799 Automated Detection of Slow Wave Coherence in Sleep EEG: A potential neurophysiological correlate of cognitive decline

Abstract

Abstract Introduction A bidirectional relationship exists between sleep disruption and neuropathology in Alzheimer’s disease (AD). The sleep electroencephalogram (EEG) is a highly stereotyped, direct neurophysiological window into brain function; prior studies have identified abnormalities in EEG slow waves in early AD. EEG coherence across channels during sleep, a normally highly coherent brain state, could be an indicator of network coordination across brain regions. Accordingly, altered slow wave coherence during sleep may be an early indicator of cognitive decline. Methods EEG was collected during an attended overnight polysomnogram (PSG) from a community-based cohort of older subjects (n=44, average age = 71), approximately 25% of whom met criteria for mild cognitive impairment or early AD. Files were exported to EDF and a slow wave peak detector was implemented in MATLAB to count the number of slow wave oscillations, with automated artifact rejection, across 6 EEG leads standard for PSG (C3, C4, F3, F4, O1, and O2). Slow wave coherence was inferred when slow waves occurred in temporal synchrony across channels within 100 ms. Results Subjects with cognitive impairment showed significantly reduced total sleep time and time spent in rapid eye movement (REM) sleep compared to age-matched controls. EEG slow wave coherence was reliably quantified during wake, non-REM stages N1, N2, N3, and REM vigilance states as well as during transition periods between sleep stages. Using this algorithm, specific signatures of slow wave propagation during sleep were identified, including increased variability in slow wave activity and coherence, that appeared more prominent in subjects with impaired cognition. Conclusion EEG slow wave coherence during sleep and wake states can be calculated by applying automated algorithms to PSG data, and may be associated with cognitive impairment. Support (if any) NIH R01 AG059507