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

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

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)3380-3390
Number of pages11
JournalJournal of Autism and Developmental Disorders
Volume51
Issue number9
DOIs
StatePublished - Sep 2021

Keywords

  • Autistic traits
  • Classification
  • Complexity
  • fNIRS
  • Interpersonal synchronization

All Science Journal Classification (ASJC) codes

  • Developmental and Educational Psychology

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