Abstract
Autism Spectrum Disorders (ASD) are an etiologically and clinically heterogeneous group of neurodevelopmental disorders. The pathophysiology of ASD remains largely unknown. One essential and well-documented observation is high comorbidity between ASD and epilepsy. Electroencephalography (EEG) is the most widely used tool to detect epileptic brain activity. The EEG signal is characterized by a high temporal resolution (on the order of milliseconds) allowing for precise temporal examination of cortical activity. This review addresses the main EEG findings derived from both the standard or qualitative (visually inspected) EEG and the quantitative (computer analyzed) EEG during resting state in individuals with ASD. The bulk of the evidence supports significant connectivity disturbances in ASD that are possibly widespread with two specific aspects: over-connectivity in the local networks and under-connectivity in the long-distance networks. Furthermore, the review suggested that disruptions appear more severe in later developing parts of the brain (e.g., prefrontal cortex). Based on available information, from both the qualitative and quantitative EEG literature, we postulate a preliminary hypothesis that increased cortical excitability may contribute to the significant overlap between ASD and epilepsy and may be contributing to the connectivity deviations noted. As the presence of a focal epileptic discharge is a clear indication of such hyperexcitability, we conclude that the presence of epileptic discharges is a potential biomarker at least for a subgroup of ASD.
Highlights
Clinical manifestations and heterogeneity Autistic spectrum disorder (ASD) patients encompass a heterogeneous group of individuals with early childhood onset of deficits in social interaction and language development, a restricted repertoire of interests and activities, as well as a wide range of cognitive skills ranging from severe deficits to high functioning individuals
Conclusions from computer-analyzed reading of the EEG (C-EEG) In 2011, Wass reviewed the available literature and concluded that the bulk of the evidence supported significant connectivity disturbances in ASD that are possibly widespread with two specific aspects: over-connectivity in the local networks and under-connectivity in the long-distance networks (Wass 2011)
They addressed the relevance of this approach in clustering phenotypes and concluded that the use of advanced techniques for increased specificity and improved spatial localization could enable the discovery of distinctive patterns of C-EEG abnormalities in ASD subjects
Summary
Clinical manifestations and heterogeneity Autistic spectrum disorder (ASD) patients encompass a heterogeneous group of individuals with early childhood onset of deficits in social interaction and language development, a restricted repertoire of interests and activities, as well as a wide range of cognitive skills ranging from severe deficits to high functioning individuals. EEG can be used to examine brain activity either during rest, or during evoked brain responses using specific tasks known to elicit these evoked responses as well as by examining the effects of specific tasks (e.g., face recognition) on the ongoing EEG signal. These two techniques (i.e., taskrelated EEG changes and evoked potentials) of examining the EEG signal in ASD have voluminous bodies of literature associated with them. We summarize the published findings based on both standard EEG and C-EEG methodologies and present an overall view of what the data have revealed far about ASD as well as possible future research directions using these methodologies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
