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

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  • Additional Information
    • Availability:
      Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: [email protected]; Web site: https://link.springer.com/
    • Peer Reviewed:
      Y
    • Source:
      11
    • Subject Terms:
      Classification; Symptoms (Individual Disorders); Autism; Pervasive Developmental Disorders; Brain; Cognitive Processes; Spectroscopy; Brain Hemisphere Functions; Task Analysis; Interaction Process Analysis
    • Accession Number:
      10.1007/s10803-020-04793-w
    • ISSN:
      0162-3257
    • 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 e-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.
    • Abstract:
      As Provided
    • Publication Date:
      2021
    • Accession Number:
      EJ1306502