Abstract

Abstract Introduction There is compelling evidence that sleep spindles, electroencephalogram (EEG) signatures of non-rapid eye movement sleep, are reliable markers of thalamocortical dysfunction in Schizophrenia. While promising, this research is limited by traditional sleep EEG methods, which cultivate small, non-representative samples. Wearable EEG headbands could be used to study naturalistic sleep across several nights in individuals who cannot tolerate standard sleep assessments, but this has yet to be tested. We aim to test feasibility of using a dry-EEG headband to measure sleep spindles in adolescents with a neurodevelopmental disorder, 22q11.2 Deletion Syndrome (22q11DS). Methods Adolescents with 22q11DS (n=7; 3 Females; Age: 15-28 years) were asked to sleep in their own bed wearing a dry-EEG headband (Dreem 3). Feasibility of data acquisition was determined by the ability of the participants to record at least 3 consecutive nights. We performed visual artifact detection and examined the ability to detect sleep spindles using the well-validated Ferrarelli Spindle Detection Algorithm on the F7-O2 electrode. Results All subjects completed at least 3 nights of recording (range: 3-5 nights), suggesting the device was well-tolerated. The data contained minimal artifact; 17 out of the 22 nights available for analysis contained artifact in < 20% of sleep epochs. The best night contained artifact in only 6% of sleep epochs. Sleep spindles were successfully detected using an automatic detector (M= 1.92 spindles/minute). Conclusion This pilot study suggests dry-EEG headbands offer a feasible method to measure sleep spindles in individuals with neurodevelopmental disorders. This new technology could allow for scalable biomarkers of atypical neurodevelopment associated with psychiatric disorders. Support (if any) RO1 MH085953; U01MH10171; UCLA Center for Autism Research Pilot Grant; Dreem Coup de Coeur Award

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