Neurocomputational Phenotypes in Female and Male Autistic Individuals

TL;DR

This study investigates sex-based differences in neural organization in autistic individuals using EEG power-law exponents, revealing significant variations that may explain behavioral differences between females and males with autism.

Contribution

It introduces the analysis of local power-law exponents in EEG data to differentiate neurocomputational phenotypes in female and male autistic individuals.

Findings

Power-law exponent was higher in male ASD compared to female ASD.

Differences were more pronounced in the left hemisphere.

Neural organization differences may underlie behavioral variances.

Abstract

Autism Spectrum Disorder (ASD) is characterized by an altered phenotype in social interaction and communication. Additionally, autism typically manifests differently in females as opposed to males: a phenomenon that has likely led to long-term problems in diagnostics of autism in females. These sex-based differences in communicative behavior may originate from differences in neurocomputational properties of brain organization. The present study looked to examine the relationship between one neurocomputational measure of brain organization, the local power-law exponent, in autistic vs. neurotypical, as well as male vs. female participants. To investigate the autistic phenotype in neural organization based on biological sex, we collected continuous resting-state EEG data for 19 autistic young adults (10 F), and 23 controls (14 F), using a 64-channel Net Station EEG acquisition system. The data was analyzed to quantify the 1/f power spectrum. Correlations between power-law exponent and behavioral measures were calculated in a between-group (female vs. male; autistic vs. neurotypical) design. On average, the power-law exponent was significantly greater in the male ASD group than in the female ASD group in fronto-central regions. The differences were more pronounced over the left hemisphere, suggesting neural organization differences in regions responsible for language complexity. These differences provide a potential explanation for behavioral variances in female vs. male autistic young adults.