EEG Microstates Analysis in Young Adults With Autism Spectrum Disorder During Resting-State - D’Croz-Baron, David F.; Baker, Mary; Michel, Christoph M.; Karp, Tanja (Frontiers in Human Neuroscience, 2019)
Electroencephalography (EEG) is a useful tool to inspect the brain activity in resting-state and allows to characterize spontaneous brain activity that is not detected when a subject is cognitively engaged. Moreover, taking advantage of the high time resolution in EEG, it is possible to perform fast topographical reference-free analysis, since different scalp potential fields correspond to changes in the underlying sources within the brain. In this study, the spontaneous EEG resting-state (eyes closed) was compared between ten young adults ages 18-30 years with Autism Spectrum Disorder (ASD) and thirteen neurotypical controls. A microstate analysis was applied, focusing on four temporal parameters: mean duration, the frequency of occurrence, the ratio of time coverage, and the Global Explained Variance (GEV). Using data that were acquired from a 65 channel EEG system, six resting-state topographies that best describe the dataset across all subjects were identified by running a two-step cluster analysis, labeled as microstate classes A-F. The results indicated that microstates B and E displayed a statistically significant differences between both groups among the temporal parameters evaluated. Classes B, D, E, and F were consistently more present in ASD, and class C in controls. The combination of these findings with the putative functional significance of the different classes suggests that during resting-state, the ASD group was more focused on visual scene-reconstruction, while the control group was more engaged with self-memory retrieval. Furthermore, from a connectivity perspective, the resting-state networks that have been previously associated with each microstate class overlap the brain regions implicated in impaired social communication and repetitive behaviors that characterize ASD.