Resting-state alpha power is selectively associated with autistic traits reflecting behavioral rigidity

Abstract Previous research suggests that variation in at-rest neural activity correlates with specific domains of the ASD phenotype; however, few studies have linked patterns of brain activity with autistic trait expression in typically developing populations. The purpose of this study was to examine associations between resting-state electroencephalography (EEG) and three domains of the broader autism phenotype (social interest, rigidity, and pragmatic language) in typically developing individuals. High-density scalp EEG was recorded in thirty-seven typically developing adult participants (13 male, aged 18–52 years). The Broad Autism Phenotype Questionnaire (BAP-Q) was used to measure autistic trait expression. Absolute alpha power (8–13 Hz) was extracted from eyes-closed epochs using spectral decomposition techniques. Analyses revealed a specific positive association between scores on the BAP-Q Rigidity subscale and alpha power in the parietal scalp region. No significant associations were found between alpha power and the BAP-Q Aloofness or Pragmatic Language subscales. Furthermore, the association between EEG power and behavioral rigidity was specific to the alpha frequency band. This study demonstrates that specific traits within the broader autism phenotype are associated with dissociable patterns of at-rest neural activity. Introduction Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by persistent impairments in social communication, restrictive, repetitive behaviors, and atypical response to sensory information1. Given its early developmental course2 and high heritability both for diagnostic status and continuous phenotypes3,4, ASD is posited to be neurobiological in origin; however, the exact etiologies of ASD remain unclear. While ASD is recognized as a single clinical entity, tremendous heterogeneity exists across individuals receiving the diagnosis, and previous research suggests that the different symptom domains of ASD may represent dissociable (or at least partially-dissociable) disorder states altogether5. Examining symptom domains independently may reveal specific patterns of neural activity associated with the different clinical dimensions of the ASD phenotype, and illuminate underpinning neurobiological mechanisms. Scalp electroencephalography (EEG) is frequently used to compare patterns of brain activity between individuals with ASD and typically developing counterparts. Although much research has focused on electrical responses to specific neurocognitive tasks (i.e., ‘task-dependent’ or ‘event-related’ activity), researchers have increasingly attributed significance to brain activity recorded in the absence of task demands (i.e., ‘task-free’ or ‘resting-state’ EEG)6. Among the most consistent findings observed across resting-state studies in ASD are alterations in power in the alpha frequency range (8–13 Hz). Widespread increases in resting-state alpha power have been described in both children7,8 and adults with ASD9 compared to typically developing individuals, although other studies have reported contradictory findings10,11,12. Relatively few studies have explored how resting-state alpha power correlates with specific domains of the ASD phenotype. One study found that children with ASD who displayed greater right frontal alpha asymmetry (i.e., increased alpha power in the right hemisphere compared to the left hemisphere) had higher levels of social impairment and better visual analytic skills than those with left frontal asymmetry13. Dawson and colleagues11 found that children classified as socially ‘passive’ exhibited reduced frontal alpha power compared to those who were ‘active-but-odd.’ Another study identified a link between specific ASD symptoms (e.g., extreme attention to detail) and variations in alpha power in the parietal lobe9. Thus, existing literature suggests that oscillatory activity within the alpha frequency range may be independently associated with specific domains of the ASD phenotype. Some researchers argue that ASD represents the upper extreme of a continuous spectrum of traits observed throughout the general population14. Accordingly, comparable patterns of neural activity have been described in individuals with ASD and typically developing individuals with high levels of autistic traits, suggesting that neural alterations associated with ASD may also be present in the subclinical population15,16. To date, however, few studies have explored how resting-state EEG activity relates to autistic trait expression in typically developing populations. One EEG study identified an inverse relationship between autistic trait expression, as measured by the Social Responsiveness Scale (SRS17), and functional connectivity strength, particularly in the lower frequency (<10 Hz) range17. A more recent study found that higher levels of autistic traits were associated with increased relative alpha power18, and this effect appeared to be driv (...truncated)