Identification of Biomarker for Autism Spectrum Disorder Using Eeg: A Review

Abstract

Background: Autism Spectrum Disorder (ASD) is a complex neurological disease characterized by difficulties in social interaction, communication, and restricted and repetitive behaviors. Early and reliable identification of ASD remains difficult despite substantial advancements in our knowledge of the disorder. A promising method for examining cerebral activity and connection patterns in people with ASD is electroencephalography (EEG). The main objective of our work is to investigate the link between particular ASD symptoms and EEG anomalies. To achieve our research goal, a systematic review of many academic publications was done. Result: the research from various articles involving our subjects produced a number of important findings about functional connectivity patterns, abnormalities in sensory processing, brain oscillations, event-related potentials (ERPs), neural responses to social stimuli, predictive modeling, and the potential for early detection. Discussion: The results of the EEG play a significant role in the ASD diagnosis. By describing the developments and challenges in this area, we highlighted the potential of EEG as a non-invasive tool to enhance the early detection and characterisation of ASD. The overall findings imply that EEG may enhance our understanding of the neurological underpinnings of ASD. © 2023 IEEE.