IQ Discrepancy Profiles and EEG Alpha Power In Autism Spectrum Disorders

Background:  Previous reports of the cognitive profile of autism spectrum disorders (ASD), specifically a non-verbal and verbal IQ discrepancy, indicate significant variability in performance. Although one profile may not effectively represent ASD, profile analysis may aid in elucidating sub-types. EEG provides an avenue to explore cognitive profiles in ASD given the consistent, although complex, relationship identified between EEG and intelligence.

Objectives:  To examine EEG alpha power in individuals with ASD and typical development, with and without the presence of a discrepancy between verbal and non-verbal intelligence, with the prospect of exploring the validity of split vs. no-split cognitive profile. 

Methods:  Spontaneous EEGs were collected during resting state condition from a sample of adults with an autism spectrum disorder (ASD, N=14) and typical development (TYP, N=11). Power was calculated in the alpha frequency band (8-12 Hz) across five regions of interest: frontal, central, parietal, temporal, and occipital. Cognitive ability was assessed using the Wechsler Adult Intelligence Scale-3rd Edition (WAIS-III). Participants in both diagnostic groups were separated into split and no-split profile groups based on a discrepancy between performance and verbal IQ greater than 15 points.

Results:  Individuals with a cognitive split, regardless of diagnosis, showed decreased alpha power during rest (p<.05). A significant interaction between diagnosis and cognitive profile was found for electrodes over the parietal lobe (p<.05). While typical participants showed no differences in spectral power based on the presence of a cognitive split, ASD participants with a cognitive split showed reduced spectral power in the alpha range compared to ASD participants without a cognitive split in the parietal region.

Conclusions:  These findings expand upon previous work indicating a relationship between resting state alpha power and intelligence, as well as differential EEG activity in ASD. They suggest that cognitive profiles may help in identifying subtypes of ASD. Further, they suggest that cognitive profiles may play a role in observed differential electrophysiological activity. The use of cognitive profiles and electrophysiology may be useful in parsing out groups within the heterogeneous ASD population.