmic theories: Predictive Coding for perception and Active Inference for decision-making. While these interconnected theories possess broad explanatory potential, they have only recently begun to receive direct empirical evaluation. Here, we review recent studies of Predictive Coding and Active Inference with a focus on evaluating the degree to which they are empirically supported. For Predictive Coding, we find that existing empirical evidence offers modest support. However, some positive results can also be explained by alternative feedforward (e.g., feature detection-based) models. For Active Inference, most empirical studies have focused on fitting these models to behavior as a means of identifying and explaining individual or group differences. While Active Inference models tend to explain behavioral data reasonably well, there has not been a focus on testing empirical validity of active inference theory per se, which would require formal comparison to other models (e.g., non-Bayesian or model-free reinforcement learning models). This review suggests that, while promising, a number of specific research directions are still necessary to evaluate the empirical adequacy and explanatory power of these algorithms.
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Affiliation(s)
| | | | - Ryan Smith
- Laureate Institute for Brain Research, USA.
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7
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Barbieri P, Sarasso P, Lodico F, Aliverti A, Murayama K, Sacco K, Ronga I. The aesthetic valve: how aesthetic appreciation may switch emotional states from anxiety to curiosity. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220413. [PMID: 38104608 PMCID: PMC10725764 DOI: 10.1098/rstb.2022.0413] [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: 03/23/2023] [Accepted: 11/02/2023] [Indexed: 12/19/2023] Open
Abstract
Pursuing new knowledge in the entropic environment is pivotal for survival. However, dealing with uncertainty is a costly challenge for the agent surrounded by the stochastic sensory world, giving rise to different epistemic emotions, such as curiosity and anxiety. We recently proposed that aesthetic appreciation may have the role of associating pleasant feedback with the update of predictive representations. According to this idea, aesthetic appreciation and its associated rewarding feeling could drive people to seek new knowledge over anxiety. However, the relationship between aesthetic appreciation, curiosity, and anxiety has been still under-examined in the literature. Here, we explore the relationship between these epistemic emotions in a series of three experiments. In study 1, we examined whether music-induced aesthetic appreciation would influence curiosity in a gambling task. In studies 2a and 2b, we explore the relationship between music-induced aesthetic appreciation and anxiety state. Overall, aesthetic appreciation promoted curiosity-driven behaviour while it was negatively associated with anxiety. These results were consistent with the idea that aesthetic appreciation could act as a 'valve', prompting the individual to perceive curiosity (i.e. to consider novelty as a valuable opportunity to acquire new knowledge) rather than anxiety (i.e. to consider novelty as a risk to be avoided). This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.
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Affiliation(s)
- Paolo Barbieri
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Turin, Piemonte 10124, Italy
| | - Pietro Sarasso
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Turin, Piemonte 10124, Italy
| | - Fabio Lodico
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Turin, Piemonte 10124, Italy
| | - Alice Aliverti
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Turin, Piemonte 10124, Italy
| | - Kou Murayama
- Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Tübingen, Baden-Württemberg, 72074, Germany
| | - Katiuscia Sacco
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Turin, Piemonte 10124, Italy
| | - Irene Ronga
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Turin, Piemonte 10124, Italy
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8
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Drew A, Soto-Faraco S. Perceptual oddities: assessing the relationship between film editing and prediction processes. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220426. [PMID: 38104604 PMCID: PMC10725757 DOI: 10.1098/rstb.2022.0426] [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: 04/07/2023] [Accepted: 10/16/2023] [Indexed: 12/19/2023] Open
Abstract
During film viewing, humans parse sequences of individual shots into larger narrative structures, often weaving transitions at edit points into an apparently seamless and continuous flow. Editing helps filmmakers manipulate visual transitions to induce feelings of fluency/disfluency, tension/relief, curiosity, expectation and several emotional responses. We propose that the perceptual dynamics induced by film editing can be captured by a predictive processing (PP) framework. We hypothesise that visual discontinuities at edit points produce discrepancies between anticipated and actual sensory input, leading to prediction error. Further, we propose that the magnitude of prediction error depends on the predictability of each shot within the narrative flow, and lay out an account based on conflict monitoring. We test this hypothesis in two empirical studies measuring electroencephalography (EEG) during passive viewing of film excerpts, as well as behavioural responses during an active edit detection task. We report the neural and behavioural modulations at editing boundaries across three levels of narrative depth, showing greater modulations for edits spanning less predictable, deeper narrative transitions. Overall, our contribution lays the groundwork for understanding film editing from a PP perspective. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectivess'.
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Affiliation(s)
- Alice Drew
- Multisensory Research Group, Centre for Brain and Cognition, Universitat Pompeu Fabra, Carrer de Ramon Trias Fargas, 25-27, 08005 Barcelona, Spain
| | - Salvador Soto-Faraco
- Multisensory Research Group, Centre for Brain and Cognition, Universitat Pompeu Fabra, Carrer de Ramon Trias Fargas, 25-27, 08005 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
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9
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Mohanta S, Cleveland DM, Afrasiabi M, Rhone AE, Górska U, Cooper Borkenhagen M, Sanders RD, Boly M, Nourski KV, Saalmann YB. Traveling waves shape neural population dynamics enabling predictions and internal model updating. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.09.574848. [PMID: 38260606 PMCID: PMC10802392 DOI: 10.1101/2024.01.09.574848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The brain generates predictions based on statistical regularities in our environment. However, it is unclear how predictions are optimized through iterative interactions with the environment. Because traveling waves (TWs) propagate across the cortex shaping neural excitability, they can carry information to serve predictive processing. Using human intracranial recordings, we show that anterior-to-posterior alpha TWs correlated with prediction strength. Learning about priors altered neural state space trajectories, and how much it altered correlated with trial-by-trial prediction strength. Learning involved mismatches between predictions and sensory evidence triggering alpha-phase resets in lateral temporal cortex, accompanied by stronger alpha phase-high gamma amplitude coupling and high-gamma power. The mismatch initiated posterior-to-anterior alpha TWs and change in the subsequent trial's state space trajectory, facilitating model updating. Our findings suggest a vital role of alpha TWs carrying both predictions to sensory cortex and mismatch signals to frontal cortex for trial-by-trial fine-tuning of predictive models.
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Affiliation(s)
- S Mohanta
- Department of Psychology, University of Wisconsin-Madison, WI, USA
| | - D M Cleveland
- Department of Psychology, University of Wisconsin-Madison, WI, USA
| | - M Afrasiabi
- Department of Psychology, University of Wisconsin-Madison, WI, USA
| | - A E Rhone
- Department of Neurosurgery, University of Iowa, IA, USA
| | - U Górska
- Department of Psychiatry, University of Wisconsin-Madison, WI, USA
| | | | - R D Sanders
- Specialty of Anaesthesia, University of Sydney, Camperdown, NSW, Australia and Department of Anaesthetics and Institute of Academic Surgery, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - M Boly
- Department of Psychiatry, University of Wisconsin-Madison, WI, USA
- Department of Neurology, University of Wisconsin-Madison, WI, USA
| | - K V Nourski
- Department of Neurosurgery, University of Iowa, IA, USA
- Iowa Neuroscience Institute, University of Iowa, IA, USA
| | - Y B Saalmann
- Department of Psychology, University of Wisconsin-Madison, WI, USA
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10
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Liu J, Fan T, Chen Y, Zhao J. Seeking the neural representation of statistical properties in print during implicit processing of visual words. NPJ SCIENCE OF LEARNING 2023; 8:60. [PMID: 38102191 PMCID: PMC10724295 DOI: 10.1038/s41539-023-00209-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 11/29/2023] [Indexed: 12/17/2023]
Abstract
Statistical learning (SL) plays a key role in literacy acquisition. Studies have increasingly revealed the influence of distributional statistical properties of words on visual word processing, including the effects of word frequency (lexical level) and mappings between orthography, phonology, and semantics (sub-lexical level). However, there has been scant evidence to directly confirm that the statistical properties contained in print can be directly characterized by neural activities. Using time-resolved representational similarity analysis (RSA), the present study examined neural representations of different types of statistical properties in visual word processing. From the perspective of predictive coding, an equal probability sequence with low built-in prediction precision and three oddball sequences with high built-in prediction precision were designed with consistent and three types of inconsistent (orthographically inconsistent, orthography-to-phonology inconsistent, and orthography-to-semantics inconsistent) Chinese characters as visual stimuli. In the three oddball sequences, consistent characters were set as the standard stimuli (probability of occurrence p = 0.75) and three types of inconsistent characters were set as deviant stimuli (p = 0.25), respectively. In the equal probability sequence, the same consistent and inconsistent characters were presented randomly with identical occurrence probability (p = 0.25). Significant neural representation activities of word frequency were observed in the equal probability sequence. By contrast, neural representations of sub-lexical statistics only emerged in oddball sequences where short-term predictions were shaped. These findings reveal that the statistical properties learned from long-term print environment continues to play a role in current word processing mechanisms and these mechanisms can be modulated by short-term predictions.
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Affiliation(s)
- Jianyi Liu
- School of Psychology, Shaanxi Normal University, and Key Laboratory for Behavior and Cognitive Neuroscience of Shaanxi Province, Xi'an, China.
| | - Tengwen Fan
- School of Psychology, Shaanxi Normal University, and Key Laboratory for Behavior and Cognitive Neuroscience of Shaanxi Province, Xi'an, China
| | - Yan Chen
- Key laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
- Key laboratory of Human Development and Mental Health of Hubei Province, School of Psychology, Central China Normal University, Wuhan, China
| | - Jingjing Zhao
- School of Psychology, Shaanxi Normal University, and Key Laboratory for Behavior and Cognitive Neuroscience of Shaanxi Province, Xi'an, China.
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11
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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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12
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Poublan-Couzardot A, Lecaignard F, Fucci E, Davidson RJ, Mattout J, Lutz A, Abdoun O. Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response. PLoS Comput Biol 2023; 19:e1010557. [PMID: 38091350 PMCID: PMC10752554 DOI: 10.1371/journal.pcbi.1010557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/27/2023] [Accepted: 11/20/2023] [Indexed: 12/28/2023] Open
Abstract
Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models' ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies.
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Affiliation(s)
- Arnaud Poublan-Couzardot
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Françoise Lecaignard
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Enrico Fucci
- 2 Institute for Globally Distributed Open Research and Education (IGDORE), Sweden
| | - Richard J. Davidson
- Center for Healthy Minds, University of Wisconsin, Madison, Wisconsin, United States of America
- Department of Psychology, University of Wisconsin, Madison, Wisconsin, United States of America
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, Wisconsin, United States of America
- Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Jérémie Mattout
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Antoine Lutz
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Oussama Abdoun
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
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13
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Lowe BG, Robinson JE, Yamamoto N, Hogendoorn H, Johnston P. Same but different: The latency of a shared expectation signal interacts with stimulus attributes. Cortex 2023; 168:143-156. [PMID: 37716110 DOI: 10.1016/j.cortex.2023.08.004] [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: 03/29/2023] [Revised: 07/13/2023] [Accepted: 08/07/2023] [Indexed: 09/18/2023]
Abstract
Predictive coding theories assert that perceptual inference is a hierarchical process of belief updating, wherein the onset of unexpected sensory data causes so-called prediction error responses that calibrate erroneous inferences. Given the functionally specialised organisation of visual cortex, it is assumed that prediction error propagation interacts with the specific visual attribute violating an expectation. We sought to test this within the temporal domain by applying time-resolved decoding methods to electroencephalography (EEG) data evoked by contextual trajectory violations of either brightness, size, or orientation within a bound stimulus. We found that following ∼170 ms post stimulus onset, responses to both size violations and orientation violations were decodable from physically identical control trials in which no attributes were violated. These two violation types were then directly compared, with attribute-specific signalling being decoded from 265 ms. Temporal generalisation suggested that this dissociation was driven by latency shifts in shared expectation signalling between the two conditions. Using a novel temporal bias method, we then found that this shared signalling occurred earlier for size violations than orientation violations. To our knowledge, we are among the first to decode expectation violations in humans using EEG and have demonstrated a temporal dissociation in attribute-specific expectancy violations.
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Affiliation(s)
- Benjamin G Lowe
- School of Psychology and Counselling, Queensland University of Technology (QUT), Kelvin Grove, QLD, Australia; Perception in Action Research Centre & School of Psychological Sciences, Macquarie University, Macquarie Park, NSW, Australia.
| | - Jonathan E Robinson
- Monash Centre for Consciousness & Contemplative Studies, Monash University, Clayton, VIC, Australia
| | - Naohide Yamamoto
- School of Psychology and Counselling, Queensland University of Technology (QUT), Kelvin Grove, QLD, Australia; Centre for Vision and Eye Research, Queensland University of Technology (QUT), Kelvin Grove, QLD, Australia
| | - Hinze Hogendoorn
- School of Psychology and Counselling, Queensland University of Technology (QUT), Kelvin Grove, QLD, Australia; Melbourne School of Psychological Science, University of Melbourne, Parkville, VIC, Australia
| | - Patrick Johnston
- School of Exercise Science and Nutrition Sciences, Queensland University of Technology (QUT), Kelvin Grove, QLD, Australia
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14
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Hein TP, Gong Z, Ivanova M, Fedele T, Nikulin V, Herrojo Ruiz M. Anterior cingulate and medial prefrontal cortex oscillations underlie learning alterations in trait anxiety in humans. Commun Biol 2023; 6:271. [PMID: 36922553 PMCID: PMC10017780 DOI: 10.1038/s42003-023-04628-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
Anxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by suppressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.
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Affiliation(s)
- Thomas P Hein
- Goldsmiths, University of London, Psychology Department, Whitehead Building New Cross, London, SE14 6NW, UK
| | - Zheng Gong
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russian Federation
| | - Marina Ivanova
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russian Federation
| | - Tommaso Fedele
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russian Federation
| | - Vadim Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Maria Herrojo Ruiz
- Goldsmiths, University of London, Psychology Department, Whitehead Building New Cross, London, SE14 6NW, UK.
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15
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Rupawala M, Bucsea O, Laudiano-Dray MP, Whitehead K, Meek J, Fitzgerald M, Olhede S, Jones L, Fabrizi L. A developmental shift in habituation to pain in human neonates. Curr Biol 2023; 33:1397-1406.e5. [PMID: 36931271 DOI: 10.1016/j.cub.2023.02.071] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 11/22/2022] [Accepted: 02/23/2023] [Indexed: 03/18/2023]
Abstract
Habituation to recurrent non-threatening or unavoidable noxious stimuli is an important aspect of adaptation to pain. Neonates, especially if preterm, are exposed to repeated noxious procedures during their clinical care. They can mount strong behavioral, autonomic, spinal, and cortical responses to a single noxious stimulus; however, it is not known whether the developing nervous system can adapt to the recurrence of these inputs. Here, we used electroencephalography to investigate changes in cortical microstates (representing the complex sequential processing of noxious inputs) following two consecutive clinically required heel lances in term and preterm infants. We show that stimulus repetition dampens the engagement of initial microstates and associated behavioral and autonomic responses in term infants, while preterm infants do not show signs of habituation. Nevertheless, both groups engage different longer-latency cortical microstates to each lance, which is likely to reflect changes in higher-level stimulus processing with repeated stimulation. These data suggest that while both age groups are capable of encoding contextual differences in pain, the preterm brain does not regulate the initial cortical, behavioral, and autonomic responses to repeated noxious stimuli. Habituation mechanisms to pain are already in place at term age but mature over the equivalent of the last trimester of gestation and are not fully functional in preterm neonates.
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Affiliation(s)
- Mohammed Rupawala
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Oana Bucsea
- Faculty of Health, Department of Psychology, York University, Toronto, ON M3J 1P3, Canada
| | | | - Kimberley Whitehead
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Judith Meek
- Elizabeth Garrett Anderson Obstetric Wing, University College London Hospitals, London WC1E 6DB, UK
| | - Maria Fitzgerald
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Sofia Olhede
- Department of Statistical Science, University College London, London WC1E 6BT, UK; Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Laura Jones
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Lorenzo Fabrizi
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK.
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16
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Tecilla M, Großbach M, Gentile G, Holland P, Sporn S, Antonini A, Herrojo Ruiz M. Modulation of Motor Vigor by Expectation of Reward Probability Trial-by-Trial Is Preserved in Healthy Ageing and Parkinson's Disease Patients. J Neurosci 2023; 43:1757-1777. [PMID: 36732072 PMCID: PMC10010462 DOI: 10.1523/jneurosci.1583-22.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 12/13/2022] [Accepted: 12/31/2022] [Indexed: 02/04/2023] Open
Abstract
Motor improvements, such as faster movement times or increased velocity, have been associated with reward magnitude in deterministic contexts. Yet whether individual inferences on reward probability influence motor vigor dynamically remains undetermined. We investigated how dynamically inferring volatile action-reward contingencies modulated motor performance trial-by-trial. We conducted three studies that coupled a reversal learning paradigm with a motor sequence task and used a validated hierarchical Bayesian model to fit trial-by-trial data. In Study 1, we tested healthy younger [HYA; 37 (24 females)] and older adults [HOA; 37 (17 females)], and medicated Parkinson's disease (PD) patients [20 (7 females)]. We showed that stronger predictions about the tendency of the action-reward contingency led to faster performance tempo, commensurate with movement time, on a trial-by-trial basis without robustly modulating reaction time (RT). Using Bayesian linear mixed models, we demonstrated a similar invigoration effect on performance tempo in HYA, HOA, and PD, despite HOA and PD being slower than HYA. In Study 2 [HYA, 39 (29 females)], we additionally showed that retrospective subjective inference about credit assignment did not contribute to differences in motor vigor effects. Last, Study 3 [HYA, 33 (27 females)] revealed that explicit beliefs about the reward tendency (confidence ratings) modulated performance tempo trial-by-trial. Our study is the first to reveal that the dynamic updating of beliefs about volatile action-reward contingencies positively biases motor performance through faster tempo. We also provide robust evidence for a preserved sensitivity of motor vigor to inferences about the action-reward mapping in aging and medicated PD.SIGNIFICANCE STATEMENT Navigating a world rich in uncertainty relies on updating beliefs about the probability that our actions lead to reward. Here, we investigated how inferring the action-reward contingencies in a volatile environment modulated motor vigor trial-by-trial in healthy younger and older adults, and in Parkinson's disease (PD) patients on medication. We found an association between trial-by-trial predictions about the tendency of the action-reward contingency and performance tempo, with stronger expectations speeding the movement. We additionally provided evidence for a similar sensitivity of performance tempo to the strength of these predictions in all groups. Thus, dynamic beliefs about the changing relationship between actions and their outcome enhanced motor vigor. This positive bias was not compromised by age or Parkinson's disease.
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Affiliation(s)
- Margherita Tecilla
- Department of Psychology, Goldsmiths, University of London, London SE146NW, United Kingdom
| | - Michael Großbach
- Institute of Music Physiology and Musicians' Medicine, Hannover University of Music Drama and Media, Hannover 30175, Germany
| | - Giovanni Gentile
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua 35131, Italy
| | - Peter Holland
- Department of Psychology, Goldsmiths, University of London, London SE146NW, United Kingdom
| | - Sebastian Sporn
- Department of Clinical and Movement Neuroscience, Queen Square Institute of Neurology, University College London, London WC1N3BG, United Kingdom
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua 35131, Italy
| | - Maria Herrojo Ruiz
- Department of Psychology, Goldsmiths, University of London, London SE146NW, United Kingdom
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17
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Yoshioka A, Tanabe HC, Nakagawa E, Sumiya M, Koike T, Sadato N. The Role of the Left Inferior Frontal Gyrus in Introspection during Verbal Communication. Brain Sci 2023; 13:brainsci13010111. [PMID: 36672092 PMCID: PMC9856826 DOI: 10.3390/brainsci13010111] [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: 11/25/2022] [Revised: 12/30/2022] [Accepted: 12/30/2022] [Indexed: 01/11/2023] Open
Abstract
Conversation enables the sharing of our subjective experiences through verbalizing introspected thoughts and feelings. The mentalizing network represents introspection, and successful conversation is characterized by alignment through imitation mediated by the mirror neuron system (MNS). Therefore, we hypothesized that the interaction between the mentalizing network and MNS mediates the conversational exchange of introspection. To test this, we performed hyperscanning functional magnetic resonance imaging during structured real-time conversations between 19 pairs of healthy participants. The participants first evaluated their preference for and familiarity with a presented object and then disclosed it. The control was the object feature identification task. When contrasted with the control, the preference/familiarity evaluation phase activated the dorso-medial prefrontal cortex, anterior cingulate cortex, precuneus, left hippocampus, right cerebellum, and orbital portion of the left inferior frontal gyrus (IFG), which represents introspection. The left IFG was activated when the two participants' statements of introspection were mismatched during the disclosure. Disclosing introspection enhanced the functional connectivity of the left IFG with the bilateral superior temporal gyrus and primary motor cortex, representing the auditory MNS. Thus, the mentalizing system and MNS are hierarchically linked in the left IFG during a conversation, allowing for the sharing of introspection of the self and others.
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Affiliation(s)
- Ayumi Yoshioka
- Department of Cognitive and Psychological Sciences, Graduate School of Informatics, Nagoya University, Nagoya 464-8601, Japan
- Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Okazaki 444-8585, Japan
- Research Organization of Science and Technology, Ritsumeikan University, Kusatsu 525-8577, Japan
| | - Hiroki C. Tanabe
- Department of Cognitive and Psychological Sciences, Graduate School of Informatics, Nagoya University, Nagoya 464-8601, Japan
- Correspondence: (H.C.T.); (N.S.); Tel.: +81-52-789-2256 (H.C.T.); +81-564-55-7841 (N.S.); Fax: +81-52-789-2256 (H.C.T.); +81-564-55-7843 (N.S.)
| | - Eri Nakagawa
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Okazaki 444-8585, Japan
| | - Motofumi Sumiya
- Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Okazaki 444-8585, Japan
| | - Takahiko Koike
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Okazaki 444-8585, Japan
| | - Norihiro Sadato
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Okazaki 444-8585, Japan
- Research Organization of Science and Technology, Ritsumeikan University, Kusatsu 525-8577, Japan
- Correspondence: (H.C.T.); (N.S.); Tel.: +81-52-789-2256 (H.C.T.); +81-564-55-7841 (N.S.); Fax: +81-52-789-2256 (H.C.T.); +81-564-55-7843 (N.S.)
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18
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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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19
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Atypical prediction error learning is associated with prodromal symptoms in individuals at clinical high risk for psychosis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:105. [PMID: 36433979 PMCID: PMC9700713 DOI: 10.1038/s41537-022-00302-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 10/20/2022] [Indexed: 11/27/2022]
Abstract
Reductions in the auditory mismatch negativity (MMN) have been well-demonstrated in schizophrenia rendering it a promising biomarker for understanding the emergence of psychosis. According to the predictive coding theory of psychosis, MMN impairments may reflect disturbances in hierarchical information processing driven by maladaptive precision-weighted prediction errors (pwPEs) and enhanced belief updating. We applied a hierarchical Bayesian model of learning to single-trial EEG data from an auditory oddball paradigm in 31 help-seeking antipsychotic-naive high-risk individuals and 23 healthy controls to understand the computational mechanisms underlying the auditory MMN. We found that low-level sensory and high-level volatility pwPE expression correlated with EEG amplitudes, coinciding with the timing of the MMN. Furthermore, we found that prodromal positive symptom severity was associated with increased expression of sensory pwPEs and higher-level belief uncertainty. Our findings provide support for the role of pwPEs in auditory MMN generation, and suggest that increased sensory pwPEs driven by changes in belief uncertainty may render the environment seemingly unpredictable. This may predispose high-risk individuals to delusion-like ideation to explain this experience. These results highlight the value of computational models for understanding the pathophysiological mechanisms of psychosis.
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Mento G, Toffoli L, Della Longa L, Farroni T, Del Popolo Cristaldi F, Duma GM. Adaptive Cognitive Control in Prematurely Born Children: An HD-EEG Investigation. Brain Sci 2022; 12:brainsci12081074. [PMID: 36009137 PMCID: PMC9406101 DOI: 10.3390/brainsci12081074] [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: 07/21/2022] [Revised: 08/08/2022] [Accepted: 08/12/2022] [Indexed: 11/29/2022] Open
Abstract
Preterm birth is a neurodevelopmental risk condition often associated with cognitive control (CC) impairment. Recent evidence showed that CC can be implicitly adapted through associative learning. In the present study we investigated the ability to flexibly adjust CC as a function of implicit stimulus-response temporal regularities in preterm (PT; N = 21; mean age 8 ± 1.3 years; gestational age 30 ± 18.5 weeks) and full-term (FT; N = 20; mean age 8 ± 1.3 years) school-age children. All children underwent an HD-EEG recording while undergoing the Dynamic Temporal Prediction (DTP) task, a simple S1–S2 detection task purposely designed to generate local-global temporal predictability of imperative stimuli. The Wisconsin card sorting test (WCST) was administered to measure explicit CC. The PT group showed more premature and slower (DTP) as well as perseverative (WCST) responses than the FT group. Moreover, pre-terms showed poor adaptive CC as revealed by less efficient global response-speed adjustment. This behavioral pattern was mirrored by a reduced and less sensitive to global manipulation anticipatory Contingent Negative Variation (CNV) and by different cortical source recruitment. These findings suggest that implicit CC may be a reliable endophenotypic marker of atypical cognitive development associated with preterm birth.
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Affiliation(s)
- Giovanni Mento
- Department of General Psychology, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center (PNC), University of Padova, 35131 Padova, Italy
- Correspondence:
| | - Lisa Toffoli
- Department of General Psychology, University of Padova, 35131 Padova, Italy
| | - Letizia Della Longa
- Department of Developmental Psychology and Socialization, University of Padova, 35131 Padova, Italy
| | - Teresa Farroni
- Padova Neuroscience Center (PNC), University of Padova, 35131 Padova, Italy
- Department of Developmental Psychology and Socialization, University of Padova, 35131 Padova, Italy
| | - Fiorella Del Popolo Cristaldi
- Department of General Psychology, University of Padova, 35131 Padova, Italy
- IRCCS “La Nostra Famiglia-Medea”, Conegliano, 31015 Treviso, Italy
| | - Gian Marco Duma
- Department of General Psychology, University of Padova, 35131 Padova, Italy
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
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21
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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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22
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Weber LA, Tomiello S, Schöbi D, Wellstein KV, Mueller D, Iglesias S, Stephan KE. Auditory mismatch responses are differentially sensitive to changes in muscarinic acetylcholine versus dopamine receptor function. eLife 2022; 11:74835. [PMID: 35502897 PMCID: PMC9098218 DOI: 10.7554/elife.74835] [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: 10/25/2021] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
The auditory mismatch negativity (MMN) has been proposed as a biomarker of NMDA receptor (NMDAR) dysfunction in schizophrenia. Such dysfunction may be caused by aberrant interactions of different neuromodulators with NMDARs, which could explain clinical heterogeneity among patients. In two studies (N = 81 each), we used a double-blind placebo-controlled between-subject design to systematically test whether auditory mismatch responses under varying levels of environmental stability are sensitive to diminishing and enhancing cholinergic vs. dopaminergic function. We found a significant drug × mismatch interaction: while the muscarinic acetylcholine receptor antagonist biperiden delayed and topographically shifted mismatch responses, particularly during high stability, this effect could not be detected for amisulpride, a dopamine D2/D3 receptor antagonist. Neither galantamine nor levodopa, which elevate acetylcholine and dopamine levels, respectively, exerted significant effects on MMN. This differential MMN sensitivity to muscarinic versus dopaminergic receptor function may prove useful for developing tests that predict individual treatment responses in schizophrenia.
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Affiliation(s)
- Lilian Aline Weber
- Translational Neuroimaging Unit (TNU), Institute for Biomedical EngineeringInstitute for Biomedical Engineering, University of Zurich, Zurich, Switzerland
| | - Sara Tomiello
- Translational Neuroimaging Unit (TNU), Institute for Biomedical Engineering, University of Zurich, Zurich, Switzerland
| | - Dario Schöbi
- Translational Neuroimaging Unit (TNU), Institute for Biomedical Engineering, University of Zurich, Zurich, Switzerland
| | - Katharina V Wellstein
- Translational Neuroimaging Unit (TNU), Institute for Biomedical Engineering, University of Zurich, Zurich, Switzerland
| | - Daniel Mueller
- Institute for Clinical Chemistry, University Hospital of Zurich, Zurich, Switzerland
| | - Sandra Iglesias
- Translational Neuroimaging Unit (TNU), Institute for Biomedical Engineering, University of Zurich, Zurich, Switzerland
| | - Klaas Enno Stephan
- Translational Neuroimaging Unit (TNU), Institute for Biomedical Engineering, University of Zurich, Zurich, Switzerland
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Ding X, Xiong M, Kang T, Zhao X, Zhao J, Liu J. Automatic change detection of multiple facial expressions: A visual mismatch negativity study. Neuropsychologia 2022; 170:108234. [DOI: 10.1016/j.neuropsychologia.2022.108234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 02/27/2022] [Accepted: 04/04/2022] [Indexed: 10/18/2022]
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24
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Zeng X, Ji L, Liu Y, Zhang Y, Fu S. Visual Mismatch Negativity Reflects Enhanced Response to the Deviant: Evidence From Event-Related Potentials and Electroencephalogram Time-Frequency Analysis. Front Hum Neurosci 2022; 16:800855. [PMID: 35350445 PMCID: PMC8957826 DOI: 10.3389/fnhum.2022.800855] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 02/15/2022] [Indexed: 12/22/2022] Open
Abstract
Automatic detection of information changes in the visual environment is crucial for individual survival. Researchers use the oddball paradigm to study the brain’s response to frequently presented (standard) stimuli and occasionally presented (deviant) stimuli. The component that can be observed in the difference wave is called visual mismatch negativity (vMMN), which is obtained by subtracting event-related potentials (ERPs) evoked by the deviant from ERPs evoked by the standard. There are three hypotheses to explain the vMMN. The sensory fatigue (or refractoriness) hypothesis considers that weakened neural activity caused by repetition results in decreased ERPs of the standard. The memory trace hypothesis proposes that vMMN results from increased responses to the deviant. The predictive coding hypothesis attributes the difference to enhanced responses for deviants and suppression for standards. However, when distinguishing between these effects, previous researchers did not consider the effect of low-level features on the vMMN. In this experiment, we used face sequences composed of different emotions (e.g., neutral and fearful face) and presented an oddball sequence, a reverse oddball sequence, and an equiprobable sequence to participants. The deviant of the oddball sequence was subtracted from the standard of the oddball sequence, the reverse oddball sequence, and the same type of stimulus of the equiprobable sequence to get oddball-vMMN (vMMN1), reverse oddball-vMMN (vMMN2), and equiprobable-vMMN (vMMN3), respectively. The results showed no significant difference between vMMN2 and vMMN3 in 100–350 ms following stimulus onset, while the vMMN effect was significant, indicating that the probability of the standard did not affect vMMN, which supported the memory trace hypothesis. Additionally, the fearful-related vMMN were more negative than the neutral-related vMMN within the range of 100–150 ms, suggesting a negative bias. We analyzed the source location of different vMMNs. There was no significant difference in brain regions between different vMMNs. Time-frequency analysis showed that the deviant had stronger theta-band oscillatory than the standard (visual mismatch oscillatory responses, vMORs). However, there was no difference between vMORs2 and vMORs3, indicating that vMORs reflect an enhanced response to the deviant in terms of neural oscillation, supporting the memory trace hypothesis.
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25
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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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26
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Hein TP, Herrojo Ruiz M. State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning. Neuroimage 2022; 249:118895. [PMID: 35017125 DOI: 10.1016/j.neuroimage.2022.118895] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 10/21/2021] [Accepted: 01/07/2022] [Indexed: 12/20/2022] Open
Abstract
Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance) encoded in gamma oscillations (>30 Hz) and associated with the suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.
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Affiliation(s)
- Thomas P Hein
- Goldsmiths, Psychology Department, Whitehead Building New Cross, University of London, Lewisham Way, New Cross, London SE14 6NW, United Kingdom.
| | - Maria Herrojo Ruiz
- Goldsmiths, Psychology Department, Whitehead Building New Cross, University of London, Lewisham Way, New Cross, London SE14 6NW, United Kingdom; Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation.
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27
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Ding X, Chen Y, Liu Y, Zhao J, Liu J. The automatic detection of unexpected emotion and neutral body postures: A visual mismatch negativity study. Neuropsychologia 2022; 164:108108. [PMID: 34863799 DOI: 10.1016/j.neuropsychologia.2021.108108] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/20/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022]
Abstract
The ability to automatically detect emotional changes in the environment is crucial for social interaction. In the visual system, expression-related mismatch negativity (EMMN) reflects the automatic processing of emotional changes in facial expression. However, body postures also carry visual emotional information that can be recognized effectively and processed automatically, although their processing mechanism remains unknown. In this study, the reverse oddball paradigm was used to investigate the mismatch responses of unexpected fear and neutral body postures. The nonparametric cluster permutation test revealed significant fear and neutral visual mismatch negativity (vMMN) activities, and the fear-related vMMN was enhanced prior (130-230 ms) to the neutral vMMN (180-230 ms). The body-sensitive N190 component may partially account for the vMMN obtained in this study. The fearful body posture evoked a greater N190 response over the neutral body, and amplitudes of N190 were more negative in the deviant condition than the standard condition. Additionally, the body-related visual mismatch oscillatory responses were associated with enhancement of the alpha band oscillation, especially for the fearful body posture. These results expanded the applicable scope of body posture cues corresponding to mismatch signals, objectively defined the electrophysiological activities evoked, and revealed the processing bias toward negative emotion.
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Affiliation(s)
- Xiaobin Ding
- School of Psychology, Northwest Normal University, Lanzhou, China
| | - Yan Chen
- School of Psychology, Northwest Normal University, Lanzhou, China
| | - Yang Liu
- School of Psychology, Northwest Normal University, Lanzhou, China
| | - Jingjing Zhao
- School of Psychology, Shaanxi Normal University, And Key Laboratory for Behavior and Cognitive Neuroscience of Shaanxi Province, Xi'an, China.
| | - Jianyi Liu
- School of Psychology, Shaanxi Normal University, And Key Laboratory for Behavior and Cognitive Neuroscience of Shaanxi Province, Xi'an, China.
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28
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Temporal–spectral signaling of sensory information and expectations in the cerebral processing of pain. Proc Natl Acad Sci U S A 2022; 119:2116616119. [PMID: 34983852 PMCID: PMC8740684 DOI: 10.1073/pnas.2116616119] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/22/2021] [Indexed: 01/14/2023] Open
Abstract
Pain is not only shaped by sensory information but also by an individual’s expectations. Here, we investigated how commonly analyzed electroencephalography (EEG) responses to pain signal sensory information, expectations, and discrepancies thereof (prediction errors) in the processing of pain. Bayesian analysis confirmed that pain perception was shaped by objective sensory information and expectations. In contrast, EEG responses at different latencies (including the N1, N2, and P2 components) and frequencies (including alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Thus, EEG responses to pain are more involved in signaling sensory information than in signaling expectations or prediction errors. Expectation effects are obviously mediated by other brain mechanisms than the effects of sensory information on pain. The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual’s expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain.
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29
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Abstract
We offer an account of mental health and well-being using the predictive processing framework (PPF). According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence is modelled as error dynamics—the change in prediction errors over time . Our aim in this paper is to show how error dynamics can account for both momentary happiness and longer term well-being. What will emerge is a new neurocomputational framework for making sense of human flourishing.
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Affiliation(s)
- Mark Miller
- Center for Consciousness and Contemplative StudiesMonash University, Melbourne, Australia
| | - Erik Rietveld
- ILLC/Department of Philosophy, University of Amsterdam, Amsterdamhe Netherlands Department of PhilosophyUniversity of Twente, Enschede, the Netherlands
| | - Julian Kiverstein
- ILLC/Department of Philosophy, University of Amsterdam, Amsterdamhe Netherlands Department of PhilosophyUniversity of Twente, Enschede, the Netherlands
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30
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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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31
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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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32
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Liu M, Dong W, Qin S, Verguts T, Chen Q. Electrophysiological Signatures of Hierarchical Learning. Cereb Cortex 2021; 32:626-639. [PMID: 34339505 DOI: 10.1093/cercor/bhab245] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 06/26/2021] [Accepted: 06/27/2021] [Indexed: 11/13/2022] Open
Abstract
Human perception and learning is thought to rely on a hierarchical generative model that is continuously updated via precision-weighted prediction errors (pwPEs). However, the neural basis of such cognitive process and how it unfolds during decision-making remain poorly understood. To investigate this question, we combined a hierarchical Bayesian model (i.e., Hierarchical Gaussian Filter [HGF]) with electroencephalography (EEG), while participants performed a probabilistic reversal learning task in alternatingly stable and volatile environments. Behaviorally, the HGF fitted significantly better than two control, nonhierarchical, models. Neurally, low-level and high-level pwPEs were independently encoded by the P300 component. Low-level pwPEs were reflected in the theta (4-8 Hz) frequency band, but high-level pwPEs were not. Furthermore, the expressions of high-level pwPEs were stronger for participants with better HGF fit. These results indicate that the brain employs hierarchical learning and encodes both low- and high-level learning signals separately and adaptively.
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Affiliation(s)
- Meng Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 510631 Guangzhou, China.,School of Psychology, South China Normal University, 510631 Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Wenshan Dong
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 510631 Guangzhou, China.,School of Psychology, South China Normal University, 510631 Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875 Beijing, China
| | - Tom Verguts
- Department of Experimental Psychology, Ghent University, B-9000 Ghent, Belgium
| | - Qi Chen
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 510631 Guangzhou, China.,School of Psychology, South China Normal University, 510631 Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
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33
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Schmitt C, Schwenk JCB, Schütz A, Churan J, Kaminiarz A, Bremmer F. Preattentive processing of visually guided self-motion in humans and monkeys. Prog Neurobiol 2021; 205:102117. [PMID: 34224808 DOI: 10.1016/j.pneurobio.2021.102117] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 06/15/2021] [Accepted: 06/29/2021] [Indexed: 10/20/2022]
Abstract
The visually-based control of self-motion is a challenging task, requiring - if needed - immediate adjustments to keep on track. Accordingly, it would appear advantageous if the processing of self-motion direction (heading) was predictive, thereby accelerating the encoding of unexpected changes, and un-impaired by attentional load. We tested this hypothesis by recording EEG in humans and macaque monkeys with similar experimental protocols. Subjects viewed a random dot pattern simulating self-motion across a ground plane in an oddball EEG paradigm. Standard and deviant trials differed only in their simulated heading direction (forward-left vs. forward-right). Event-related potentials (ERPs) were compared in order to test for the occurrence of a visual mismatch negativity (vMMN), a component that reflects preattentive and likely also predictive processing of sensory stimuli. Analysis of the ERPs revealed signatures of a prediction mismatch for deviant stimuli in both humans and monkeys. In humans, a MMN was observed starting 110 ms after self-motion onset. In monkeys, peak response amplitudes following deviant stimuli were enhanced compared to the standard already 100 ms after self-motion onset. We consider our results strong evidence for a preattentive processing of visual self-motion information in humans and monkeys, allowing for ultrafast adjustments of their heading direction.
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Affiliation(s)
- Constanze Schmitt
- Dept. Neurophysics, Philipps-Universität Marburg, Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Philipps-Universität Marburg and Justus-Liebig Universität Giessen, Germany.
| | - Jakob C B Schwenk
- Dept. Neurophysics, Philipps-Universität Marburg, Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Philipps-Universität Marburg and Justus-Liebig Universität Giessen, Germany.
| | - Adrian Schütz
- Dept. Neurophysics, Philipps-Universität Marburg, Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Philipps-Universität Marburg and Justus-Liebig Universität Giessen, Germany.
| | - Jan Churan
- Dept. Neurophysics, Philipps-Universität Marburg, Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Philipps-Universität Marburg and Justus-Liebig Universität Giessen, Germany.
| | - André Kaminiarz
- Dept. Neurophysics, Philipps-Universität Marburg, Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Philipps-Universität Marburg and Justus-Liebig Universität Giessen, Germany.
| | - Frank Bremmer
- Dept. Neurophysics, Philipps-Universität Marburg, Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Philipps-Universität Marburg and Justus-Liebig Universität Giessen, Germany.
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34
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Kask A, Põldver N, Ausmees L, Kreegipuu K. Subjectively different emotional schematic faces not automatically discriminated from the brain's bioelectrical responses. Conscious Cogn 2021; 93:103150. [PMID: 34051391 DOI: 10.1016/j.concog.2021.103150] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 05/03/2021] [Accepted: 05/05/2021] [Indexed: 10/21/2022]
Abstract
The present study investigates how the brain automatically discriminates emotional schematic faces, as indicated by the mismatch responses, and how reliable these brain responses are. Thirty-three healthy volunteers participated in the vMMN EEG experiment with four experimental sets differing from each other by the type of standard (object with scrambled face features) and the type of deviants (Angry, Happy and Neutral schematic faces) presented. Conscious subjective evaluations of valence, arousal and attention catching of the same stimuli showed clear differentiation of emotional expressions. Deviant faces elicited rather similar vMMN at frontal and occipital sites. Bayesian analyses suggest that vMMN does not differ between angry and happy faces. Neutral faces, however, did not yield statistically significant vMMN at occipital leads. Pearson's correlation and intra-class correlation analyses showed that the brain's reactions to the stimuli were highly stable within individuals across the experimental sets, whereas the mismatch responses were much more variable.
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Affiliation(s)
- Annika Kask
- Institute of Psychology, University of Tartu, Tartu, Estonia; Doctoral School of Behavioural, Social and Health Sciences, Tartu, Estonia
| | - Nele Põldver
- Institute of Psychology, University of Tartu, Tartu, Estonia
| | - Liisi Ausmees
- Institute of Psychology, University of Tartu, Tartu, Estonia
| | - Kairi Kreegipuu
- Institute of Psychology, University of Tartu, Tartu, Estonia.
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35
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Feuerriegel D, Vogels R, Kovács G. Evaluating the evidence for expectation suppression in the visual system. Neurosci Biobehav Rev 2021; 126:368-381. [PMID: 33836212 DOI: 10.1016/j.neubiorev.2021.04.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 02/16/2021] [Accepted: 04/02/2021] [Indexed: 01/25/2023]
Abstract
Reports of expectation suppression have shaped the development of influential predictive coding-based theories of visual perception. However recent work has highlighted confounding factors that may mimic or inflate expectation suppression effects. In this review, we describe four confounds that are prevalent across experiments that tested for expectation suppression: effects of surprise, attention, stimulus repetition and adaptation, and stimulus novelty. With these confounds in mind we then critically review the evidence for expectation suppression across probabilistic cueing, statistical learning, oddball, action-outcome learning and apparent motion designs. We found evidence for expectation suppression within a specific subset of statistical learning designs that involved weeks of sequence learning prior to neural activity measurement. Across other experimental contexts, whereby stimulus appearance probabilities were learned within one or two testing sessions, there was inconsistent evidence for genuine expectation suppression. We discuss how an absence of expectation suppression could inform models of predictive processing, repetition suppression and perceptual decision-making. We also provide suggestions for designing experiments that may better test for expectation suppression in future work.
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Affiliation(s)
- Daniel Feuerriegel
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
| | - Rufin Vogels
- Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Gyula Kovács
- Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
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36
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Krylova M, Ristow I, Marr V, Borchardt V, Li M, Witzel J, Drumkova K, Harris JA, Zacharias N, Schiltz K, Amelung T, Beier KM, Kruger THC, Ponseti J, Schiffer B, Walter H, Kärgel C, Walter M. MEG reveals preference specific increases of sexual-image-evoked responses in paedophilic sexual offenders and healthy controls. World J Biol Psychiatry 2021; 22:257-270. [PMID: 32623929 DOI: 10.1080/15622975.2020.1789216] [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: 10/23/2022]
Abstract
OBJECTIVES Paedophilic disorder is characterised by sexual attraction towards children. Classification of a counterpart as sexually attractive likely occurs rapidly, and involves both conscious and unconscious attentional and cognitive processes. Magnetoencephalography (MEG) is an imaging method especially well-suited to examine visual and attentional processes triggered by sexual images within the range of milliseconds. METHODS We investigated brain responses to sexual images depicting adults (frequent) and children (infrequent stimulus) in seventeen paedophilic patients with a history of child sexual offending (P + CSO) and twenty healthy controls (HC) during a passive visual oddball paradigm. Event-related fields (ERF) were measured to extract the magnetic visual mismatch negativity (vMMNm), and how it relates to the processing of different classes of sexual stimuli. RESULTS P + CSO exhibited significantly longer vMMNm latencies (100-180 ms post-stimulus) than HC. Moreover, P + CSO showed widespread increased amplitudes in response to child images starting from P3a and P3b components and lasting up to 400 ms post-stimulus presentation localised in frontal and temporal brain regions. CONCLUSIONS This study uncovers the first MEG differences in automatic change detection between P + CSO and HC during the presentation of subliminal sexual images of adults and children, contributing towards a better understanding of the neurobiological processes of P + CSO.
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Affiliation(s)
- Marina Krylova
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany.,Department of Psychiatry, Eberhard Karls University, Tübingen, Germany
| | - Inka Ristow
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,Leibniz Institute for Neurobiology, Department for Behavioral Neurology, Magdeburg, Germany.,Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Vanessa Marr
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,Leibniz Institute for Neurobiology, Department for Behavioral Neurology, Magdeburg, Germany
| | - Viola Borchardt
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,Leibniz Institute for Neurobiology, Department for Behavioral Neurology, Magdeburg, Germany
| | - Meng Li
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
| | - Joachim Witzel
- Forensic Psychiatric State Hospital of Saxony-Anhalt, Stendal-Uchtspringe, Germany
| | - Krasimira Drumkova
- Forensic Psychiatric State Hospital of Saxony-Anhalt, Stendal-Uchtspringe, Germany
| | - Joseph A Harris
- Department of Psychology, Bradley University, Peoria, IL, USA
| | - Norman Zacharias
- Clinical Neuroscience Research Group, Experimental and Clinical Research Center (ECRC), Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Kolja Schiltz
- Section of Forensic Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany.,Department of Psychiatry and Psychotherapy, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany
| | - Till Amelung
- Institute of Sexology and Sexual Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Klaus M Beier
- Institute of Sexology and Sexual Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Tillmann H C Kruger
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Section of Clinical Psychology and Sexual Medicine, Hannover Medical School, Hannover, Germany
| | - Jorge Ponseti
- Institute of Sexual Medicine and Forensic Psychiatry and Psychotherapy, Christian-Albrechts-University of Kiel, Medical School, Kiel, Germany
| | - Boris Schiffer
- Division of Forensic Psychiatry, LWL-University Hospital, Ruhr University Bochum, Bochum, Germany
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Christian Kärgel
- Division of Forensic Psychiatry, LWL-University Hospital, Ruhr University Bochum, Bochum, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany.,Department of Psychiatry, Eberhard Karls University, Tübingen, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,Leibniz Institute for Neurobiology, Department for Behavioral Neurology, Magdeburg, Germany.,Department of Psychiatry and Psychotherapy, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany.,Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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37
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Del Popolo Cristaldi F, Mento G, Buodo G, Sarlo M. What's next? Neural correlates of emotional predictions: A high-density EEG investigation. Brain Cogn 2021; 150:105708. [PMID: 33714004 DOI: 10.1016/j.bandc.2021.105708] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 02/09/2021] [Accepted: 02/18/2021] [Indexed: 01/22/2023]
Abstract
Emotions were recently reconsidered as predictions, constructed by the brain (generation stage) to prearrange action (implementation stage), and update internal models according to incoming stimuli (updating stage). However, it is unclear how emotional predictions are shaped by stimuli predictability. This study investigated the role of stimuli predictability on emotional predictions through high-density EEG. Twenty-six undergraduates underwent a S1-S2 paradigm, with emotional faces as S1s and emotional pictures as S2s. Stimuli predictability was manipulated across three blocks, in which S1 valence was predictive of S2 in the 100%, 75%, or 50% of trials. ERPs and brain sources were analyzed for each stage. During prediction generation, a larger N170/superior temporal sulcus activity emerged to fearful faces in blocks with full (100%) and medium (75%) predictive ratios. During implementation, the random block (50%) elicited a valence-independent pre-allocation of resources, reflected by a larger CNV and activation of a wide left network. In the updating stage, emotional pictures always elicited a larger LPP, while a larger P2 to neutral stimuli and a higher activity of the orbitofrontal cortex signaled early valence-dependent and late block-dependent prediction errors. These findings provide the first evidence of how stimuli predictability shape each neurocomputational stage of emotional predictions construction.
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Affiliation(s)
| | - Giovanni Mento
- Department of General Psychology, University of Padua, Via Venezia 8, 35131 Padova, Italy; Padua Neuroscience Center (PNC), University of Padua, Via Orus 2, 35131 Padova, Italy
| | - Giulia Buodo
- Department of General Psychology, University of Padua, Via Venezia 8, 35131 Padova, Italy
| | - Michela Sarlo
- Department of Communication Sciences, Humanities and International Studies, University of Urbino Carlo Bo, Via Saffi 15, 61029 Urbino, Italy
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38
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Gijsen S, Grundei M, Lange RT, Ostwald D, Blankenburg F. Neural surprise in somatosensory Bayesian learning. PLoS Comput Biol 2021; 17:e1008068. [PMID: 33529181 PMCID: PMC7880500 DOI: 10.1371/journal.pcbi.1008068] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 02/12/2021] [Accepted: 12/18/2020] [Indexed: 02/08/2023] Open
Abstract
Tracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Indications of Bayesian surprise encoding, reflecting model updating, are found in primary somatosensory cortex from around 140ms. This dissociation is compatible with the idea that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its underlying mechanisms. Our environment features statistical regularities, such as a drop of rain predicting imminent rainfall. Despite the importance for behavior and survival, much remains unknown about how these dependencies are learned, particularly for somatosensation. As surprise signalling about novel observations indicates a mismatch between one’s beliefs and the world, it has been hypothesized that surprise computation plays an important role in perceptual learning. By analyzing EEG data from human participants receiving sequences of tactile stimulation, we compare different formulations of surprise and investigate the employed underlying learning model. Our results indicate that the brain estimates transitions between observations. Furthermore, we identified different signatures of surprise computation and thereby provide a dissociation of the neural correlates of belief inadequacy and belief updating. Specifically, early surprise responses from around 70ms were found to signal the need for changes to the model, with encoding of its subsequent updating occurring from around 140ms. These results provide insights into how somatosensory surprise signals may contribute to the learning of environmental statistics.
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Affiliation(s)
- Sam Gijsen
- Neurocomputation and Neuroimaging Unit, Freie Universität Berlin, Germany
- Humboldt-Universität zu Berlin, Faculty of Philosophy, Berlin School of Mind and Brain, Berlin, Germany
- * E-mail: (SG); (MG)
| | - Miro Grundei
- Neurocomputation and Neuroimaging Unit, Freie Universität Berlin, Germany
- Humboldt-Universität zu Berlin, Faculty of Philosophy, Berlin School of Mind and Brain, Berlin, Germany
- * E-mail: (SG); (MG)
| | - Robert T. Lange
- Berlin Institute of Technology, Berlin, Germany
- Einstein Center for Neurosciences, Berlin, Germany
| | - Dirk Ostwald
- Computational Cognitive Neuroscience, Freie Universität Berlin, Germany
| | - Felix Blankenburg
- Neurocomputation and Neuroimaging Unit, Freie Universität Berlin, Germany
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39
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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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40
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Feuerriegel D, Yook J, Quek GL, Hogendoorn H, Bode S. Visual mismatch responses index surprise signalling but not expectation suppression. Cortex 2020; 134:16-29. [PMID: 33249297 DOI: 10.1016/j.cortex.2020.10.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 09/04/2020] [Accepted: 10/13/2020] [Indexed: 01/17/2023]
Abstract
The ability to distinguish between commonplace and unusual sensory events is critical for efficient learning and adaptive behaviour. This has been investigated using oddball designs in which sequences of often-appearing (i.e., expected) stimuli are interspersed with rare (i.e., surprising) deviants. Resulting differences in electrophysiological responses following surprising compared to expected stimuli are known as visual mismatch responses (VMRs). VMRs are thought to index co-occurring contributions of stimulus repetition effects, expectation suppression (that occurs when one's expectations are fulfilled), and expectation violation (i.e., surprise) responses; however, these different effects have been conflated in existing oddball designs. To better isolate and quantify effects of expectation suppression and surprise, we adapted an oddball design based on Fast Periodic Visual Stimulation (FPVS) that controls for stimulus repetition effects. We recorded electroencephalography (EEG) while participants (N = 48) viewed stimulation sequences in which a single face identity was periodically presented at 6 Hz. Critically, one of two different face identities (termed oddballs) appeared as every 7th image throughout the sequence. The presentation probabilities of each oddball image within a sequence varied between 10 and 90%, such that participants could form expectations about which oddball face identity was more likely to appear within each sequence. We also included 'expectation neutral' 50% probability sequences, whereby consistently biased expectations would not be formed for either oddball face identity. We found that VMRs indexed surprise responses, and effects of expectation suppression were absent. That is, ERPs were more negative-going at occipitoparietal electrodes for surprising compared to neutral oddballs, but did not differ between expected and neutral oddballs. Surprising oddball-evoked ERPs were also highly similar across the 10-40% appearance probability conditions. Our findings indicate that VMRs which are not accounted for by repetition effects are best described as an all-or-none surprise response, rather than a minimisation of prediction error responses associated with expectation suppression.
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Affiliation(s)
- Daniel Feuerriegel
- Melbourne School of Psychological Sciences, The University of Melbourne, Australia.
| | - Jane Yook
- Melbourne School of Psychological Sciences, The University of Melbourne, Australia
| | - Genevieve L Quek
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Hinze Hogendoorn
- Melbourne School of Psychological Sciences, The University of Melbourne, Australia
| | - Stefan Bode
- Melbourne School of Psychological Sciences, The University of Melbourne, Australia; Department of Psychology, University of Cologne, Germany
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41
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Hein TP, de Fockert J, Ruiz MH. State anxiety biases estimates of uncertainty and impairs reward learning in volatile environments. Neuroimage 2020; 224:117424. [PMID: 33035670 DOI: 10.1016/j.neuroimage.2020.117424] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 08/27/2020] [Accepted: 09/29/2020] [Indexed: 01/01/2023] Open
Abstract
Clinical and subclinical (trait) anxiety impairs decision making and interferes with learning. Less understood are the effects of temporary anxious states on learning and decision making in healthy populations, and whether these can serve as a model for clinical anxiety. Here we test whether anxious states in healthy individuals elicit a pattern of aberrant behavioural, neural, and physiological responses comparable with those found in anxiety disorders-particularly when processing uncertainty in unstable environments. In our study, both a state anxious and a control group learned probabilistic stimulus-outcome mappings in a volatile task environment while we recorded their electrophysiological (EEG) signals. By using a hierarchical Bayesian model of inference and learning, we assessed the effect of state anxiety on Bayesian belief updating with a focus on uncertainty estimates. State anxiety was associated with an underestimation of environmental uncertainty, and informational uncertainty about the reward tendency. Anxious individuals' beliefs about reward contingencies were more precise (had smaller uncertainty) and thus more resistant to updating, ultimately leading to impaired reward-based learning. State anxiety was also associated with greater uncertainty about volatility. We interpret this pattern as evidence that state anxious individuals are less tolerant to informational uncertainty about the contingencies governing their environment and more willing to be uncertain about the level of stability of the world itself. Further, we tracked the neural representation of belief update signals in the trial-by-trial EEG amplitudes. In control participants, lower-level precision-weighted prediction errors (pwPEs) about reward tendencies were represented in the ERP signals across central and parietal electrodes peaking at 496 ms, overlapping with the late P300 in classical ERP analysis. The state anxiety group did not exhibit a significant representation of low-level pwPEs, and there were no significant differences between the groups. Smaller variance in low-level pwPE about reward tendencies in state anxiety could partially account for the null results. Expanding previous computational work on trait anxiety, our findings establish that temporary anxious states in healthy individuals impair reward-based learning in volatile environments, primarily through changes in uncertainty estimates, which play a central role in current Bayesian accounts of perceptual inference and learning.
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Affiliation(s)
- Thomas P Hein
- Goldsmiths, University of London, Psychology Department, Whitehead Building, New Cross, London, SE146NW, United Kingdom
| | - Jan de Fockert
- Goldsmiths, University of London, Psychology Department, Whitehead Building, New Cross, London, SE146NW, United Kingdom
| | - Maria Herrojo Ruiz
- Goldsmiths, University of London, Psychology Department, Whitehead Building, New Cross, London, SE146NW, United Kingdom; Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation.
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42
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Rossion B, Retter TL, Liu‐Shuang J. Understanding human individuation of unfamiliar faces with oddball fast periodic visual stimulation and electroencephalography. Eur J Neurosci 2020; 52:4283-4344. [DOI: 10.1111/ejn.14865] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 05/19/2020] [Accepted: 05/30/2020] [Indexed: 01/08/2023]
Affiliation(s)
- Bruno Rossion
- CNRS, CRAN UMR7039 Université de Lorraine F‐54000Nancy France
- Service de Neurologie, CHRU‐Nancy Université de Lorraine F‐54000Nancy France
| | - Talia L. Retter
- Department of Behavioural and Cognitive Sciences Faculty of Language and Literature Humanities, Arts and Education University of Luxembourg Luxembourg Luxembourg
| | - Joan Liu‐Shuang
- Institute of Research in Psychological Science Institute of Neuroscience Université de Louvain Louvain‐la‐Neuve Belgium
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43
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Ouyang G, Zhou C. Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development. Cogn Neurodyn 2020; 14:731-742. [PMID: 33101527 DOI: 10.1007/s11571-020-09631-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/09/2020] [Accepted: 08/27/2020] [Indexed: 01/02/2023] Open
Abstract
The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.
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Affiliation(s)
- Guang Ouyang
- Faculty of Education, The University of Hong Kong, Pokfulam, Hong Kong Island Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies, Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
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44
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Donaldson KR, Novak KD, Foti D, Marder M, Perlman G, Kotov R, Mohanty A. Associations of mismatch negativity with psychotic symptoms and functioning transdiagnostically across psychotic disorders. JOURNAL OF ABNORMAL PSYCHOLOGY 2020; 129:570-580. [PMID: 32757601 PMCID: PMC9236595 DOI: 10.1037/abn0000506] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Mismatch negativity (MMN) amplitude has been widely shown to be diminished in schizophrenia and, more recently, in other psychotic disorders. Although there is considerable evidence linking MMN reduction to cognitive and functional deficits in schizophrenia, there is little evidence of associations with specific psychotic symptoms. Further, it is unclear if MMN reductions relate to specific symptoms, cognitive, and functional deficits transdiagnostically across different psychotic disorders. The present study examines MMN amplitude in a large cohort of cases diagnosed with psychotic disorders including schizophrenia and schizoaffective disorder (N = 116); bipolar disorder and major depressive disorder (N = 75); and other psychotic disorders (N = 25), as well as individuals with no psychotic disorder diagnoses (N = 248). Furthermore, we examined the association of MMN with symptoms, cognitive functioning, and real-world functioning to determine whether these relationships differ by diagnosis. Results showed that MMN amplitude was reduced in cases overall compared to never-psychotic individuals, with no differences between psychotic disorders. Furthermore, there were transdiagnostic associations of reduced duration MMN (MMN-D) with worse auditory hallucinations (r = .14) and disorganization (r = .14), frequency MMN (MMN-F) with real-word functioning (r = .20) and episodic memory (r = -.22), and both components with executive functioning (MMN-D: r = -.17; MMN-F: r = -.15). Our findings relating MMN reductions with cognitive and real-world functioning replicate earlier research in schizophrenia and extend these relationships to other psychotic disorders. Furthermore, our correlations with MMN-D are consistent with computational modeling research and theoretical proposals that view MMN reduction, cognitive dysfunction, and psychotic symptoms as reflecting underlying predictive coding deficits. However, differences in relationships with MMN-F suggest that additional work is warranted on this topic. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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Affiliation(s)
| | - Keisha D. Novak
- Purdue University Department of Psychological Sciences, West Lafayette, IN
| | - Dan Foti
- Purdue University Department of Psychological Sciences, West Lafayette, IN
| | - Maya Marder
- Stony Brook University Department of Psychology, Stony Brook, NY
| | - Greg Perlman
- Stony Brook Medicine, Psychiatry Department, Stony Brook, NY
| | - Roman Kotov
- Stony Brook Medicine, Psychiatry Department, Stony Brook, NY
| | - Aprajita Mohanty
- Stony Brook University Department of Psychology, Stony Brook, NY
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45
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Ketamine Affects Prediction Errors about Statistical Regularities: A Computational Single-Trial Analysis of the Mismatch Negativity. J Neurosci 2020; 40:5658-5668. [PMID: 32561673 DOI: 10.1523/jneurosci.3069-19.2020] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 05/12/2020] [Accepted: 06/05/2020] [Indexed: 12/12/2022] Open
Abstract
The auditory mismatch negativity (MMN) is significantly reduced in schizophrenia. Notably, a similar MMN reduction can be achieved with NMDA receptor (NMDAR) antagonists. Both phenomena have been interpreted as reflecting an impairment of predictive coding or, more generally, the "Bayesian brain" notion that the brain continuously updates a hierarchical model to infer the causes of its sensory inputs. Specifically, neurobiological interpretations of predictive coding view perceptual inference as an NMDAR-dependent process of minimizing hierarchical precision-weighted prediction errors (PEs), and disturbances of this putative process play a key role in hierarchical Bayesian theories of schizophrenia. Here, we provide empirical evidence for this theory, demonstrating the existence of multiple, hierarchically related PEs in a "roving MMN" paradigm. We applied a hierarchical Bayesian model to single-trial EEG data from healthy human volunteers of either sex who received the NMDAR antagonist S-ketamine in a placebo-controlled, double-blind, within-subject fashion. Using an unrestricted analysis of the entire time-sensor space, our trial-by-trial analysis indicated that low-level PEs (about stimulus transitions) are expressed early (102-207 ms poststimulus), while high-level PEs (about transition probability) are reflected by later components (152-199 and 215-277 ms) of single-trial responses. Furthermore, we find that ketamine significantly diminished the expression of high-level PE responses, implying that NMDAR antagonism disrupts the inference on abstract statistical regularities. Our findings suggest that NMDAR dysfunction impairs hierarchical Bayesian inference about the world's statistical structure. Beyond the relevance of this finding for schizophrenia, our results illustrate the potential of computational single-trial analyses for assessing potential pathophysiological mechanisms.
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46
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Sporn S, Hein T, Herrojo Ruiz M. Alterations in the amplitude and burst rate of beta oscillations impair reward-dependent motor learning in anxiety. eLife 2020; 9:e50654. [PMID: 32423530 PMCID: PMC7237220 DOI: 10.7554/elife.50654] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 04/08/2020] [Indexed: 01/08/2023] Open
Abstract
Anxiety results in sub-optimal motor learning, but the precise mechanisms through which this effect occurs remain unknown. Using a motor sequence learning paradigm with separate phases for initial exploration and reward-based learning, we show that anxiety states in humans impair learning by attenuating the update of reward estimates. Further, when such estimates are perceived as unstable over time (volatility), anxiety constrains adaptive behavioral changes. Neurally, anxiety during initial exploration increased the amplitude and the rate of long bursts of sensorimotor and prefrontal beta oscillations (13-30 Hz). These changes extended to the subsequent learning phase, where phasic increases in beta power and burst rate following reward feedback were linked to smaller updates in reward estimates, with a higher anxiety-related increase explaining the attenuated belief updating. These data suggest that state anxiety alters the dynamics of beta oscillations during reward processing, thereby impairing proper updating of motor predictions when learning in unstable environments.
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Affiliation(s)
- Sebastian Sporn
- School of Psychology, University of BirminghamBirminghamUnited Kingdom
- Department of Psychology, Goldsmiths University of LondonLondonUnited Kingdom
| | - Thomas Hein
- Department of Psychology, Goldsmiths University of LondonLondonUnited Kingdom
| | - Maria Herrojo Ruiz
- Department of Psychology, Goldsmiths University of LondonLondonUnited Kingdom
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of EconomicsMoscowRussian Federation
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47
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Differential Effects of Awareness and Task Relevance on Early and Late ERPs in a No-Report Visual Oddball Paradigm. J Neurosci 2020; 40:2906-2913. [PMID: 32122954 DOI: 10.1523/jneurosci.2077-19.2020] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 12/09/2019] [Accepted: 01/13/2020] [Indexed: 01/22/2023] Open
Abstract
To date it is poorly understood how and when deviance processing interacts with awareness and task relevance. Furthermore, an important issue in the study of consciousness is the prevalent confound of conscious perception with the requirement of reporting it. This study addresses these topics using a no-report inattentional blindness paradigm with a visual oddball sequence of geometrical shapes presented to male and female human participants. Electrophysiological responses were obtained in three physically identical Phases A-C that differed only with respect to the instructions: (A) participants were uninformed about the shapes and attended an unrelated foreground task (inattentional blind), (B) were informed about the shapes but still attended the foreground task, and (C) attended the shapes. Conscious processing of shapes was indexed by the visual awareness negativity but not a P3. Deviance processing was associated with the visual mismatch negativity independently of consciousness and task relevance. The oddball P3, however, only emerged when the stimuli were task relevant, and was absent for consciously perceived but task irrelevant stimuli. The P3 thus does not represent a reliable marker of stimulus awareness. This result pattern supports the view of hierarchical predictive processing, where lower levels display automatic deviance processing, whereas higher levels require attention and task relevance.SIGNIFICANCE STATEMENT To react to potentially important changes in our environment it is fundamental to detect deviations from regularities of sensory input. It has yet to be understood how awareness and task relevance of this input interact with deviance processing. We investigated the role of awareness in deviance detection while at the same time circumventing the confound of awareness and report by means of a no-report paradigm. Our results suggest that early processes are elicited automatically, whereas, contrary to prominent theories, late processes do not depend on awareness but on task-based attention.
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Walsh KS, McGovern DP, Clark A, O'Connell RG. Evaluating the neurophysiological evidence for predictive processing as a model of perception. Ann N Y Acad Sci 2020; 1464:242-268. [PMID: 32147856 PMCID: PMC7187369 DOI: 10.1111/nyas.14321] [Citation(s) in RCA: 109] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 01/21/2020] [Accepted: 02/03/2020] [Indexed: 12/12/2022]
Abstract
For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.
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Affiliation(s)
- Kevin S. Walsh
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
| | - David P. McGovern
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
- School of PsychologyDublin City UniversityDublinIreland
| | - Andy Clark
- Department of PhilosophyUniversity of SussexBrightonUK
- Department of InformaticsUniversity of SussexBrightonUK
| | - Redmond G. O'Connell
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
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Ruusuvirta T. The release from refractoriness hypothesis of N1 of event-related potentials needs reassessment. Hear Res 2020; 399:107923. [PMID: 32089324 DOI: 10.1016/j.heares.2020.107923] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 02/11/2020] [Accepted: 02/11/2020] [Indexed: 12/01/2022]
Abstract
N1 of event-related potentials (ERPs) is augmented in amplitude in ∼50-150 ms by occasional changes (deviants) in the physical features of a sound repeated at intervals of from ∼400 ms to seconds (standard). The release-from-refractoriness hypothesis links the N1 augmentation to a deviant-feature-specific neural population that is fresh to fully respond as opposed to a standard-feature-specific neural population that is unresponsive due to its post-response refractoriness. The present work explored this hypothesis in the context of ERP studies, behavioral habituation studies and studies on stimulus-specific adaptation (SSA). The idea of hundreds of milliseconds neural population-level refractoriness was observed to be founded upon negative N1 evidence (no observable effect of dishabituating stimuli on N1 to standards - the null hypothesis retained) and merely supported by positive N1 evidence (null hypotheses rejected). This idea was also found to be directly challenged by positive N1 evidence. No conclusive network- or single-neuron-level evidence was found for the refractoriness. Therefore, the validity of the release-from-refractoriness hypothesis of N1 to guide psychophysiological research needs reassessment.
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Affiliation(s)
- Timo Ruusuvirta
- University of Turku, Department of Teacher Education, Seminaarinkatu 1, FIN-26100, Rauma, Finland.
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Wiesing M, Fink GR, Weidner R, Vossel S. Combined expectancies: the role of expectations for the coding of salient bottom-up signals. Exp Brain Res 2020; 238:381-393. [PMID: 31932865 PMCID: PMC7007893 DOI: 10.1007/s00221-019-05710-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 12/12/2019] [Indexed: 11/30/2022]
Abstract
The visual system forms predictions about upcoming visual features based on previous visual experiences. Such predictions impact on current perception, so that expected stimuli can be detected faster and with higher accuracy. A key question is how these predictions are formed and on which levels of processing they arise. Particularly, predictions could be formed on early levels of processing, where visual features are represented separately, or might require higher levels of processing, with predictions formed based on full object representations that involve combinations of visual features. In four experiments, the present study investigated whether the visual system forms joint prediction errors or whether expectations about different visual features such as color and orientation are formed independently. The first experiment revealed that task-irrelevant and implicitly learned expectations were formed independently when the features were separately bound to different objects. In a second experiment, no evidence for a mutual influence of both types of task-irrelevant and implicitly formed feature expectations was observed, although both visual features were assigned to the same objects. A third experiment confirmed the findings of the previous experiments for explicitly rather than implicitly formed expectations. Finally, no evidence for a mutual influence of different feature expectations was observed when features were assigned to a single centrally presented object. Overall, the present results do not support the view that object feature binding generates joint feature-based expectancies of different object features. Rather, the results suggest that expectations for color and orientation are processed and resolved independently at the feature level.
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Affiliation(s)
- Michael Wiesing
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Wilhelm-Johnen-Strasse, 52428, Juelich, Germany.
| | - Gereon R Fink
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Wilhelm-Johnen-Strasse, 52428, Juelich, Germany.,Department of Neurology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Kerpener Strasse 62, 50937, Cologne, Germany
| | - Ralph Weidner
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Wilhelm-Johnen-Strasse, 52428, Juelich, Germany
| | - Simone Vossel
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Wilhelm-Johnen-Strasse, 52428, Juelich, Germany.,Department of Psychology, Faculty of Human Sciences, University of Cologne, Gronewaldstrasse 2, 50931, Cologne, Germany
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