22456
Differences in EEG Coherence Between ASD and Typical Development Are State-Dependent

Friday, May 13, 2016: 2:52 PM
Room 307 (Baltimore Convention Center)
A. W. Buckley1, C. Farmer1, R. Scott2, A. Tyler2, J. M. Mahoney2, S. Burroughs2, G. Holmes2, S. E. Swedo1 and A. Thurm1, (1)Pediatrics and Developmental Neuroscience Branch, National Institute of Mental Health, Bethesda, MD, (2)University of Vermont College of Medicine, Burlington, VT
Background:  The role of sleep in the proper maturation of the developing brain is an area of current intense interest, with the contribution of state-specific processes to synaptic refinement just beginning to be understood. There is increasing evidence of altered brain connectivity in autism, however, the vast majority of ASD coherence studies are not performed during sleep, and taken as a whole, show very mixed results.

Objectives:  The aim of the present study was to compare connectivity in children aged 2 to 6 years with ASD (n=87) to that of typically developing controls (TYP; n=29).

Methods: Digital EEGs were recorded during the fully awake, drowsy, and sleep states using the 10–20 System of Electrode placement (Figure 2). Ten minute segments of awake, slow wave sleep, and rapid eye movement sleep were selected for analysis. Analysis was performed masked to participant diagnosis using Neuroguide software. Coherence values were subjected to Fisher-transformation for statistical analysis. Differences in mean coherence and phase lag between groups were assessed using the general linear model, controlling for age.  

Results:  Significantly increased coherence was observed in ASD relative to TYP, concentrated in the frontal-parietal pairs (Figure 1). Significantly decreased phase lag, particularly in long-distance pairs, was also observed in ASD relative to TYP (Figure 2). Strikingly, these differences were found exclusively during sleep, most commonly during slow wave sleep. No differences in coherence or phase lag were observed during the awake state.

Conclusions: Evaluation of brain connectivity during sleep is extremely important, as the sleep EEG reflects the maturation of the brain and allows for examination of dynamic neural networks in the absence of external stimuli. Future attempts to classify developmental disorders by using differences in connectivity must take into account brain state.