Systematic Review on EEG Analysis to Diagnose and Treat Autism by Evaluating Functional Connectivity and Spectral Power

Abstract

An abnormality in neural connectivity is linked to autism spectrum disorder (ASD). There is no way to test the concept of neural connectivity empirically. According to recent network theory and time series analysis findings, electroencephalography (EEG) can assess neural network architecture, a sign of activity in the brain. This systematic review aims to evaluate functional connectivity and spectral power using EEG signals. EEG records the brain activity of an individual by displaying wavy lines that depict brain cells' communication through electrical impulses. EEG can diagnose various brain disorders, including epilepsy and related seizure illness, brain dysfunction, tumors, and damage. We found 21 studies using two of the most common EEG analysis methods: functional connectivity and spectral power. ASD and non-ASD individuals were found to differ significantly in all selected papers. Due to high heterogeneity in the outcomes, generalizations cannot be drawn, and no single method is currently beneficial as a diagnostic tool. For ASD subtype delineation, the lack of research prevented the evaluation of these techniques as diagnostic tools. These findings confirm the presence of abnormalities in the EEG in ASD, but they are insufficient to diagnose. Our study suggests that EEG is useful in diagnosing ASD by evaluating entropy in the brain. Researchers may be able to develop new diagnostic methods for ASD which focuses on particular stimuli and brainwaves if they conduct more extensive studies with higher numbers and more rigorous study designs.

Keywords: autism spectrum disorder; early diagnoses; multiscale entropy; neuroimaging.

Figure 1

PRISMA flow diagram for further selecting some key journals. The inclusion and exclusion criteria were based on six factors; the year of publication, the country, language, subject, type of materials, and the population included. The studies were included if they were (a) published between 2007 to 2022 in any country worldwide, (b) written in English., (c) involved EEG signals in diagnosing ASD in children and adults with ASD disorder, and (d) peer-reviewed articles. The studies were also considered eligible if they included individuals with ASD diagnosed based on the Diagnostic and Manual of Mental Disorders, Fourth Edition (DSM-IV) and if the diagnosis was based on the individual’s age and intelligence quotient (IQ). Finally, the EEG signal analysis on functional connectivity and lower spectral power.