Autistic traits are related to worse performance in a volatile reward learning task despite adaptive learning rates / Judith GORIS in Autism, 25-2 (February 2021)  

Public ISBD [article]  inAutism > 25-2 (February 2021) . - p.440-451 Titre : Autistic traits are related to worse performance in a volatile reward learning task despite adaptive learning rates Type de document : texte imprimé Auteurs : Judith GORIS, Auteur ; Massimo SILVETTI, Auteur ; Tom VERGUTS, Auteur ; Jan R. WIERSEMA, Auteur ; Marcel BRASS, Auteur ; Senne BRAEM, Auteur Article en page(s) : p.440-451 Langues : Anglais (eng) Mots-clés : autism spectrum disorders  learning rate  reward decision-making Index. décimale : PER Périodiques Résumé : Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. Here, we investigated this hypothesis by estimating learning rates (i.e. the speed with which one learns) in three different environments that differed in rule stability and uncertainty. We found that neurotypical participants with more autistic traits performed worse in a volatile environment (with unstable rules), as they chose less often for the most rewarding option. Exploratory analyses indicated that performance was specifically worse when reward rules were opposite to those initially learned for participants with more autistic traits. However, there were no differences in the adjustment of learning rates between participants with more versus less autistic traits. Together, these results suggest that performance in volatile environments is lower in participants with more autistic traits, but that this performance difference cannot be unambiguously explained by an impairment in adjusting learning rates. En ligne : http://dx.doi.org/10.1177/1362361320962237 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=442 [article] Autistic traits are related to worse performance in a volatile reward learning task despite adaptive learning rates [texte imprimé] / Judith GORIS, Auteur ; Massimo SILVETTI, Auteur ; Tom VERGUTS, Auteur ; Jan R. WIERSEMA, Auteur ; Marcel BRASS, Auteur ; Senne BRAEM, Auteur . - p.440-451. Langues : Anglais (eng) in Autism > 25-2 (February 2021) . - p.440-451 Mots-clés : autism spectrum disorders  learning rate  reward decision-making Index. décimale : PER Périodiques Résumé : Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. Here, we investigated this hypothesis by estimating learning rates (i.e. the speed with which one learns) in three different environments that differed in rule stability and uncertainty. We found that neurotypical participants with more autistic traits performed worse in a volatile environment (with unstable rules), as they chose less often for the most rewarding option. Exploratory analyses indicated that performance was specifically worse when reward rules were opposite to those initially learned for participants with more autistic traits. However, there were no differences in the adjustment of learning rates between participants with more versus less autistic traits. Together, these results suggest that performance in volatile environments is lower in participants with more autistic traits, but that this performance difference cannot be unambiguously explained by an impairment in adjusting learning rates. En ligne : http://dx.doi.org/10.1177/1362361320962237 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=442

Different exploration strategies along the autism spectrum: diverging effects of autism diagnosis and autism traits / Fien GOETMAECKERS in Molecular Autism, 16 (2025)  

Public ISBD [article]  inMolecular Autism > 16 (2025) . - 47 Titre : Different exploration strategies along the autism spectrum: diverging effects of autism diagnosis and autism traits Type de document : texte imprimé Auteurs : Fien GOETMAECKERS, Auteur ; Judith GORIS, Auteur ; Jan R. WIERSEMA, Auteur ; Tom VERGUTS, Auteur ; Senne BRAEM, Auteur ; Fien Secondary GOETMAECKERS, Auteur ; Judith GORIS, Auteur ; Jan R. WIERSEMA, Auteur ; Tom VERGUTS, Auteur ; Senne BRAEM, Auteur Article en page(s) : 47 Langues : Anglais (eng) Mots-clés : Autism  Computational cognitive modeling  Exploration  Uncertainty  Value-based decision-making  by the Ethics Committee of the Faculty of Psychological and Pedagogical Sciences  of Ghent University and all participants gave their informed consent. Consent for  publication: Not applicable. Competing interests: The authors declare no  competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: When faced with many options to choose from, humans typically need to explore the utility of new choice options. People with an autism diagnosis or elevated autism traits are thought to avoid exploring such unknown options, but it remains unclear how autism affects exploration in decision spaces with many options. METHODS: In a large online sample (N = 588), we investigated the impact of autism diagnosis or elevated autism traits on exploration behavior during value-based decision-making in vast decision spaces. We used a 121-armed bandit with spatially correlated choice options, and a dedicated computational model to disentangle generalization, uncertainty-guided exploration, and random exploration strategies. RESULTS: Our findings show that participants with a self-reported autism diagnosis were less likely to explore novel choice options and more likely to exploit known high-value options. Computational modeling suggests they engaged in less uncertainty-driven exploration but exhibited equal random exploration and generalization strategies. Interestingly, among non-diagnosed participants, people with elevated autism traits did not explore less. LIMITATIONS: This study relies on self-reported autism diagnoses and trait measures collected online. This may limit the generalizability of the findings to clinically verified or more diverse autism populations. CONCLUSIONS: Our findings highlight important differences in exploration strategies between clinical and subclinical populations and emphasize the importance of cognitive modeling and using vast decision spaces to better understand autism. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13229-025-00679-9. En ligne : https://dx.doi.org/10.1186/s13229-025-00679-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=569 [article] Different exploration strategies along the autism spectrum: diverging effects of autism diagnosis and autism traits [texte imprimé] / Fien GOETMAECKERS, Auteur ; Judith GORIS, Auteur ; Jan R. WIERSEMA, Auteur ; Tom VERGUTS, Auteur ; Senne BRAEM, Auteur ; Fien Secondary GOETMAECKERS, Auteur ; Judith GORIS, Auteur ; Jan R. WIERSEMA, Auteur ; Tom VERGUTS, Auteur ; Senne BRAEM, Auteur . - 47. Langues : Anglais (eng) in Molecular Autism > 16 (2025) . - 47 Mots-clés : Autism  Computational cognitive modeling  Exploration  Uncertainty  Value-based decision-making  by the Ethics Committee of the Faculty of Psychological and Pedagogical Sciences  of Ghent University and all participants gave their informed consent. Consent for  publication: Not applicable. Competing interests: The authors declare no  competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: When faced with many options to choose from, humans typically need to explore the utility of new choice options. People with an autism diagnosis or elevated autism traits are thought to avoid exploring such unknown options, but it remains unclear how autism affects exploration in decision spaces with many options. METHODS: In a large online sample (N = 588), we investigated the impact of autism diagnosis or elevated autism traits on exploration behavior during value-based decision-making in vast decision spaces. We used a 121-armed bandit with spatially correlated choice options, and a dedicated computational model to disentangle generalization, uncertainty-guided exploration, and random exploration strategies. RESULTS: Our findings show that participants with a self-reported autism diagnosis were less likely to explore novel choice options and more likely to exploit known high-value options. Computational modeling suggests they engaged in less uncertainty-driven exploration but exhibited equal random exploration and generalization strategies. Interestingly, among non-diagnosed participants, people with elevated autism traits did not explore less. LIMITATIONS: This study relies on self-reported autism diagnoses and trait measures collected online. This may limit the generalizability of the findings to clinically verified or more diverse autism populations. CONCLUSIONS: Our findings highlight important differences in exploration strategies between clinical and subclinical populations and emphasize the importance of cognitive modeling and using vast decision spaces to better understand autism. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13229-025-00679-9. En ligne : https://dx.doi.org/10.1186/s13229-025-00679-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=569

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