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Ward EK, Buitelaar JK, Hunnius S. Autistic and nonautistic adolescents do not differ in adaptation to gaze direction. Autism Res 2024; 17:1001-1015. [PMID: 38433357 DOI: 10.1002/aur.3118] [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: 05/17/2023] [Accepted: 02/18/2024] [Indexed: 03/05/2024]
Abstract
Predictive processing accounts of autism posit that autistic individuals' perception is less biased by expectations than nonautistic individuals', perhaps through stronger precision-weighting of prediction errors. Since precision-weighting is fundamental to all information processing, under this theory, the differences between autistic and nonautistic individuals should be domain-general and observable in both behavior and brain responses. This study used EEG, behavioral responses, and eye-tracking co-registration during gaze-direction adaptation, to investigate whether increased precision-weighting of prediction errors is evident through smaller adaptation after-effects in autistic adolescents compared with nonautistic peers. Multilevel modeling showed that autistic and nonautistic adolescents' responses were consistent with behavioral adaptation, with Bayesian statistics providing extremely strong evidence for the absence of a group difference. Cluster-based permutation testing of ERP responses did not show the expected adaptation after-effect but did show habituation to repeated stimulus presentation, and no group difference was detected, a result not consistent with the theoretical account. Combined with the few other available studies, the current findings raise challenges for the theory, suggesting no fundamental difference in precision-weighting of prediction errors in autism.
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Affiliation(s)
- Emma K Ward
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Birkbeck, University of London, London, UK
| | - Jan K Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Sabine Hunnius
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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2
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Beeckmans M, Huycke P, Verguts T, Verbeke P. How much data do we need to estimate computational models of decision-making? The COMPASS toolbox. Behav Res Methods 2024; 56:2537-2548. [PMID: 37369937 DOI: 10.3758/s13428-023-02165-7] [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] [Accepted: 06/06/2023] [Indexed: 06/29/2023]
Abstract
How much data are needed to obtain useful parameter estimations from a computational model? The standard approach to address this question is to carry out a goodness-of-recovery study. Here, the correlation between individual-participant true and estimated parameter values determines when a sample size is large enough. However, depending on one's research question, this approach may be suboptimal, potentially leading to sample sizes that are either too small (underpowered) or too large (overcostly or unfeasible). In this paper, we formulate a generalized concept of statistical power and use this to propose a novel approach toward determining how much data is needed to obtain useful parameter estimates from a computational model. We describe a Python-based toolbox (COMPASS) that allows one to determine how many participants are needed to fit one specific computational model, namely the Rescorla-Wagner model of learning and decision-making. Simulations revealed that a high number of trials per person (more than the number of persons) are a prerequisite for high-powered studies in this particular setting.
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Affiliation(s)
- Maud Beeckmans
- Rehabilitation Research Institute (REVAL), Hasselt University, Hasselt, Belgium
- Department of Imaging and Pathology, Catholic University Leuven, Leuven, Belgium
| | - Pieter Huycke
- Department of experimental psychology, Ghent University, Ghent, Belgium
| | - Tom Verguts
- Department of experimental psychology, Ghent University, Ghent, Belgium
| | - Pieter Verbeke
- Department of experimental psychology, Ghent University, Ghent, Belgium.
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3
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Lage C, Smith ES, Lawson RP. A meta-analysis of cognitive flexibility in autism spectrum disorder. Neurosci Biobehav Rev 2024; 157:105511. [PMID: 38104788 DOI: 10.1016/j.neubiorev.2023.105511] [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: 09/06/2023] [Revised: 12/04/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023]
Abstract
Cognitive flexibility is a fundamental process that underlies adaptive behaviour in response to environmental change. Studies examining the profile of cognitive flexibility in autism spectrum disorder (ASD) have reported inconsistent findings. To address whether difficulties with cognitive flexibility are characteristic of autism, we conducted a random-effects meta-analysis and employed subgroup analyses and meta-regression to assess the impact of relevant moderator variables such as task, outcomes, and age. Fifty-nine studies were included and comprised of 2122 autistic individuals without intellectual disabilities and 2036 neurotypical controls, with an age range of 4 to 85 years. The results showed that autistic individuals have greater difficulties with cognitive flexibility, with an overall statistically significant small to moderate effect size. Subgroup analyses revealed a significant difference between task outcomes, with perseverative errors obtaining the largest effect size. In summary, the present meta-analysis highlights the existence of cognitive flexibility difficulties in autistic people, in the absence of learning disabilities, but also that this profile is characterised by substantial heterogeneity. Potential contributing factors are discussed.
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Affiliation(s)
- Claudia Lage
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom.
| | - Eleanor S Smith
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom
| | - Rebecca P Lawson
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom
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4
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Sapey-Triomphe LA, Sanchez G, Hénaff MA, Sonié S, Schmitz C, Mattout J. Disentangling sensory precision and prior expectation of change in autism during tactile discrimination. NPJ SCIENCE OF LEARNING 2023; 8:54. [PMID: 38057355 DOI: 10.1038/s41539-023-00207-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 11/17/2023] [Indexed: 12/08/2023]
Abstract
Predictive coding theories suggest that core symptoms in autism spectrum disorders (ASD) may stem from atypical mechanisms of perceptual inference (i.e., inferring the hidden causes of sensations). Specifically, there would be an imbalance in the precision or weight ascribed to sensory inputs relative to prior expectations. Using three tactile behavioral tasks and computational modeling, we specifically targeted the implicit dynamics of sensory adaptation and perceptual learning in ASD. Participants were neurotypical and autistic adults without intellectual disability. In Experiment I, tactile detection thresholds and adaptation effects were measured to assess sensory precision. Experiments II and III relied on two-alternative forced choice tasks designed to elicit a time-order effect, where prior knowledge biases perceptual decisions. Our results suggest a subtler explanation than a simple imbalance in the prior/sensory weights, having to do with the dynamic nature of perception, that is the adjustment of precision weights to context. Compared to neurotypicals, autistic adults showed no difference in average performance and sensory sensitivity. Both groups managed to implicitly learn and adjust a prior that biased their perception. However, depending on the context, autistic participants showed no, normal or slower adaptation, a phenomenon that computational modeling of trial-to-trial responses helped us to associate with a higher expectation for sameness in ASD, and to dissociate from another observed robust difference in terms of response bias. These results point to atypical perceptual learning rather than altered perceptual inference per se, calling for further empirical and computational studies to refine the current predictive coding theories of ASD.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Université Claude Bernard Lyon 1, CNRS UMR5292, INSERM U1028, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, COPHY, F-69500, Bron, France.
| | - Gaëtan Sanchez
- Université Claude Bernard Lyon 1, CNRS UMR5292, INSERM U1028, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, COPHY, F-69500, Bron, France
| | - Marie-Anne Hénaff
- Université Claude Bernard Lyon 1, CNRS UMR5292, INSERM U1028, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, COPHY, F-69500, Bron, France
| | - Sandrine Sonié
- Université Claude Bernard Lyon 1, CNRS UMR5292, INSERM U1028, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, COPHY, F-69500, Bron, France
- Centre de Ressource Autisme Rhône-Alpes, Centre Hospitalier Le Vinatier, Bron, France
- Hôpital Saint-Jean-de-Dieu, Lyon, France
| | - Christina Schmitz
- Université Claude Bernard Lyon 1, CNRS UMR5292, INSERM U1028, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, COPHY, F-69500, Bron, France
| | - Jérémie Mattout
- Université Claude Bernard Lyon 1, CNRS UMR5292, INSERM U1028, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, COPHY, F-69500, Bron, France
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5
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Naamani G, Shahar N, Ger Y, Yovel Y. Fruit bats adjust their decision-making process according to environmental dynamics. BMC Biol 2023; 21:278. [PMID: 38031023 PMCID: PMC10687778 DOI: 10.1186/s12915-023-01774-0] [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: 11/21/2023] [Indexed: 12/01/2023] Open
Abstract
One of the main functions of behavioral plasticity lies in the ability to contend with dynamic environments. Indeed, while numerous studies have shown that animals adapt their behavior to the environment, how they adapt their latent learning and decision strategies to changes in the environment is less understood. Here, we used a controlled experiment to examine the bats' ability to adjust their decision strategy according to the environmental dynamics. Twenty-five Egyptian fruit bats were placed individually in either a stable or a volatile environment for four consecutive nights. In the stable environment, two feeders offered food, each with a different reward probability (0.2 vs. 0.8) that remained fixed over two nights and were then switched, while in the volatile environment, the positions of the more and the less rewarding feeders were changed every hour. We then fit two alternative commonly used models namely, reinforcement learning and win-stay-lose-shift strategies to the bats' behavior. We found that while the bats adapted their decision-making strategy to the environmental dynamics, they seemed to be limited in their responses based on natural priors. Namely, when the environment had changed slowly, at a rate that is natural for these bats, they seemed to rely on reinforcement learning and their performance was nearly optimal, but when the experimental environment changed much faster than in the natural environment, the bats stopped learning and switched to a random decision-making strategy. Together, these findings exemplify both the bats' decision-making plasticity as well as its natural limitations.
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Affiliation(s)
- Goni Naamani
- School of Zoology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel.
| | - Nitzan Shahar
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel
- The School of Psychological Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Yoav Ger
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Yossi Yovel
- School of Zoology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel
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6
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Arthur T, Brosnan M, Harris D, Buckingham G, Wilson M, Williams G, Vine S. Investigating how Explicit Contextual Cues Affect Predictive Sensorimotor Control in Autistic Adults. J Autism Dev Disord 2023; 53:4368-4381. [PMID: 36063311 PMCID: PMC10539449 DOI: 10.1007/s10803-022-05718-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/08/2022] [Indexed: 12/21/2022]
Abstract
Research suggests that sensorimotor difficulties in autism could be reduced by providing individuals with explicit contextual information. To test this, we examined autistic visuomotor control during a virtual racquetball task, in which participants hit normal and unexpectedly-bouncy balls using a handheld controller. The probability of facing each type of ball was varied unpredictably over time. However, during cued trials, participants received explicit information about the likelihood of facing each uncertain outcome. When compared to neurotypical controls, autistic individuals displayed poorer task performance, atypical gaze profiles, and more restricted swing kinematics. These visuomotor patterns were not significantly affected by contextual cues, indicating that autistic people exhibit underlying differences in how prior information and environmental uncertainty are dynamically modulated during movement tasks.
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Affiliation(s)
- Tom Arthur
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK.
- Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, BA2 7AY, UK.
| | - Mark Brosnan
- Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, BA2 7AY, UK
| | - David Harris
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK
| | - Gavin Buckingham
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK
| | - Mark Wilson
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK
| | - Genevieve Williams
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK
| | - Sam Vine
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK.
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7
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Ong JH, Liu F. Probabilistic Learning of Cue-Outcome Associations is not Influenced by Autistic Traits. J Autism Dev Disord 2023; 53:4047-4059. [PMID: 35951205 PMCID: PMC9366807 DOI: 10.1007/s10803-022-05690-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/17/2022] [Indexed: 11/12/2022]
Abstract
According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to infer which cue(s) among many to track. Across two experiments, we compared adult learners with varying levels of autistic traits on their ability to infer the correct cue to learn probabilistic cue-outcome associations when explicitly instructed to do so or when exposed implicitly. We found no evidence for the effect of autistic traits on probabilistic learning accuracy, contrary to the predictions of Bayesian/predictive coding models. Implications for the current Bayesian/predictive coding models are discussed.
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Affiliation(s)
- Jia Hoong Ong
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Fang Liu
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
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8
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Björlin Avdic H, Strannegård C, Engberg H, Willfors C, Nordgren I, Frisén L, Hirschberg AL, Guath M, Nordgren A, Kleberg JL. Reduced effects of social feedback on learning in Turner syndrome. Sci Rep 2023; 13:15858. [PMID: 37739980 PMCID: PMC10516979 DOI: 10.1038/s41598-023-42628-7] [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: 03/31/2023] [Accepted: 09/12/2023] [Indexed: 09/24/2023] Open
Abstract
Turner syndrome is a genetic condition caused by a complete or partial loss of one of the X chromosomes. Previous studies indicate that Turner syndrome is associated with challenges in social skills, but the underlying mechanisms remain largely unexplored. A possible mechanism is a reduced social influence on learning. The current study examined the impact of social and non-social feedback on learning in women with Turner syndrome (n = 35) and a sex- and age-matched control group (n = 37). Participants were instructed to earn points by repeatedly choosing between two stimuli with unequal probabilities of resulting in a reward. Mastering the task therefore required participants to learn through feedback which of the two stimuli was more likely to be rewarded. Data were analyzed using computational modeling and analyses of choice behavior. Social feedback led to a more explorative choice behavior in the control group, resulting in reduced learning compared to non-social feedback. No effects of social feedback on learning were found in Turner syndrome. The current study thus indicates that women with Turner syndrome may be less sensitive to social influences on reinforcement learning, than the general population.
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Affiliation(s)
- Hanna Björlin Avdic
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
| | - Claes Strannegård
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Division of Cognition and Communication, Department of Applied IT, University of Gothenburg, Gothenburg, Sweden
| | - Hedvig Engberg
- Department of Women's and Children's Health, Karolinska Institutet & Department of Gynaecology and Reproductive Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Charlotte Willfors
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ida Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Louise Frisén
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Angelica Lindén Hirschberg
- Department of Women's and Children's Health, Karolinska Institutet & Department of Gynaecology and Reproductive Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Mona Guath
- Department of Psychology, Uppsala University, Uppsala, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Lundin Kleberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Psychology, Stockholm University, Stockholm, Sweden
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9
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Arthur T, Vine S, Buckingham G, Brosnan M, Wilson M, Harris D. Testing predictive coding theories of autism spectrum disorder using models of active inference. PLoS Comput Biol 2023; 19:e1011473. [PMID: 37695796 PMCID: PMC10529610 DOI: 10.1371/journal.pcbi.1011473] [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: 02/28/2023] [Revised: 09/27/2023] [Accepted: 08/28/2023] [Indexed: 09/13/2023] Open
Abstract
Several competing neuro-computational theories of autism have emerged from predictive coding models of the brain. To disentangle their subtly different predictions about the nature of atypicalities in autistic perception, we performed computational modelling of two sensorimotor tasks: the predictive use of manual gripping forces during object lifting and anticipatory eye movements during a naturalistic interception task. In contrast to some accounts, we found no evidence of chronic atypicalities in the use of priors or weighting of sensory information during object lifting. Differences in prior beliefs, rates of belief updating, and the precision weighting of prediction errors were, however, observed for anticipatory eye movements. Most notably, we observed autism-related difficulties in flexibly adapting learning rates in response to environmental change (i.e., volatility). These findings suggest that atypical encoding of precision and context-sensitive adjustments provide a better explanation of autistic perception than generic attenuation of priors or persistently high precision prediction errors. Our results did not, however, support previous suggestions that autistic people perceive their environment to be persistently volatile.
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Affiliation(s)
- Tom Arthur
- School of Public Health and Sport Sciences, Medical School, University of Exeter, Exeter, United Kingdom
- Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, United Kingdom
| | - Sam Vine
- School of Public Health and Sport Sciences, Medical School, University of Exeter, Exeter, United Kingdom
| | - Gavin Buckingham
- School of Public Health and Sport Sciences, Medical School, University of Exeter, Exeter, United Kingdom
| | - Mark Brosnan
- Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, United Kingdom
| | - Mark Wilson
- School of Public Health and Sport Sciences, Medical School, University of Exeter, Exeter, United Kingdom
| | - David Harris
- School of Public Health and Sport Sciences, Medical School, University of Exeter, Exeter, United Kingdom
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10
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Pesthy O, Farkas K, Sapey-Triomphe LA, Guttengéber A, Komoróczy E, Janacsek K, Réthelyi JM, Németh D. Intact predictive processing in autistic adults: evidence from statistical learning. Sci Rep 2023; 13:11873. [PMID: 37481676 PMCID: PMC10363128 DOI: 10.1038/s41598-023-38708-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/13/2023] [Indexed: 07/24/2023] Open
Abstract
Impairment in predictive processes gained a lot of attention in recent years as an explanation for autistic symptoms. However, empirical evidence does not always underpin this framework. Thus, it is unclear what aspects of predictive processing are affected in autism spectrum disorder. In this study, we tested autistic adults on a task in which participants acquire probability-based regularities (that is, a statistical learning task). Twenty neurotypical and 22 autistic adults learned a probabilistic, temporally distributed regularity for about 40 min. Using frequentist and Bayesian methods, we found that autistic adults performed comparably to neurotypical adults, and the dynamics of learning did not differ between groups either. Thus, our study provides evidence for intact statistical learning in autistic adults. Furthermore, we discuss potential ways this result can extend the scope of the predictive processing framework, noting that atypical processing might not always mean a deficit in performance.
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Affiliation(s)
- Orsolya Pesthy
- Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Research Centre for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Budapest, Hungary
| | - Kinga Farkas
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Laurie-Anne Sapey-Triomphe
- Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, Lyon, France
| | - Anna Guttengéber
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Department of Clinical Psychology, Semmelweis University, Budapest, Hungary
| | - Eszter Komoróczy
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Karolina Janacsek
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Faculty of Education, Health and Human Sciences, Centre for Thinking and Learning, School of Human Sciences, Institute for Lifecourse Development, University of Greenwich, London, UK
| | - János M Réthelyi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Dezső Németh
- Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, Lyon, France.
- BML-NAP Research Group, Institute of Psychology & Institute of Cognitive Neuroscience and Psychology, Eötvös Loránd University & Research Centre for Natural Sciences, Budapest, Hungary.
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11
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Sapey-Triomphe LA, Pattyn L, Weilnhammer V, Sterzer P, Wagemans J. Neural correlates of hierarchical predictive processes in autistic adults. Nat Commun 2023; 14:3640. [PMID: 37336874 DOI: 10.1038/s41467-023-38580-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 05/08/2023] [Indexed: 06/21/2023] Open
Abstract
Bayesian theories of autism spectrum disorders (ASD) suggest that atypical predictive mechanisms could underlie the autistic symptomatology, but little is known about their neural correlates. Twenty-six neurotypical (NT) and 26 autistic adults participated in an fMRI study where they performed an associative learning task in a volatile environment. By inverting a model of perceptual inference, we characterized the neural correlates of hierarchically structured predictions and prediction errors in ASD. Behaviorally, the predictive abilities of autistic adults were intact. Neurally, predictions were encoded hierarchically in both NT and ASD participants and biased their percepts. High-level predictions were following activity levels in a set of regions more closely in ASD than NT. Prediction errors yielded activation in shared regions in NT and ASD, but group differences were found in the anterior cingulate cortex and putamen. This study sheds light on the neural specificities of ASD that might underlie atypical predictive processing.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium.
- Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium.
| | - Lauren Pattyn
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
| | - Veith Weilnhammer
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany
- Berlin Institute of Health, Charité-Universitätsmedizin Berlin, 10178, Berlin, Germany
| | - Philipp Sterzer
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany
- Berlin Institute of Health, Charité-Universitätsmedizin Berlin, 10178, Berlin, Germany
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium
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12
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Sandhu TR, Xiao B, Lawson RP. Transdiagnostic computations of uncertainty: towards a new lens on intolerance of uncertainty. Neurosci Biobehav Rev 2023; 148:105123. [PMID: 36914079 DOI: 10.1016/j.neubiorev.2023.105123] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/21/2023] [Accepted: 03/08/2023] [Indexed: 03/13/2023]
Abstract
People radically differ in how they cope with uncertainty. Clinical researchers describe a dispositional characteristic known as "intolerance of uncertainty", a tendency to find uncertainty aversive, reported to be elevated across psychiatric and neurodevelopmental conditions. Concurrently, recent research in computational psychiatry has leveraged theoretical work to characterise individual differences in uncertainty processing. Under this framework, differences in how people estimate different forms of uncertainty can contribute to mental health difficulties. In this review, we briefly outline the concept of intolerance of uncertainty within its clinical context, and we argue that the mechanisms underlying this construct may be further elucidated through modelling how individuals make inferences about uncertainty. We will review the evidence linking psychopathology to different computationally specified forms of uncertainty and consider how these findings might suggest distinct mechanistic routes towards intolerance of uncertainty. We also discuss the implications of this computational approach for behavioural and pharmacological interventions, as well as the importance of different cognitive domains and subjective experiences in studying uncertainty processing.
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Affiliation(s)
- Timothy R Sandhu
- Department of Psychology, Downing Place, University of Cambridge, CB2 3EB, UK; MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, CB2 7EF, UK.
| | - Bowen Xiao
- Department of Psychology, Downing Place, University of Cambridge, CB2 3EB, UK
| | - Rebecca P Lawson
- Department of Psychology, Downing Place, University of Cambridge, CB2 3EB, UK; MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, CB2 7EF, UK
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13
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Angeletos Chrysaitis N, Seriès P. 10 years of Bayesian theories of autism: A comprehensive review. Neurosci Biobehav Rev 2023; 145:105022. [PMID: 36581168 DOI: 10.1016/j.neubiorev.2022.105022] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 12/24/2022] [Indexed: 12/27/2022]
Abstract
Ten years ago, Pellicano and Burr published one of the most influential articles in the study of autism spectrum disorders, linking them to aberrant Bayesian inference processes in the brain. In particular, they proposed that autistic individuals are less influenced by their brains' prior beliefs about the environment. In this systematic review, we investigate if this theory is supported by the experimental evidence. To that end, we collect all studies which included comparisons across diagnostic groups or autistic traits and categorise them based on the investigated priors. Our results are highly mixed, with a slight majority of studies finding no difference in the integration of Bayesian priors. We find that priors developed during the experiments exhibited reduced influences more frequently than priors acquired previously, with various studies providing evidence for learning differences between participant groups. Finally, we focus on the methodological and computational aspects of the included studies, showing low statistical power and often inconsistent approaches. Based on our findings, we propose guidelines for future research.
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Affiliation(s)
- Nikitas Angeletos Chrysaitis
- Institute for Adaptive and Neural Computation, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom.
| | - Peggy Seriès
- Institute for Adaptive and Neural Computation, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom.
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14
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Spee BTM, Sladky R, Fingerhut J, Laciny A, Kraus C, Carls-Diamante S, Brücke C, Pelowski M, Treven M. Repeating patterns: Predictive processing suggests an aesthetic learning role of the basal ganglia in repetitive stereotyped behaviors. Front Psychol 2022; 13:930293. [PMID: 36160532 PMCID: PMC9497189 DOI: 10.3389/fpsyg.2022.930293] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
Recurrent, unvarying, and seemingly purposeless patterns of action and cognition are part of normal development, but also feature prominently in several neuropsychiatric conditions. Repetitive stereotyped behaviors (RSBs) can be viewed as exaggerated forms of learned habits and frequently correlate with alterations in motor, limbic, and associative basal ganglia circuits. However, it is still unclear how altered basal ganglia feedback signals actually relate to the phenomenological variability of RSBs. Why do behaviorally overlapping phenomena sometimes require different treatment approaches−for example, sensory shielding strategies versus exposure therapy for autism and obsessive-compulsive disorder, respectively? Certain clues may be found in recent models of basal ganglia function that extend well beyond action selection and motivational control, and have implications for sensorimotor integration, prediction, learning under uncertainty, as well as aesthetic learning. In this paper, we systematically compare three exemplary conditions with basal ganglia involvement, obsessive-compulsive disorder, Parkinson’s disease, and autism spectrum conditions, to gain a new understanding of RSBs. We integrate clinical observations and neuroanatomical and neurophysiological alterations with accounts employing the predictive processing framework. Based on this review, we suggest that basal ganglia feedback plays a central role in preconditioning cortical networks to anticipate self-generated, movement-related perception. In this way, basal ganglia feedback appears ideally situated to adjust the salience of sensory signals through precision weighting of (external) new sensory information, relative to the precision of (internal) predictions based on prior generated models. Accordingly, behavioral policies may preferentially rely on new data versus existing knowledge, in a spectrum spanning between novelty and stability. RSBs may then represent compensatory or reactive responses, respectively, at the opposite ends of this spectrum. This view places an important role of aesthetic learning on basal ganglia feedback, may account for observed changes in creativity and aesthetic experience in basal ganglia disorders, is empirically testable, and may inform creative art therapies in conditions characterized by stereotyped behaviors.
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Affiliation(s)
- Blanca T. M. Spee
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Radboud University Medical Center, Nijmegen, Netherlands
| | - Ronald Sladky
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Joerg Fingerhut
- Berlin School of Mind and Brain, Department of Philosophy, Humboldt-Universität zu Berlin, Berlin, Germany
- Faculty of Philosophy, Philosophy of Science and Religious Studies, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Alice Laciny
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria
| | - Christoph Kraus
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Medical Neuroscience Cluster, Medical University of Vienna, Vienna, Austria
| | | | - Christof Brücke
- Medical Neuroscience Cluster, Medical University of Vienna, Vienna, Austria
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Matthew Pelowski
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Marco Treven
- Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria
- Medical Neuroscience Cluster, Medical University of Vienna, Vienna, Austria
- Department of Neurology, Medical University of Vienna, Vienna, Austria
- *Correspondence: Marco Treven,
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15
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Hadad BS, Yashar A. Sensory Perception in Autism: What Can We Learn? Annu Rev Vis Sci 2022; 8:239-264. [PMID: 35804481 DOI: 10.1146/annurev-vision-093020-035217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Autism is a neurodevelopmental disorder of unknown etiology. Recently, there has been a growing interest in sensory processing in autism as a core phenotype. However, basic questions remain unanswered. Here, we review the major findings and models of perception in autism and point to methodological issues that have led to conflicting results. We show that popular models of perception in autism, such as the reduced prior hypothesis, cannot explain the many and varied findings. To resolve these issues, we point to the benefits of using rigorous psychophysical methods to study perception in autism. We advocate for perceptual models that provide a detailed explanation of behavior while also taking into account factors such as context, learning, and attention. Furthermore, we demonstrate the importance of tracking changes over the course of development to reveal the causal pathways and compensatory mechanisms. Finally, we propose a developmental perceptual narrowing account of the condition. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Bat-Sheva Hadad
- Department of Special Education and The Edmond J. Safra Brain Research Center, University of Haifa, Haifa, Israel; ,
| | - Amit Yashar
- Department of Special Education and The Edmond J. Safra Brain Research Center, University of Haifa, Haifa, Israel; ,
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16
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Ellis Weismer S, Saffran JR. Differences in Prediction May Underlie Language Disorder in Autism. Front Psychol 2022; 13:897187. [PMID: 35756305 PMCID: PMC9221834 DOI: 10.3389/fpsyg.2022.897187] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/19/2022] [Indexed: 01/01/2023] Open
Abstract
Language delay is often one of the first concerns of parents of toddlers with autism spectrum disorder (ASD), and early language abilities predict broader outcomes for children on the autism spectrum. Yet, mechanisms underlying language deficits in autistic children remain underspecified. One prominent component of linguistic behavior is the use of predictions or expectations during learning and processing. Several researcher teams have posited prediction deficit accounts of ASD. The basic assumption of the prediction accounts is that information is processed by making predictions and testing violations against expectations (prediction errors). Flexible (neurotypical) brains attribute differential weights to prediction errors to determine when new learning is appropriate, while autistic individuals are thought to assign disproportionate weight to prediction errors. According to some views, these prediction deficits are hypothesized to lead to higher levels of perceived novelty, resulting in “hyperplasticity” of learning based on the most recent input. In this article, we adopt the perspective that it would be useful to investigate whether language deficits in children with ASD can be attributed to atypical domain-general prediction processes.
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Affiliation(s)
- Susan Ellis Weismer
- Waisman Center, University of Wisconsin, Madison, WI, United States.,Department of Communication Sciences and Disorders, University of Wisconsin, Madison, WI, United States
| | - Jenny R Saffran
- Waisman Center, University of Wisconsin, Madison, WI, United States.,Department of Psychology, University of Wisconsin, Madison, WI, United States
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17
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Binur N, Hel-Or H, Hadad BS. Individuals with autism show non-adaptive relative weighting of perceptual prior and sensory reliability. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 26:2052-2065. [PMID: 35317640 DOI: 10.1177/13623613221074416] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
LAY ABSTRACT Unique perceptual skills and abnormalities in perception have been extensively demonstrated in those with autism for many perceptual domains, accounting, at least in part, for some of the main symptoms. Several new hypotheses suggest that perceptual representations in autism are unrefined, appear less constrained by exposure and regularities of the environment, and rely more on actual concrete input. Consistent with these emerging views, a bottom-up, data-driven fashion of processing has been suggested to account for the atypical perception in autism. It is yet unclear, however, whether reduced effects of prior knowledge and top-down information, or rather reduced noise in the sensory input, account for the often-reported bottom-up mode of processing in autism. We show that neither is sufficiently supported. Instead, we demonstrate clear differences between autistics and neurotypicals in how incoming input is weighted against prior knowledge and experience in determining the final percept. Importantly, the findings tap central differences in perception between those with and without autism that are consistent across identified sub-clusters within each group.
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Affiliation(s)
| | | | - Bat-Sheva Hadad
- University of Haifa, Israel.,Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, Israel
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18
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Rybicki AJ, Sowden SL, Schuster B, Cook JL. Dopaminergic challenge dissociates learning from primary versus secondary sources of information. eLife 2022; 11:74893. [PMID: 35289748 PMCID: PMC9023054 DOI: 10.7554/elife.74893] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Some theories of human cultural evolution posit that humans have social-specific learning mechanisms that are adaptive specialisations moulded by natural selection to cope with the pressures of group living. However, the existence of neurochemical pathways that are specialised for learning from social information and individual experience is widely debated. Cognitive neuroscientific studies present mixed evidence for social-specific learning mechanisms: some studies find dissociable neural correlates for social and individual learning, whereas others find the same brain areas and, dopamine-mediated, computations involved in both. Here, we demonstrate that, like individual learning, social learning is modulated by the dopamine D2 receptor antagonist haloperidol when social information is the primary learning source, but not when it comprises a secondary, additional element. Two groups (total N = 43) completed a decision-making task which required primary learning, from own experience, and secondary learning from an additional source. For one group, the primary source was social, and secondary was individual; for the other group this was reversed. Haloperidol affected primary learning irrespective of social/individual nature, with no effect on learning from the secondary source. Thus, we illustrate that dopaminergic mechanisms underpinning learning can be dissociated along a primary-secondary but not a social-individual axis. These results resolve conflict in the literature and support an expanding field showing that, rather than being specialised for particular inputs, neurochemical pathways in the human brain can process both social and non-social cues and arbitrate between the two depending upon which cue is primarily relevant for the task at hand.
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19
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Lacroix A, Dutheil F, Logemann A, Cserjesi R, Peyrin C, Biro B, Gomot M, Mermillod M. Flexibility in autism during unpredictable shifts of socio-emotional stimuli: Investigation of group and sex differences. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2021; 26:1681-1697. [PMID: 34957880 DOI: 10.1177/13623613211062776] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT Flexibility difficulties in autism might be particularly common in complex situations, when shifts (i.e. the switch of attentional resources or strategy according to the situation) are unpredictable, implicit (i.e. not guided by explicit rules) and the stimuli are complex. We analyzed the data of 101 autistic and 145 non-autistic adults, without intellectual deficiency, on two flexibility tasks performed online. The first task involved unpredictable and non-explicit shifts of complex socio-emotional stimuli, whereas the second task involved predictable and explicit shifts of character stimuli. Considering the discrepancies between laboratory results and the real-life flexibility-related challenges faced by autistic individuals, we need to determine which factor could be of particular importance in flexibility difficulties. We point out that the switch cost (i.e. the difference between shift and non-shift condition) was larger for autistic than for non-autistic participants on the complex flexibility task with unpredictable and non-explicit shifts of socio-emotional stimuli, whereas this was not the case when shifts were predictable, explicit and involved less complex stimuli. We also highlight sex differences, suggesting that autistic females have better social skills than autistic males and that they also have a specific cognitive profile, which could contribute to social camouflaging. The findings of this work help us understand which factors could influence flexibility difficulties in autism and are important for designing future studies. They also add to the literature on sex differences in autism which underpin better social skills, executive function, and camouflaging in autistic females.
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Affiliation(s)
- Adeline Lacroix
- University of Grenoble Alpes, France.,University of Savoie Mont Blanc, France
| | | | | | | | - Carole Peyrin
- University of Grenoble Alpes, France.,University of Savoie Mont Blanc, France
| | - Brigi Biro
- Eötvös Loránd University (ELTE), Hungary
| | | | - Martial Mermillod
- University of Grenoble Alpes, France.,University of Savoie Mont Blanc, France
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20
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Rybicki AJ, Galea JM, Schuster BA, Hiles C, Fabian C, Cook JL. Intact predictive motor sequence learning in autism spectrum disorder. Sci Rep 2021; 11:20693. [PMID: 34667226 PMCID: PMC8526822 DOI: 10.1038/s41598-021-00173-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 10/06/2021] [Indexed: 01/14/2023] Open
Abstract
Atypical motor learning has been suggested to underpin the development of motoric challenges (e.g., handwriting difficulties) in autism. Bayesian accounts of autistic cognition propose a mechanistic explanation for differences in the learning process in autism. Specifically, that autistic individuals overweight incoming, at the expense of prior, information and are thus less likely to (a) build stable expectations of upcoming events and (b) react to statistically surprising events. Although Bayesian accounts have been suggested to explain differences in learning across a range of domains, to date, such accounts have not been extended to motor learning. 28 autistic and 35 non-autistic controls (IQ > 70) completed a computerised task in which they learned sequences of actions. On occasional "surprising" trials, an expected action had to be replaced with an unexpected action. Sequence learning was indexed as the reaction time difference between blocks which featured a predictable sequence and those that did not. Surprise-related slowing was indexed as the reaction time difference between surprising and unsurprising trials. No differences in sequence-learning or surprise-related slowing were observed between the groups. Bayesian statistics provided anecdotal to moderate evidence to support the conclusion that sequence learning and surprise-related slowing were comparable between the two groups. We conclude that individuals with autism do not show atypicalities in response to surprising events in the context of motor sequence-learning. These data demand careful consideration of the way in which Bayesian accounts of autism can (and cannot) be extended to the domain of motor learning.
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Affiliation(s)
- A. J. Rybicki
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, B15 2TT UK
| | - J. M. Galea
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, B15 2TT UK
| | - B. A. Schuster
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, B15 2TT UK
| | - C. Hiles
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, B15 2TT UK
| | - C. Fabian
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, B15 2TT UK
| | - J. L. Cook
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, B15 2TT UK
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21
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Arthur T, Harris D, Buckingham G, Brosnan M, Wilson M, Williams G, Vine S. An examination of active inference in autistic adults using immersive virtual reality. Sci Rep 2021; 11:20377. [PMID: 34645899 PMCID: PMC8514518 DOI: 10.1038/s41598-021-99864-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/27/2021] [Indexed: 11/25/2022] Open
Abstract
The integration of prior expectations, sensory information, and environmental volatility is proposed to be atypical in Autism Spectrum Disorder, yet few studies have tested these predictive processes in active movement tasks. To address this gap in the research, we used an immersive virtual-reality racquetball paradigm to explore how visual sampling behaviours and movement kinematics are adjusted in relation to unexpected, uncertain, and volatile changes in environmental statistics. We found that prior expectations concerning ball 'bounciness' affected sensorimotor control in both autistic and neurotypical participants, with all individuals using prediction-driven gaze strategies to track the virtual ball. However, autistic participants showed substantial differences in visuomotor behaviour when environmental conditions were more volatile. Specifically, uncertainty-related performance difficulties in these conditions were accompanied by atypical movement kinematics and visual sampling responses. Results support proposals that autistic people overestimate the volatility of sensory environments, and suggest that context-sensitive differences in active inference could explain a range of movement-related difficulties in autism.
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Affiliation(s)
- Tom Arthur
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, Devon, UK.
- Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, BA2 7AY, UK.
| | - David Harris
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, Devon, UK
| | - Gavin Buckingham
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, Devon, UK
| | - Mark Brosnan
- Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, BA2 7AY, UK
| | - Mark Wilson
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, Devon, UK
| | - Genevieve Williams
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, Devon, UK
| | - Sam Vine
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, Devon, UK.
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22
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Sapey-Triomphe LA, Temmerman J, Puts NAJ, Wagemans J. Prediction learning in adults with autism and its molecular correlates. Mol Autism 2021; 12:64. [PMID: 34615532 PMCID: PMC8493731 DOI: 10.1186/s13229-021-00470-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/23/2021] [Indexed: 12/28/2022] Open
Abstract
Background According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. Methods Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA + and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). Results Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA + ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. Limitations We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. Conclusions Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA + in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-021-00470-6.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium. .,Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium.
| | - Joke Temmerman
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences and the Institute of Psychiatry, Psychology, and Neuroscience, Sackler Institute for Translational Neurodevelopment, King's College London, London, SE5 8AF, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE5 8AF, UK
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium
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23
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Sapey-Triomphe LA, Weilnhammer VA, Wagemans J. Associative learning under uncertainty in adults with autism: Intact learning of the cue-outcome contingency, but slower updating of priors. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2021; 26:1216-1228. [PMID: 34533061 DOI: 10.1177/13623613211045026] [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] [Indexed: 11/17/2022]
Abstract
LAY ABSTRACT We have an internal representation of the world that guides our behavior, helps us predicting what comes next and therefore, reducing uncertainty. For instance, after hearing the noise of a door opening, we usually expect to see a person appearing, whose features differ depending on the context. In this example of associative learning, predictions need to be adjusted if there is a change in the environment (e.g. different person depending on the location). Recent theories suggest that the symptoms encountered in autism could be due to an atypical learning of predictions or to a decreased influence of these expectations on perception. Here, we conducted an experiment assessing whether adults with autism could learn and adjust their predictions in a changing environment. Throughout a behavioral task, participants learned to associate a sound with a visual outcome, but this association could sometimes reverse. Results showed that autistic adults could learn to make predictions that fitted the main sound-vision association, but were slower to adapt their expectations when there was an unannounced change in the environment. We also observed that both adults with and without autism tended to be biased by their expectations, as they reported seeing what they expected to see rather than what was actually shown. Altogether, our results indicate that autistic adults can learn predictions but are more inflexible to adjust these predictions in a changing environment. These results help refining recent theories of autism (called "predictive coding" theories), which intend to identify the core mechanisms underlying the autistic symptomatology.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Veith A Weilnhammer
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
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24
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Angeletos Chrysaitis N, Jardri R, Denève S, Seriès P. No increased circular inference in adults with high levels of autistic traits or autism. PLoS Comput Biol 2021; 17:e1009006. [PMID: 34559803 PMCID: PMC8494311 DOI: 10.1371/journal.pcbi.1009006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Revised: 10/06/2021] [Accepted: 08/24/2021] [Indexed: 01/02/2023] Open
Abstract
Autism spectrum disorders have been proposed to arise from impairments in the probabilistic integration of prior knowledge with sensory inputs. Circular inference is one such possible impairment, in which excitation-to-inhibition imbalances in the cerebral cortex cause the reverberation and amplification of prior beliefs and sensory information. Recent empirical work has associated circular inference with the clinical dimensions of schizophrenia. Inhibition impairments have also been observed in autism, suggesting that signal reverberation might be present in that condition as well. In this study, we collected data from 21 participants with self-reported diagnoses of autism spectrum disorders and 155 participants with a broad range of autistic traits in an online probabilistic decision-making task (the fisher task). We used previously established Bayesian models to investigate possible associations between autistic traits or autism and circular inference. There was no correlation between prior or likelihood reverberation and autistic traits across the whole sample. Similarly, no differences in any of the circular inference model parameters were found between autistic participants and those with no diagnosis. Furthermore, participants incorporated information from both priors and likelihoods in their decisions, with no relationship between their weights and psychiatric traits, contrary to what common theories for both autism and schizophrenia would suggest. These findings suggest that there is no increased signal reverberation in autism, despite the known presence of excitation-to-inhibition imbalances. They can be used to further contrast and refine the Bayesian theories of schizophrenia and autism, revealing a divergence in the computational mechanisms underlying the two conditions.
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Affiliation(s)
- Nikitas Angeletos Chrysaitis
- Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Renaud Jardri
- École Normale Supérieure, Institut de Sciences Cognitives, LNC (INSERM U960), Paris, France
- Université de Lille, INSERM U1172, Lille Neuroscience & Cognition Research Centre, Plasticity & SubjectivitY (PSY) team, CHU Lille, Lille, France
| | - Sophie Denève
- École Normale Supérieure, Institut de Sciences Cognitives, LNC (INSERM U960), Paris, France
| | - Peggy Seriès
- Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
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25
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Ward EK, Buitelaar JK, Hunnius S. Implicit learning in 3-year-olds with high and low likelihood of autism shows no evidence of precision weighting differences. Dev Sci 2021; 25:e13158. [PMID: 34251731 PMCID: PMC9286672 DOI: 10.1111/desc.13158] [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: 10/08/2020] [Revised: 06/24/2021] [Accepted: 07/01/2021] [Indexed: 11/27/2022]
Abstract
Predictive Processing accounts of autism claim that autistic individuals assign higher precision to their prediction errors than non-autistic individuals, that is, autistic individuals update their predictions more readily when faced with unexpected sensory input. Since setting the level of precision is a fundamental part of perception and learning, we propose that such differences should be detectable in various domains at a very early age, before clinical symptoms have fully emerged. We therefore tested 3-year-old younger siblings of autistic children, with a high likelihood of later receiving an autism diagnosis themselves, and low-likelihood children with an older sibling without autism. We used a novel implicit learning paradigm to examine the effect of sensory noise on the predictions participants built. In order to learn a sequence, our participants had to select which visual information to attend to and disregard low-level prediction errors caused by the sensory noise, which the theory claims is more difficult for autistic individuals. Contrary to the proposed higher precision-weighting of prediction errors in autism, the high-likelihood children did not show signs of updating their predictions more readily when we added sensory noise compared to the low-likelihood children, either in their reaction times or in the recurrence and determinism of their response locations. These results raise challenges for Predictive Processing theories of autism, specifically for the notion that prediction errors are inflexibly highly weighted by individuals with autism.
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Affiliation(s)
- Emma K Ward
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jan K Buitelaar
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Sabine Hunnius
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
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26
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Cannon J, O’Brien AM, Bungert L, Sinha P. Prediction in Autism Spectrum Disorder: A Systematic Review of Empirical Evidence. Autism Res 2021; 14:604-630. [PMID: 33570249 PMCID: PMC8043993 DOI: 10.1002/aur.2482] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/18/2020] [Accepted: 01/21/2021] [Indexed: 12/20/2022]
Abstract
According to a recent influential proposal, several phenotypic features of autism spectrum disorder (ASD) may be accounted for by differences in predictive skills between individuals with ASD and neurotypical individuals. In this systematic review, we describe results from 47 studies that have empirically tested this hypothesis. We assess the results based on two observable aspects of prediction: learning a pairing between an antecedent and a consequence and responding to an antecedent in a predictive manner. Taken together, these studies suggest distinct differences in both predictive learning and predictive response. Studies documenting differences in learning predictive pairings indicate challenges in detecting such relationships especially when predictive features of an antecedent have low salience or consistency, and studies showing differences in habituation and perceptual adaptation suggest low-level predictive processing differences in ASD. These challenges may account for the observed differences in the influence of predictive priors, in spontaneous predictive movement or gaze, and in social prediction. An important goal for future research will be to better define and constrain the broad domain-general hypothesis by testing multiple types of prediction within the same individuals. Additional promising avenues include studying prediction within naturalistic contexts and assessing the effect of prediction-based intervention on supporting functional outcomes for individuals with ASD. LAY SUMMARY: Researchers have suggested that many features of autism spectrum disorder (ASD) may be explained by differences in the prediction skills of people with ASD. We review results from 47 studies. These studies suggest that ASD may be associated with differences in the learning of predictive pairings (e.g., learning cause and effect) and in low-level predictive processing in the brain (e.g., processing repeated sounds). These findings lay the groundwork for research that can improve our understanding of ASD and inform interventions. Autism Res 2021, 14: 604-630. © 2021 International Society for Autism Research and Wiley Periodicals LLC.
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Affiliation(s)
- Jonathan Cannon
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
| | - Amanda M. O’Brien
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
- Program in Speech and Hearing Bioscience and Technology, Harvard University
| | - Lindsay Bungert
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
| | - Pawan Sinha
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
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27
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Husain L, Berggren N, Remington A, Forster S. Intact Goal-Driven Attentional Capture in Autistic Adults. J Cogn 2021; 4:23. [PMID: 33817551 PMCID: PMC7996432 DOI: 10.5334/joc.156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/08/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Autistic individuals have been found to show increased distractibility by salient irrelevant information, yet reduced distractibility by information of personal motivational salience. Here we tested whether these prior discrepancies reflect differences in the automatic guidance of attention by top-down goals. METHODS Autistic (self-reported diagnoses, confirmed with scores on the Social Responsiveness Scale) and non-autistic adults, without intellectual disability (IQ > 80 on Wechsler Abbreviated Scale of Intelligence), searched for a color-defined target object (e.g., red) among irrelevant color objects. Spatially uninformative cues, matching either the target color or a nontarget/irrelevant color, were presented prior to each display. RESULTS Replicating previous work, only target color cues reliably captured attention, delaying responses when invalidly versus validly predicting target location. Crucially, this capture was robust for both autistic and neurotypical participants, as confirmed by Bayesian analysis. Limitations: While well powered for our research questions, our sample size precluded investigation of the automatic guidance of attention in a diverse group of autistic people (e.g. those with a range of cognitive abilities). CONCLUSIONS Our findings imply that key mechanisms underlying the automatic implementation of top-down attentional goals are intact in autism, challenging theories of reduced top-down control.
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Affiliation(s)
- Layal Husain
- Centre for Research in Autism and Education, Department of Psychology and Human Development, UCL Institute of Education, University College London, UK
| | - Nick Berggren
- Department of Psychological Sciences, Birkbeck College, University of London, UK
| | - Anna Remington
- Centre for Research in Autism and Education, Department of Psychology and Human Development, UCL Institute of Education, University College London, UK
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28
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Achermann S, Falck-Ytter T, Bölte S, Nyström P. Updating Expectations About Unexpected Object Motion in Infants Later Diagnosed with Autism Spectrum Disorder. J Autism Dev Disord 2021; 51:4186-4198. [PMID: 33517525 PMCID: PMC8510946 DOI: 10.1007/s10803-021-04876-2] [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] [Accepted: 01/05/2021] [Indexed: 11/30/2022]
Abstract
In typical development, infants form predictions about future events based on incoming sensory information, which is essential for perception and goal-directed action. It has been suggested that individuals with autism spectrum disorder (ASD) make predictions differently compared to neurotypical individuals. We investigated how infants who later received an ASD diagnosis and neurotypical infants react to temporarily occluded moving objects that violate initial expectations about object motion. Our results indicate that infants regardless of clinical outcome react similarly to unexpected object motion patterns, both in terms of gaze shift latencies and pupillary responses. These findings indicate that the ability to update representations about such regularities in light of new information may not differ between typically developing infants and those with later ASD.
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Affiliation(s)
- Sheila Achermann
- Development and Neurodiversity Lab, Department of Psychology, Uppsala University, Box 1225, 75142, Uppsala, Sweden.
| | - Terje Falck-Ytter
- Development and Neurodiversity Lab, Department of Psychology, Uppsala University, Box 1225, 75142, Uppsala, Sweden.,Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.,Swedish Collegium for Advanced Study (SCAS), Uppsala, Sweden
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, WA, USA
| | - Pär Nyström
- Development and Neurodiversity Lab, Department of Psychology, Uppsala University, Box 1225, 75142, Uppsala, Sweden
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29
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Allenmark F, Shi Z, Pistorius RL, Theisinger LA, Koutsouleris N, Falkai P, Müller HJ, Falter-Wagner CM. Acquisition and Use of 'Priors' in Autism: Typical in Deciding Where to Look, Atypical in Deciding What Is There. J Autism Dev Disord 2020; 51:3744-3758. [PMID: 33373014 PMCID: PMC8460564 DOI: 10.1007/s10803-020-04828-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2020] [Indexed: 11/27/2022]
Abstract
Individuals with Autism Spectrum Disorder (ASD) are thought to under-rely on prior knowledge in perceptual decision-making. This study examined whether this applies to decisions of attention allocation, of relevance for ‘predictive-coding’ accounts of ASD. In a visual search task, a salient but task-irrelevant distractor appeared with higher probability in one display half. Individuals with ASD learned to avoid ‘attentional capture’ by distractors in the probable region as effectively as control participants—indicating typical priors for deploying attention. However, capture by a ‘surprising’ distractor at an unlikely location led to greatly slowed identification of a subsequent target at that location—indicating that individuals with ASD attempt to control surprise (unexpected attentional capture) by over-regulating parameters in post-selective decision-making.
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Affiliation(s)
- Fredrik Allenmark
- Department of Psychology, Ludwig-Maximilians-Universität München, Leopoldstr. 13, 80802, Munich, Germany.
| | - Zhuanghua Shi
- Department of Psychology, Ludwig-Maximilians-Universität München, Leopoldstr. 13, 80802, Munich, Germany
| | - Rasmus L Pistorius
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Laura A Theisinger
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Hermann J Müller
- Department of Psychology, Ludwig-Maximilians-Universität München, Leopoldstr. 13, 80802, Munich, Germany
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30
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Sapey-Triomphe LA, Timmermans L, Wagemans J. Priors Bias Perceptual Decisions in Autism, But Are Less Flexibly Adjusted to the Context. Autism Res 2020; 14:1134-1146. [PMID: 33283970 DOI: 10.1002/aur.2452] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/23/2020] [Accepted: 11/24/2020] [Indexed: 11/07/2022]
Abstract
According to the predictive coding framework, percepts emerge from combinations of sensory input and prior knowledge, whose relative contributions depend on their reliability. Recent predictive coding theories suggest that Autism Spectrum Disorder (ASD) could be characterized by an atypical weighting of priors. Here, we assessed whether individuals with ASD can flexibly adjust the weight (precision) of the prior to the context. Thirty-one neurotypical adults (NT) and 26 adults with ASD participated in a visual discrimination task designed to elicit a time-order effect (TOE). The TOE reflects the integration of priors with sensory estimates. We used two experimental contexts: a narrow stimulus range (Narrow condition) and a broader range (Broad condition) in order to induce a prior with a higher and lower precision, respectively. Both groups learned a prior that biased their perception, as shown with the TOE. As expected, the NT group had a larger TOE in the Narrow condition than in the Broad condition, revealing a contextual adjustment of the prior precision. In contrast, ASD participants were more inflexible: the extent of the TOE was not modulated by the context. In addition, the accuracy increased when the stimulus range decreased in both group, which may be interpreted as a contextual adjustment of the sensory precision. To conclude, adults with and without ASD implicitly learned a prior mean, but ASD participants failed to flexibly adjust the prior precision to the context. This increased inflexibility in ASD could account for many symptoms, such as their intolerance of uncertainty. LAY SUMMARY: Based on our experience, we have expectations about our environment. Theories suggest that the symptoms encountered in autism could be due to atypical expectations, leading to an impression of an unpredictable world. Using a visual discrimination task, we showed that adults with and without autism were biased by their expectations. Yet, the extent to which expectations biased perception did not depend on the context in autism. This higher inflexibility found in autism may explain symptoms such as resistance to change.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Laboratory of Experimental Psychology, Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Laura Timmermans
- Laboratory of Experimental Psychology, Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Johan Wagemans
- Laboratory of Experimental Psychology, Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
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31
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Tschida JE, Yerys BE. A Systematic Review of the Positive Valence System in Autism Spectrum Disorder. Neuropsychol Rev 2020; 31:58-88. [PMID: 33174110 DOI: 10.1007/s11065-020-09459-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 09/23/2020] [Indexed: 01/04/2023]
Abstract
This review synthesized current literature of behavioral and cognitive studies targeting reward processing in autism spectrum disorder (ASD). The National Institute of Mental Health's Research Domain Criteria (RDoC) Positive Valence System (PVS) domain was used as an overarching framework. The objectives were to determine which component operations of reward processing may be atypical in ASD and consequently postulate a heuristic model of reward processing in ASD that could be evaluated with future research. 34 studies were identified from the Embase, PubMed, PsycINFO, and Web of Science databases and included in the review using guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (also known as PRISMA guidelines). The extant literature suggested potential relationships between social symptoms of ASD and PVS sub-constructs of reward anticipation, probabilistic and reinforcement learning, reward prediction error, reward (probability), delay, and effort as well as between restricted and repetitive behaviors and interests (RRBIs) and PVS-sub constructs of initial response to reward, reward anticipation, reward (probability), delay, and effort. However, these findings are limited by a sparse and mixed literature for some sub-constructs. We put forward a developmentally informed heuristic model that posits how these component reward processes may be implicated in early ASD behaviors as well as later emerging and more intransigent symptoms. Future research is needed to comprehensively evaluate the proposed model.
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Affiliation(s)
- Jessica E Tschida
- Children's Hospital of Philadelphia, Roberts Center for Pediatric Research Building, Center for Autism Research, 2716 South Street, 5th Floor, Philadelphia, PA, 19146, USA.
| | - Benjamin E Yerys
- Children's Hospital of Philadelphia, Roberts Center for Pediatric Research Building, Center for Autism Research, 2716 South Street, 5th Floor, Philadelphia, PA, 19146, USA.,Perelman School of Medicine, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
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32
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Crawley D, Zhang L, Jones EJH, Ahmad J, Oakley B, San José Cáceres A, Charman T, Buitelaar JK, Murphy DGM, Chatham C, den Ouden H, Loth E. Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group. PLoS Biol 2020; 18:e3000908. [PMID: 33108370 PMCID: PMC7591042 DOI: 10.1371/journal.pbio.3000908] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 09/22/2020] [Indexed: 12/28/2022] Open
Abstract
Flexible behavior is critical for everyday decision-making and has been implicated in restricted, repetitive behaviors (RRB) in autism spectrum disorder (ASD). However, how flexible behavior changes developmentally in ASD remains largely unknown. Here, we used a developmental approach and examined flexible behavior on a probabilistic reversal learning task in 572 children, adolescents, and adults (ASD N = 321; typical development [TD] N = 251). Using computational modeling, we quantified latent variables that index mechanisms underlying perseveration and feedback sensitivity. We then assessed these variables in relation to diagnosis, developmental stage, core autism symptomatology, and associated psychiatric symptoms. Autistic individuals showed on average more perseveration and less feedback sensitivity than TD individuals, and, across cases and controls, older age groups showed more feedback sensitivity than younger age groups. Computational modeling revealed that dominant learning mechanisms underpinning flexible behavior differed across developmental stages and reduced flexible behavior in ASD was driven by less optimal learning on average within each age group. In autistic children, perseverative errors were positively related to anxiety symptoms, and in autistic adults, perseveration (indexed by both task errors and model parameter estimates) was positively related to RRB. These findings provide novel insights into reduced flexible behavior in relation to clinical symptoms in ASD.
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Affiliation(s)
- Daisy Crawley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Lei Zhang
- Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Neuropsychopharmacology and Biopsychology Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- F. Hoffmann La Roche, Innovation Center Basel, Basel, Switzerland
| | - Emily J. H. Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom
| | - Jumana Ahmad
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Department of Psychology, Social Work and Counselling, University of Greenwich, London, United Kingdom
| | - Bethany Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Antonia San José Cáceres
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Instituto de Investigación Sanitaria Gregorio Marañón, Departamento de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust (SLaM), London, United Kingdom
| | - Jan K. Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, the Netherlands
| | - Declan G. M. Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust (SLaM), London, United Kingdom
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | | | - Hanneke den Ouden
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
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33
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Schreiter ML, Beste C. Inflexible adjustment of expectations affects cognitive-emotional conflict control in adolescents with autism spectrum disorder. Cortex 2020; 130:231-245. [DOI: 10.1016/j.cortex.2020.06.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 04/28/2020] [Accepted: 06/10/2020] [Indexed: 01/01/2023]
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34
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Bianco V, Finisguerra A, Betti S, D’Argenio G, Urgesi C. Autistic Traits Differently Account for Context-Based Predictions of Physical and Social Events. Brain Sci 2020; 10:E418. [PMID: 32630346 PMCID: PMC7407668 DOI: 10.3390/brainsci10070418] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/12/2020] [Accepted: 06/18/2020] [Indexed: 11/16/2022] Open
Abstract
Autism is associated with difficulties in making predictions based on contextual cues. Here, we investigated whether the distribution of autistic traits in the general population, as measured through the Autistic Quotient (AQ), is associated with alterations of context-based predictions of social and non-social stimuli. Seventy-eight healthy participants performed a social task, requiring the prediction of the unfolding of an action as interpersonal (e.g., to give) or individual (e.g., to eat), and a non-social task, requiring the prediction of the appearance of a moving shape as a short (e.g., square) or a long (e.g., rectangle) figure. Both tasks consisted of (i) a familiarization phase, in which the association between each stimulus type and a contextual cue was manipulated with different probabilities of co-occurrence, and (ii) a testing phase, in which visual information was impoverished by early occlusion of video display, thus forcing participants to rely on previously learned context-based associations. Findings showed that the prediction of both social and non-social stimuli was facilitated when embedded in high-probability contexts. However, only the contextual modulation of non-social predictions was reduced in individuals with lower 'Attention switching' abilities. The results provide evidence for an association between weaker context-based expectations of non-social events and higher autistic traits.
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Affiliation(s)
- Valentina Bianco
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, 33100 Udine, Italy; (V.B.); (S.B.); GIULIA.D' (G.D.)
| | | | - Sonia Betti
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, 33100 Udine, Italy; (V.B.); (S.B.); GIULIA.D' (G.D.)
- Department of General Psychology, University of Padova, 35131 Padova, Italy
| | - Giulia D’Argenio
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, 33100 Udine, Italy; (V.B.); (S.B.); GIULIA.D' (G.D.)
- PhD Program in Neural and Cognitive Sciences, Department of Life Sciences, University of Trieste, 34128 Trieste, Italy
| | - Cosimo Urgesi
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, 33100 Udine, Italy; (V.B.); (S.B.); GIULIA.D' (G.D.)
- Scientific Institute, IRCCS E. Medea, Pasian di Prato, 33037 Udine, Italy;
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35
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Coll MP, Whelan E, Catmur C, Bird G. Autistic traits are associated with atypical precision-weighted integration of top-down and bottom-up neural signals. Cognition 2020; 199:104236. [DOI: 10.1016/j.cognition.2020.104236] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 01/31/2020] [Accepted: 02/10/2020] [Indexed: 12/31/2022]
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36
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Increased variability but intact integration during visual navigation in Autism Spectrum Disorder. Proc Natl Acad Sci U S A 2020; 117:11158-11166. [PMID: 32358192 DOI: 10.1073/pnas.2000216117] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here, we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects' dynamic belief states. Both groups showed a previously documented bias pattern by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a nonuniform speed prior rather than imperfect integration. We tracked participants' beliefs and found no difference in the speed prior, but there was heightened variability in the ASD group. Both end point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced, and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.
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37
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Hare I. Semantic feature dissociation: A new hypothesis concerning autism. PHILOSOPHICAL PSYCHOLOGY 2019. [DOI: 10.1080/09515089.2019.1683728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Ian Hare
- Department of Philosophy, Politics, Language, and Communication Studies, University of East Anglia, Norwich, UK
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38
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Amoruso L, Narzisi A, Pinzino M, Finisguerra A, Billeci L, Calderoni S, Fabbro F, Muratori F, Volzone A, Urgesi C. Contextual priors do not modulate action prediction in children with autism. Proc Biol Sci 2019; 286:20191319. [PMID: 31409253 DOI: 10.1098/rspb.2019.1319] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Bayesian accounts of autism suggest that this disorder may be rooted in an impaired ability to estimate the probability of future events, possibly owing to reduced priors. Here, we tested this hypothesis within the action domain in children with and without autism using a behavioural paradigm comprising a familiarization and a testing phase. During familiarization, children observed videos depicting a child model performing actions in diverse contexts. Crucially, within this phase, we implicitly biased action-context associations in terms of their probability of co-occurrence. During testing, children observed the same videos but drastically shortened (i.e. reduced amount of kinematics information) and were asked to infer action unfolding. Since during the testing phase movement kinematics became ambiguous, we expected children's responses to be biased to contextual priors, thus compensating for perceptual uncertainty. While this probabilistic effect was present in controls, no such modulation was observed in autistic children, overall suggesting an impairment in using contextual priors when predicting other peoples' actions in uncertain environments.
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Affiliation(s)
- Lucia Amoruso
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy.,Basque Center on Cognition, Brain and Language, San Sebastian, Spain
| | | | | | | | - Lucia Billeci
- Institute of Clinical Physiology, National Research Council (CNR), Pisa, Italy
| | - Sara Calderoni
- IRCCS Stella Maris Foundation, Pisa (Calambrone), Italy.,Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Franco Fabbro
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
| | - Filippo Muratori
- IRCCS Stella Maris Foundation, Pisa (Calambrone), Italy.,Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Anna Volzone
- Scientific Institute, IRCCS E. Medea, Pasian di Prato, Udine, Italy
| | - Cosimo Urgesi
- Laboratory of Cognitive Neuroscience, Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy.,Scientific Institute, IRCCS E. Medea, Pasian di Prato, Udine, Italy
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Perrykkad K, Hohwy J. Modelling Me, Modelling You: the Autistic Self. REVIEW JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS 2019. [DOI: 10.1007/s40489-019-00173-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Karvelis P, Seitz AR, Lawrie SM, Seriès P. Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration. eLife 2018; 7:e34115. [PMID: 29757142 PMCID: PMC5966274 DOI: 10.7554/elife.34115] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 05/06/2018] [Indexed: 11/13/2022] Open
Abstract
Recent theories propose that schizophrenia/schizotypy and autistic spectrum disorder are related to impairments in Bayesian inference that is, how the brain integrates sensory information (likelihoods) with prior knowledge. However existing accounts fail to clarify: (i) how proposed theories differ in accounts of ASD vs. schizophrenia and (ii) whether the impairments result from weaker priors or enhanced likelihoods. Here, we directly address these issues by characterizing how 91 healthy participants, scored for autistic and schizotypal traits, implicitly learned and combined priors with sensory information. This was accomplished through a visual statistical learning paradigm designed to quantitatively assess variations in individuals' likelihoods and priors. The acquisition of the priors was found to be intact along both traits spectra. However, autistic traits were associated with more veridical perception and weaker influence of expectations. Bayesian modeling revealed that this was due, not to weaker prior expectations, but to more precise sensory representations.
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Affiliation(s)
- Povilas Karvelis
- IANC, School of InformaticsUniversity of EdinburghEdinburghUnited Kingdom
| | - Aaron R Seitz
- Department of PsychologyUC RiversideRiversideUnited States
| | - Stephen M Lawrie
- Division of PsychiatryUniversity of EdinburghEdinburghUnited Kingdom
- Patrick Wild CentreUniversity of EdinburghEdinburghUnited Kingdom
| | - Peggy Seriès
- IANC, School of InformaticsUniversity of EdinburghEdinburghUnited Kingdom
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41
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Lawson RP, Mathys C, Rees G. Adults with autism overestimate the volatility of the sensory environment. Nat Neurosci 2017; 20:1293-1299. [PMID: 28758996 PMCID: PMC5578436 DOI: 10.1038/nn.4615] [Citation(s) in RCA: 219] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2016] [Accepted: 07/04/2017] [Indexed: 12/21/2022]
Abstract
Insistence on sameness and intolerance of change are among the diagnostic criteria for autism spectrum disorder (ASD), but little research has addressed how people with ASD represent and respond to environmental change. Here, behavioral and pupillometric measurements indicated that adults with ASD are less surprised than neurotypical adults when their expectations are violated, and decreased surprise is predictive of greater symptom severity. A hierarchical Bayesian model of learning suggested that in ASD, a tendency to overlearn about volatility in the face of environmental change drives a corresponding reduction in learning about probabilistically aberrant events, thus putatively rendering these events less surprising. Participant-specific modeled estimates of surprise about environmental conditions were linked to pupil size in the ASD group, thus suggesting heightened noradrenergic responsivity in line with compromised neural gain. This study offers insights into the behavioral, algorithmic and physiological mechanisms underlying responses to environmental volatility in ASD.
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Affiliation(s)
- Rebecca P Lawson
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Christoph Mathys
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy
- Max Planck UCL Centre for Computational Psychiatry and Ageing, University College London, London, UK
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland
| | - Geraint Rees
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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Maule J, Stanworth K, Pellicano E, Franklin A. Ensemble perception of color in autistic adults. Autism Res 2017; 10:839-851. [PMID: 27874263 PMCID: PMC5484362 DOI: 10.1002/aur.1725] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Revised: 10/20/2016] [Accepted: 10/21/2016] [Indexed: 11/12/2022]
Abstract
Dominant accounts of visual processing in autism posit that autistic individuals have an enhanced access to details of scenes [e.g., weak central coherence] which is reflected in a general bias toward local processing. Furthermore, the attenuated priors account of autism predicts that the updating and use of summary representations is reduced in autism. Ensemble perception describes the extraction of global summary statistics of a visual feature from a heterogeneous set (e.g., of faces, sizes, colors), often in the absence of local item representation. The present study investigated ensemble perception in autistic adults using a rapidly presented (500 msec) ensemble of four, eight, or sixteen elements representing four different colors. We predicted that autistic individuals would be less accurate when averaging the ensembles, but more accurate in recognizing individual ensemble colors. The results were consistent with the predictions. Averaging was impaired in autism, but only when ensembles contained four elements. Ensembles of eight or sixteen elements were averaged equally accurately across groups. The autistic group also showed a corresponding advantage in rejecting colors that were not originally seen in the ensemble. The results demonstrate the local processing bias in autism, but also suggest that the global perceptual averaging mechanism may be compromised under some conditions. The theoretical implications of the findings and future avenues for research on summary statistics in autism are discussed. Autism Res 2017, 10: 839-851. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
- John Maule
- Sussex Colour Group, School of Psychology, Pevensey 1, North‐South RoadUniversity of SussexBrightonBN1 9QHUK
| | - Kirstie Stanworth
- Sussex Colour Group, School of Psychology, Pevensey 1, North‐South RoadUniversity of SussexBrightonBN1 9QHUK
| | - Elizabeth Pellicano
- UCL Institute of EducationUniversity College London55‐59 Gordon SquareWC1H 0NULondon
| | - Anna Franklin
- Sussex Colour Group, School of Psychology, Pevensey 1, North‐South RoadUniversity of SussexBrightonBN1 9QHUK
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