Schedule of Events | Symposia

Divergent aging trajectories of aperiodic neural activity between neurotypical adults and those with autism spectrum disorder

Poster Session A - Saturday, March 29, 2025, 3:00 – 5:00 pm EDT, Back Bay Ballroom/Republic Ballroom

Christian Cazares¹ (cazares@ucsd.edu), Anet Estrada¹, Bradley Voytek¹; ¹University of California, San Diego

Previous studies have identified several candidate electrophysiological biomarkers for cognitive aging in adults, with one emerging biomarker being aperiodic (1/f-like) neural activity measures. However, how these age-related changes in aperiodic neural activity differentially manifest in autism spectrum disorder (ASD) remains unknown. Here, we analyzed an open, resting-state EEG dataset from 56 participants (ASD and age-matched neurotypical controls, aged 20-70 years, sourced from Dickinson et al., 2022) using mixed-effects models to characterize non-linear age relationships while controlling for aperiodic-adjusted oscillatory power (theta, alpha, beta), social responsiveness scale scores, and sex. All regions showed negative associations between aperiodic neural activity measures and aging (p<0.001), replicating prior work showing that older adults tend to have “flatter” spectra than younger adults. For the aperiodic exponent, we found group differences in how aging was associated with activity in central (β=0.786, p<0.001) and temporal regions (β=0.821, p=0.015), where people with ASD had lower exponents with increasing age. We found similar age-related group differences in aperiodic offset across central (β=1.019, p=0.011), temporal (β=1.053, p=0.036), and occipital regions (β=1.146, p=0.037). Our findings suggest fundamentally different aging trajectories in aperiodic neural activity between ASD and healthy individuals. Specifically, while neurotypical controls showed negatively-tilted, U-shaped trajectories across age, individuals with ASD showed continuous decline in both aperiodic neural activity measures. Given higher rates of cognitive and neurodegenerative conditions in aging adults with ASD, these findings support the inclusion of resting-state aperiodic features as candidate biomarkers for tracking aging trajectories in ASD, potentially informing targeted interventions for this highly heterogeneous population.

Topic Area: EXECUTIVE PROCESSES: Development &aging