Resting state EEG in youth with ASD: age, sex, and relation to phenotype

Abstract

Background Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy. Methods We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations. Results Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD. Conclusions Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

Predicting the Symptom Severity in Autism Spectrum Disorder Based on EEG Metrics

“…The CC, GE, and LE were identified to be negatively related to the ADOS scores, while the CP L was positively correlated with the ADOS scores. In fact, in previous studies, the researchers also found similar relations between the electrophysiological and ASD measurements [30], [55], [59], for example, Jung et al found that the strengths of resting-state functional connectivities in ASD subjects were significantly lower than TD subjects and showed negative correlation with the autism-spectrum quotient score [60]. And in children and adolescents with autism, the degree centrality of functional connectivity of the left inferior frontal gyrus and superior temporal gyrus were also found to be negatively correlated with the ADOS scores [61].…”

“…As the PSD of EEG has been applied for studying the ASD [31], the PSD values were also applied to predict the ADOS scores for all enrolled children in current study. Concretely, based on those artifact-free EEG segments, the PSD value of each electrode was first calculated by using Welch's averaged modified periodogram method within frequency band of [1,30] Hz. Then, the PSD values averaged across electrodes were obtained for each participant, and further adopted as the features to predict the ADOS scores.…”

“…The resting-state design does not require individuals to make a particular response and is remarkably promising for ASD children. In fact, previous studies have greatly reported the dysfunctional resting-state activity in ASD children, which helps deepen our knowledge about their behavioral deficits [29], [30]. For example, Wang et al reported decreased alpha EEG power in the ASD children compared to the TD children [31].…”

A Preliminary Study on Photic Driving in the Electroencephalogram of Children with Autism across a Wide Cognitive and Behavioral Range

“…On the other hand, interestingly, this "U-shaped" profile in a resting condition is in line with our preliminary findings based on repetitive visual stimulation technique, representing a potential biomarker of disrupted oscillatory synchronization in ASD. Indeed, as a recent work highlights [48], the use of visual stimuli could have a particular impact on α power, suggesting that resting conditions with visual input elicit reduced α power compared to resting conditions without such input.…”

“…Typical development is characterized by two major age-dependent changes in neural oscillatory powers, a decrease in slow oscillatory powers (δ, θ, and α) mainly in the caudal region, and an increase in the fast oscillatory powers (β and γ) mainly in the rostral region [48,52]. One three-month longitudinal study [42] in ASD children indicated that EEG characteristics are relatively stable across short time intervals.…”