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.

Keywords: Alpha; Autism; Biomarker; EEG; Electroencephalography; Power; Resting; Sex differences.

Fig. 1

EEG montage with channels indicated. Channel numbers for regions are (1) frontal left (23, F3-24, 27, 28), (2) frontal midline (5, FZ-11, 12, 16), (3) frontal right (3, 117, 123, F4-124), (4) central left (35, C3-36, 41, 42), (5) central midline (7, 31, 80, 106), (6) central right (93, 103, C4-104, 110), (7) posterior left (51, P3-52, 59, 60), (8) posterior midline (Pz-62, 71, 72, 76), and (9) posterior right (85, 91, P4-92, 97)

Fig. 2

Topographical plots of absolute power (natural log-transformed) by frequency band and group. Colors depicted represent power (μV²) within frequency bands across regions. Blue areas correspond to lower power for a respective frequency band and red areas correspond to higher power