13 recherche sur le mot-clé 'Predictive coding'

Do Children and Adults with Autism Spectrum Condition Anticipate Others' Actions as Goal-Directed? A Predictive Coding Perspective / Kerstin GANGLMAYER in Journal of Autism and Developmental Disorders, 50-6 (June 2020)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 50-6 (June 2020) . - p.2077-2089 Titre : Do Children and Adults with Autism Spectrum Condition Anticipate Others' Actions as Goal-Directed? A Predictive Coding Perspective Type de document : texte imprimé Auteurs : Kerstin GANGLMAYER, Auteur ; Tobias SCHUWERK, Auteur ; Beate SODIAN, Auteur ; Markus PAULUS, Auteur Article en page(s) : p.2077-2089 Langues : Anglais (eng) Mots-clés : Autism spectrum condition  Cognitive processes  Eye-tracking  Goal anticipation  Predictive coding  Social cognition Index. décimale : PER Périodiques Résumé : An action's end state can be anticipated by considering the agent's goal, or simply by projecting the movement trajectory. Theories suggest that individuals with autism spectrum condition (ASC) have difficulties anticipating other's goal-directed actions, caused by an impairment using prior information. We examined whether children, adolescents and adults with and without ASC visually anticipate another's action based on its goal or movement trajectory by presenting participants an agent repeatedly taking different paths to reach the same of two targets. The ASC group anticipated the goal and not just the movement pattern, but needed more time to perform goal-directed anticipations. Results are in line with predictive coding accounts, claiming that the use of prior information is impaired in ASC. En ligne : http://dx.doi.org/10.1007/s10803-019-03964-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=425 [article] Do Children and Adults with Autism Spectrum Condition Anticipate Others' Actions as Goal-Directed? A Predictive Coding Perspective [texte imprimé] / Kerstin GANGLMAYER, Auteur ; Tobias SCHUWERK, Auteur ; Beate SODIAN, Auteur ; Markus PAULUS, Auteur . - p.2077-2089. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 50-6 (June 2020) . - p.2077-2089 Mots-clés : Autism spectrum condition  Cognitive processes  Eye-tracking  Goal anticipation  Predictive coding  Social cognition Index. décimale : PER Périodiques Résumé : An action's end state can be anticipated by considering the agent's goal, or simply by projecting the movement trajectory. Theories suggest that individuals with autism spectrum condition (ASC) have difficulties anticipating other's goal-directed actions, caused by an impairment using prior information. We examined whether children, adolescents and adults with and without ASC visually anticipate another's action based on its goal or movement trajectory by presenting participants an agent repeatedly taking different paths to reach the same of two targets. The ASC group anticipated the goal and not just the movement pattern, but needed more time to perform goal-directed anticipations. Results are in line with predictive coding accounts, claiming that the use of prior information is impaired in ASC. En ligne : http://dx.doi.org/10.1007/s10803-019-03964-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=425

Electrophysiological alterations in motor-auditory predictive coding in autism spectrum disorder / Toni VAN LAARHOVEN in Autism Research, 12-4 (April 2019)  

Public ISBD [article]  inAutism Research > 12-4 (April 2019) . - p.589-599 Titre : Electrophysiological alterations in motor-auditory predictive coding in autism spectrum disorder Type de document : texte imprimé Auteurs : Toni VAN LAARHOVEN, Auteur ; Jeroen J. STEKELENBURG, Auteur ; Mart L.J.M. EUSSEN, Auteur ; Jean VROOMEN, Auteur Article en page(s) : p.589-599 Langues : Anglais (eng) Mots-clés : ERPs  autism spectrum disorder  motor-auditory  predictive coding Index. décimale : PER Périodiques Résumé : The amplitude of the auditory N1 component of the event-related potential (ERP) is typically attenuated for self-initiated sounds, compared to sounds with identical acoustic and temporal features that are triggered externally. This effect has been ascribed to internal forward models predicting the sensory consequences of one's own motor actions. The predictive coding account of autistic symptomatology states that individuals with autism spectrum disorder (ASD) have difficulties anticipating upcoming sensory stimulation due to a decreased ability to infer the probabilistic structure of their environment. Without precise internal forward prediction models to rely on, perception in ASD could be less affected by prior expectations and more driven by sensory input. Following this reasoning, one would expect diminished attenuation of the auditory N1 due to self-initiation in individuals with ASD. Here, we tested this hypothesis by comparing the neural response to self- versus externally-initiated tones between a group of individuals with ASD and a group of age matched neurotypical controls. ERPs evoked by tones initiated via button-presses were compared with ERPs evoked by the same tones replayed at identical pace. Significant N1 attenuation effects were only found in the TD group. Self-initiation of the tones did not attenuate the auditory N1 in the ASD group, indicating that they may be unable to anticipate the auditory sensory consequences of their own motor actions. These results show that individuals with ASD have alterations in sensory attenuation of self-initiated sounds, and support the notion of impaired predictive coding as a core deficit underlying autistic symptomatology. Autism Res 2019, 12: 589-599. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Many individuals with ASD experience difficulties in processing sensory information (for example, increased sensitivity to sound). Here we show that these difficulties may be related to an inability to anticipate upcoming sensory stimulation. Our findings contribute to a better understanding of the neural mechanisms underlying the different sensory perception experienced by individuals with ASD. En ligne : https://dx.doi.org/10.1002/aur.2087 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=388 [article] Electrophysiological alterations in motor-auditory predictive coding in autism spectrum disorder [texte imprimé] / Toni VAN LAARHOVEN, Auteur ; Jeroen J. STEKELENBURG, Auteur ; Mart L.J.M. EUSSEN, Auteur ; Jean VROOMEN, Auteur . - p.589-599. Langues : Anglais (eng) in Autism Research > 12-4 (April 2019) . - p.589-599 Mots-clés : ERPs  autism spectrum disorder  motor-auditory  predictive coding Index. décimale : PER Périodiques Résumé : The amplitude of the auditory N1 component of the event-related potential (ERP) is typically attenuated for self-initiated sounds, compared to sounds with identical acoustic and temporal features that are triggered externally. This effect has been ascribed to internal forward models predicting the sensory consequences of one's own motor actions. The predictive coding account of autistic symptomatology states that individuals with autism spectrum disorder (ASD) have difficulties anticipating upcoming sensory stimulation due to a decreased ability to infer the probabilistic structure of their environment. Without precise internal forward prediction models to rely on, perception in ASD could be less affected by prior expectations and more driven by sensory input. Following this reasoning, one would expect diminished attenuation of the auditory N1 due to self-initiation in individuals with ASD. Here, we tested this hypothesis by comparing the neural response to self- versus externally-initiated tones between a group of individuals with ASD and a group of age matched neurotypical controls. ERPs evoked by tones initiated via button-presses were compared with ERPs evoked by the same tones replayed at identical pace. Significant N1 attenuation effects were only found in the TD group. Self-initiation of the tones did not attenuate the auditory N1 in the ASD group, indicating that they may be unable to anticipate the auditory sensory consequences of their own motor actions. These results show that individuals with ASD have alterations in sensory attenuation of self-initiated sounds, and support the notion of impaired predictive coding as a core deficit underlying autistic symptomatology. Autism Res 2019, 12: 589-599. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Many individuals with ASD experience difficulties in processing sensory information (for example, increased sensitivity to sound). Here we show that these difficulties may be related to an inability to anticipate upcoming sensory stimulation. Our findings contribute to a better understanding of the neural mechanisms underlying the different sensory perception experienced by individuals with ASD. En ligne : https://dx.doi.org/10.1002/aur.2087 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=388

A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder / Gerrit I. VAN SCHALKWYK in Journal of Autism and Developmental Disorders, 47-5 (May 2017)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 47-5 (May 2017) . - p.1323-1340 Titre : A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder Type de document : texte imprimé Auteurs : Gerrit I. VAN SCHALKWYK, Auteur ; Fred R. VOLKMAR, Auteur ; Philip R. CORLETT, Auteur Article en page(s) : p.1323-1340 Langues : Anglais (eng) Mots-clés : Predictive coding  ASD and psychosis  ASD and schizophrenia Index. décimale : PER Périodiques Résumé : The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions—predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top–down predictions or an enhanced weighting of bottom–up prediction errors. Likewise, autism has been explained in terms of similar perturbations. We suggest that this theoretical overlap may explain overlapping symptomatology. Experimental evidence highlights meaningful distinctions and consistencies between these disorders. We hypothesize individuals with ASD may experience some degree of delusions without the presence of any additional impairment, but that hallucinations are likely indicative of a distinct process. En ligne : http://dx.doi.org/10.1007/s10803-017-3065-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=305 [article] A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder [texte imprimé] / Gerrit I. VAN SCHALKWYK, Auteur ; Fred R. VOLKMAR, Auteur ; Philip R. CORLETT, Auteur . - p.1323-1340. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 47-5 (May 2017) . - p.1323-1340 Mots-clés : Predictive coding  ASD and psychosis  ASD and schizophrenia Index. décimale : PER Périodiques Résumé : The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions—predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top–down predictions or an enhanced weighting of bottom–up prediction errors. Likewise, autism has been explained in terms of similar perturbations. We suggest that this theoretical overlap may explain overlapping symptomatology. Experimental evidence highlights meaningful distinctions and consistencies between these disorders. We hypothesize individuals with ASD may experience some degree of delusions without the presence of any additional impairment, but that hallucinations are likely indicative of a distinct process. En ligne : http://dx.doi.org/10.1007/s10803-017-3065-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=305

Systematic Review and Meta-Analysis of Mismatch Negativity in Autism: Insights Into Predictive Mechanisms / Laurie-Anne SAPEY-TRIOMPHE in Autism Research, 18-12 (December 2025)  

Public ISBD [article]  inAutism Research > 18-12 (December 2025) . - p.2431-2450 Titre : Systematic Review and Meta-Analysis of Mismatch Negativity in Autism: Insights Into Predictive Mechanisms Type de document : texte imprimé Auteurs : Laurie-Anne SAPEY-TRIOMPHE, Auteur ; Romain BOUET, Auteur ; Jérémie MATTOUT, Auteur ; Sandrine SONIE, Auteur ; Christina SCHMITZ, Auteur ; Françoise LECAIGNARD, Auteur Article en page(s) : p.2431-2450 Langues : Anglais (eng) Mots-clés : adaptation  auditory  Autism Spectrum Disorders  EEG  mismatch negativity (MMN)  perceptual learning  predictive coding Index. décimale : PER Périodiques Résumé : ABSTRACT Mismatch negativity (MMN) has been frequently used to assess auditory processing and change detection in autism spectrum disorder (ASD), but findings have been fairly inconsistent. To address this issue, we conducted a systematic review and meta-analysis of MMN amplitude (76 effect sizes) and latency (62 effect sizes) in ASD to identify factors contributing to this heterogeneity and to interpret findings within the predictive coding framework. While residual heterogeneity remained, significant effects of the interaction between age group and design type (unifeature vs. multifeature, i.e., one or several types of deviants) and deviant type were found for MMN amplitude. In multifeature designs, autistic children and adolescents exhibited reduced MMN amplitudes compared to neurotypical peers (g?=?0.25, p?=?0.01), whereas autistic adults showed increased MMN amplitudes (g?=??0.26, p?=?0.02). In addition, autistic individuals had significantly smaller MMN amplitudes than neurotypical individuals in paradigms using phoneme deviants (g?=?0.41, p? En ligne : https://doi.org/10.1002/aur.70131 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=578 [article] Systematic Review and Meta-Analysis of Mismatch Negativity in Autism: Insights Into Predictive Mechanisms [texte imprimé] / Laurie-Anne SAPEY-TRIOMPHE, Auteur ; Romain BOUET, Auteur ; Jérémie MATTOUT, Auteur ; Sandrine SONIE, Auteur ; Christina SCHMITZ, Auteur ; Françoise LECAIGNARD, Auteur . - p.2431-2450. Langues : Anglais (eng) in Autism Research > 18-12 (December 2025) . - p.2431-2450 Mots-clés : adaptation  auditory  Autism Spectrum Disorders  EEG  mismatch negativity (MMN)  perceptual learning  predictive coding Index. décimale : PER Périodiques Résumé : ABSTRACT Mismatch negativity (MMN) has been frequently used to assess auditory processing and change detection in autism spectrum disorder (ASD), but findings have been fairly inconsistent. To address this issue, we conducted a systematic review and meta-analysis of MMN amplitude (76 effect sizes) and latency (62 effect sizes) in ASD to identify factors contributing to this heterogeneity and to interpret findings within the predictive coding framework. While residual heterogeneity remained, significant effects of the interaction between age group and design type (unifeature vs. multifeature, i.e., one or several types of deviants) and deviant type were found for MMN amplitude. In multifeature designs, autistic children and adolescents exhibited reduced MMN amplitudes compared to neurotypical peers (g?=?0.25, p?=?0.01), whereas autistic adults showed increased MMN amplitudes (g?=??0.26, p?=?0.02). In addition, autistic individuals had significantly smaller MMN amplitudes than neurotypical individuals in paradigms using phoneme deviants (g?=?0.41, p? En ligne : https://doi.org/10.1002/aur.70131 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=578

Do autistic individuals show atypical performance in probabilistic learning? A comparison of cue-number, predictive strength, and prediction error / Lei ZHANG ; Fang LIU in Molecular Autism, 16 (2025)  

Public ISBD [article]  inMolecular Autism > 16 (2025) . - 15 Titre : Do autistic individuals show atypical performance in probabilistic learning? A comparison of cue-number, predictive strength, and prediction error Type de document : texte imprimé Auteurs : Lei ZHANG, Auteur ; Fang LIU, Auteur Article en page(s) : 15 Langues : Anglais (eng) Mots-clés : Humans  Autistic Disorder/psychology/physiopathology/diagnosis  Cues  Male  Adult  Female  Probability Learning  Young Adult  Reinforcement, Psychology  Learning  Associative learning  Bayesian  Prediction errors  Predictive coding  Probabilistic learning  Reinforcement learning  reviewed and approved by the University Research Ethics Committee (UREC) at the  University of Reading (reference number: UREC 20/28). All participants provided  their written informed consent prior to their participation. Consent for  publication: Not applicable. Competing interests: The authors declare no  competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: According to recent models of autism, autistic individuals may find learning probabilistic cue-outcome associations more challenging than deterministic learning, though empirical evidence for this is mixed. Here we examined the mechanism of probabilistic learning more closely by comparing autistic and non-autistic adults on inferring a target cue from multiple cues or integrating multiple target cues and learning from associations with various predictive strengths. METHODS: 52 autistic and 52 non-autistic participants completed three tasks: (i) single-cue probabilistic learning, in which they had to infer a single target cue from multiple cues to learn cue-outcome associations; (ii) multi-cue probabilistic learning, in which they had to learn associations of various predictive strengths via integration of multiple cues; and (iii) reinforcement learning, which required learning the contingencies of two stimuli with a probabilistic reinforcement schedule. Accuracy on the two probabilistic learning tasks was modelled separately using a binomial mixed effects model whereas computational modelling was performed on the reinforcement learning data to obtain a model parameter on prediction error integration (i.e., learning rate). RESULTS: No group differences were found in the single-cue probabilistic learning task. Group differences were evident for the multi-cue probabilistic learning task for associations that are weakly predictive (between 40 and 60%) but not when they are strongly predictive (10-20% or 80-90%). Computational modelling on the reinforcement learning task revealed that, as a group, autistic individuals had a higher learning rate than non-autistic individuals. LIMITATIONS: Due to the online nature of the study, we could not confirm the diagnosis of our autistic sample. The autistic participants were likely to have typical intelligence, and so our findings may not be generalisable to the entire autistic population. The learning tasks are constrained by a relatively small number of trials, and so it is unclear whether group differences will still be seen when given more trials. CONCLUSIONS: Autistic adults showed similar performance as non-autistic adults in learning associations by inferring a single cue or integrating multiple cues when the predictive strength was strong. However, non-autistic adults outperformed autistic adults when the predictive strength was weak, but only in the later phase. Autistic individuals were also more likely to incorporate prediction errors during decision making, which may explain their atypical performance on the weakly predictive associations. Our findings have implications for understanding differences in social cognition, which is often noisy and weakly predictive, among autistic individuals. En ligne : https://dx.doi.org/10.1186/s13229-025-00651-7 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=555 [article] Do autistic individuals show atypical performance in probabilistic learning? A comparison of cue-number, predictive strength, and prediction error [texte imprimé] / Lei ZHANG, Auteur ; Fang LIU, Auteur . - 15. Langues : Anglais (eng) in Molecular Autism > 16 (2025) . - 15 Mots-clés : Humans  Autistic Disorder/psychology/physiopathology/diagnosis  Cues  Male  Adult  Female  Probability Learning  Young Adult  Reinforcement, Psychology  Learning  Associative learning  Bayesian  Prediction errors  Predictive coding  Probabilistic learning  Reinforcement learning  reviewed and approved by the University Research Ethics Committee (UREC) at the  University of Reading (reference number: UREC 20/28). All participants provided  their written informed consent prior to their participation. Consent for  publication: Not applicable. Competing interests: The authors declare no  competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: According to recent models of autism, autistic individuals may find learning probabilistic cue-outcome associations more challenging than deterministic learning, though empirical evidence for this is mixed. Here we examined the mechanism of probabilistic learning more closely by comparing autistic and non-autistic adults on inferring a target cue from multiple cues or integrating multiple target cues and learning from associations with various predictive strengths. METHODS: 52 autistic and 52 non-autistic participants completed three tasks: (i) single-cue probabilistic learning, in which they had to infer a single target cue from multiple cues to learn cue-outcome associations; (ii) multi-cue probabilistic learning, in which they had to learn associations of various predictive strengths via integration of multiple cues; and (iii) reinforcement learning, which required learning the contingencies of two stimuli with a probabilistic reinforcement schedule. Accuracy on the two probabilistic learning tasks was modelled separately using a binomial mixed effects model whereas computational modelling was performed on the reinforcement learning data to obtain a model parameter on prediction error integration (i.e., learning rate). RESULTS: No group differences were found in the single-cue probabilistic learning task. Group differences were evident for the multi-cue probabilistic learning task for associations that are weakly predictive (between 40 and 60%) but not when they are strongly predictive (10-20% or 80-90%). Computational modelling on the reinforcement learning task revealed that, as a group, autistic individuals had a higher learning rate than non-autistic individuals. LIMITATIONS: Due to the online nature of the study, we could not confirm the diagnosis of our autistic sample. The autistic participants were likely to have typical intelligence, and so our findings may not be generalisable to the entire autistic population. The learning tasks are constrained by a relatively small number of trials, and so it is unclear whether group differences will still be seen when given more trials. CONCLUSIONS: Autistic adults showed similar performance as non-autistic adults in learning associations by inferring a single cue or integrating multiple cues when the predictive strength was strong. However, non-autistic adults outperformed autistic adults when the predictive strength was weak, but only in the later phase. Autistic individuals were also more likely to incorporate prediction errors during decision making, which may explain their atypical performance on the weakly predictive associations. Our findings have implications for understanding differences in social cognition, which is often noisy and weakly predictive, among autistic individuals. En ligne : https://dx.doi.org/10.1186/s13229-025-00651-7 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=555

Acquisition and Use of 'Priors' in Autism: Typical in Deciding Where to Look, Atypical in Deciding What Is There / Fredrik ALLENMARK in Journal of Autism and Developmental Disorders, 51-10 (October 2021)  

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Priors Bias Perceptual Decisions in Autism, But Are Less Flexibly Adjusted to the Context / Laurie-Anne SAPEY-TRIOMPHE in Autism Research, 14-6 (June 2021)  

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Sensory responsivity and its relation to alexithymia, social processing and restricted interests and repetitive behaviour in autistic children / Madeleine DIEPMAN in Research in Autism Spectrum Disorders, 118 (October 2024)  

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Structural and contextual priors affect visual search in children with and without autism / Sander VAN DE CRUYS in Autism Research, 14-7 (July 2021)  

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Atypical perception in autism: A failure of perceptual specialization? / Bat-Sheva HADAD in Autism Research, 10-9 (September 2017)  

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