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18-11-2020 | Brief Report

Brief Report: Classification of Autistic Traits According to Brain Activity Recoded by fNIRS Using ε-Complexity Coefficients

Auteurs: Anat Dahan, Yuri A. Dubnov, Alexey Y. Popkov, Itai Gutman, Hila Gvirts Probolovski

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 9/2021

Abstract

Individuals with ASD have been shown to have different pattern of functional connectivity. In this study, brain activity of participants with many and few autistic traits, was recorded using an fNIRS device, as participants preformed an interpersonal synchronization task. This type of task involves synchronization and functional connectivity of different brain regions. A novel method for assessing signal complexity, using ε-complexity coefficients, applied for the first i.e. on fNIRS recording, was used to classify brain recording of participants with many/few autistic traits. Successful classification was achieved implying that this method may be useful for classification of fNIRS recordings and that there is a difference in brain activity between participants with low and high autistic traits as they perform an interpersonal synchronization task.

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Titel: Brief Report: Classification of Autistic Traits According to Brain Activity Recoded by fNIRS Using ε-Complexity Coefficients
Auteurs: Anat Dahan
Yuri A. Dubnov
Alexey Y. Popkov
Itai Gutman
Hila Gvirts Probolovski
Publicatiedatum: 18-11-2020
Uitgeverij: Springer US
Gepubliceerd in: Journal of Autism and Developmental Disorders / Uitgave 9/2021
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI: https://doi.org/10.1007/s10803-020-04793-w

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