Sleep characteristics, cognitive performance, and gray matter volume: findings from the BiDirect Study

Study objectives: Sleep is essential for restorative metabolic changes and its physiological correlates can be examined using overnight polysomnography. However, the association between physiological sleep characteristics and brain structure is not well understood. We aimed to investigate gray matter volume and cognitive performance related to physiological sleep characteristics.

Methods: Polysomnographic recordings from 190 community-dwelling participants were analyzed with a principal component analysis in order to identify and aggregate shared variance into principal components. The relationship between aggregated sleep components and gray matter volume was then analyzed using voxel-based morphometry. In addition, we explored how cognitive flexibility, selective attention, and semantic fluency were related to aggregated sleep components and gray matter volume.

Results: Three principal components were identified from the polysomnographic recordings. The first component, primarily described by apnea events and cortical arousal, was significantly associated with lower gray matter volume in the left frontal pole. This apnea-related component was furthermore associated with lower cognitive flexibility and lower selective attention.

Conclusions: Sleep disrupted by cortical arousal and breathing disturbances is paralleled by lower gray matter volume in the frontal pole, a proposed hub for the integration of cognitive processes. The observed effects provide new insights on the interplay between disrupted sleep, particularly breathing disturbances and arousal, and the brain.