Developmental trajectories of resting EEG power: an endophenotype of autism spectrum disorder
Tierney, Adrienne L.
Nelson, Charles A.
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Citation (published version)Adrienne L Tierney, Laurel Gabard-Durnam, Vanessa Vogel-Farley, Helen Tager-Flusberg, Charles A Nelson. 2012. "Developmental Trajectories of Resting EEG Power: An Endophenotype of Autism Spectrum Disorder." PLOS ONE, Volume 7, Issue 6, 10 pp. https://doi.org/10.1371/journal.pone.0039127
Current research suggests that autism spectrum disorder (ASD) is characterized by asynchronous neural oscillations. However, it is unclear whether changes in neural oscillations represent an index of the disorder or are shared more broadly among both affected and unaffected family members. Additionally, it remains unclear how early these differences emerge in development and whether they remain constant or change over time. In this study we examined developmental trajectories in spectral power in infants at high- or low-risk for ASD. Spectral power was extracted from resting EEG recorded over frontal regions of the scalp when infants were 6, 9, 12, 18 and 24 months of age. We used multilevel modeling to assess change over time between risk groups in the delta, theta, low alpha, high alpha, beta, and gamma frequency bands. The results indicated that across all bands, spectral power was lower in high-risk infants as compared to low-risk infants at 6-months of age. Furthermore high-risk infants showed different trajectories of change in spectral power in the subsequent developmental window indicating that not only are the patterns of change different, but that group differences are dynamic within the first two years of life. These findings remained the same after removing data from a subset of participants who displayed ASD related behaviors at 24 or 36 months. These differences in the nature of the trajectories of EEG power represent important endophenotypes of ASD.
RightsCopyright © 2012 Tierney et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.