Temporal Predictions in Music and Language: The Case of Autism Spectrum Disorder

Auteurs

Denis M, Mazzocconi C, Da Fonseca D, Schön D

Les auteurs en lien sont membres de l'INS.

Équipes

D-CAP

Résumé

ABSTRACT The predictive coding theory of autism suggests that individuals with autism may show atypicalities in how predictions are formed or updated. This may in turn affect how they process temporal information. While predictive coding has been widely applied to the study of language, including conversation, and music, including musical interactions, relatively few studies have explored the intersection of these domains in autism. Even fewer have focused on the role of temporal predictions in both language and music. This review examines studies that investigate temporal processing and predictive mechanisms in both music and language in individuals with autism spectrum disorder (ASD). Understanding these shared temporal mechanisms is crucial for providing a more comprehensive view of the underlying cognitive processes and difficulties in ASD. Furthermore, exploring the relationship between music and language from a temporal prediction perspective offers valuable insights into more ecologically valid and interactive settings, such as conversation and music‐making. Such research not only improves our understanding of autism but also has important implications for therapeutic interv

ABSTRACT The predictive coding theory of autism suggests that individuals with autism may show atypicalities in how predictions are formed or updated. This may in turn affect how they process temporal information. While predictive coding has been widely applied to the study of language, including conversation, and music, including musical interactions, relatively few studies have explored the intersection of these domains in autism. Even fewer have focused on the role of temporal predictions in both language and music. This review examines studies that investigate temporal processing and predictive mechanisms in both music and language in individuals with autism spectrum disorder (ASD). Understanding these shared temporal mechanisms is crucial for providing a more comprehensive view of the underlying cognitive processes and difficulties in ASD. Furthermore, exploring the relationship between music and language from a temporal prediction perspective offers valuable insights into more ecologically valid and interactive settings, such as conversation and music‐making. Such research not only improves our understanding of autism but also has important implications for therapeutic interv

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