Characterization of specific spatial functional connectivity difference in depression during sleep.

Depression is a common mental illness and a large number of researchers have been still devoted to exploring effective biomarkers for the identification of depression. Few researches have been conducted on functional connectivity (FC) during sleep in depression. In this paper, a novel depression characterization is proposed using specific spatial FC features of sleep electroencephalography (EEG). Overnight polysomnography recordings were obtained from 26 healthy individuals and 25 patients with depression. The weighted phase lag indexes (WPLIs) of four frequency bands and five sleep periods were obtained from 16 EEG channels. The high discriminative connections extracted via feature evaluation and the cross-within variation (CW)-the spatial feature constructed to characterize the different performances in inter- and intra-hemispheric FC based on WPLIs, were utilized to classify patients and normal controls. The results showed that enhanced average FC and spatial differences, higher inter-hemispheric FC and lower intra-hemispheric FC, were found in patients. Furthermore, abnormalities in the inter-hemispheric connections of the temporal lobe in the theta band should be important indicators of depression. Finally, both CW and high discriminative WPLI features performed well in depression screening and CW was more specific for characterizing abnormal cortical EEG performance of depression. Our work investigated and characterized the abnormalities in sleep cortical activity in patients with depression, and may provide potential biomarkers for assisting with depression identification and new insights into the understanding of pathological mechanisms in depression.