Dysregulation of temporal dynamics of synchronous neural activity in adolescents on autism spectrum.

Abstract

Autism spectrum disorder is increasingly understood to be based on atypical signal transfer among multiple interconnected networks in the brain. Relative temporal patterns of neural activity have been shown to underlie both the altered neurophysiology and the altered behaviors in a variety of neurogenic disorders. We assessed brain network dynamics variability in autism spectrum disorders (ASD) using measures of synchronization (phase-locking) strength, and timing of synchronization and desynchronization of neural activity (desynchronization ratio) across frequency bands of resting-state electroencephalography (EEG). Our analysis indicated that frontoparietal synchronization is higher in ASD but with more short periods of desynchronization. It also indicates that the relationship between the properties of neural synchronization and behavior is different in ASD and typically developing populations. Recent theoretical studies suggest that neural networks with a high desynchronization ratio have increased sensitivity to inputs. Our results point to the potential significance of this phenomenon to the autistic brain. This sensitivity may disrupt the production of an appropriate neural and behavioral responses to external stimuli. Cognitive processes dependent on the integration of activity from multiple networks maybe, as a result, particularly vulnerable to disruption. Autism Res 2020, 13: 24-31. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Parts of the brain can work together by synchronizing the activity of the neurons. We recorded the electrical activity of the brain in adolescents with autism spectrum disorder and then compared the recording to that of their peers without the diagnosis. We found that in participants with autism, there were a lot of very short time periods of non-synchronized activity between frontal and parietal parts of the brain. Mathematical models show that the brain system with this kind of activity is very sensitive to external events.