Abstract
Recent evidence suggests that problems in information processing within neural networks may underlie depressive disease. In this study, we investigated whether sleep functional brain networks are abnormally organized during a major depressive episode (MDE). We characterized spatial patterns of functional connectivity by computing the "synchronization likelihood" (SL) of 19 sleep EEG channels in 11 acutely depressed patients [42 (20-51) years] and 14 healthy controls [32.9 (27-42) years]. To test whether disrupting an optimal pattern ["small-world network" (SWN)] of functional brain connectivity underlies MDE, graph theoretical measures were then applied to the resulting synchronization matrices, and a clustering coefficient (C, measure of local connectedness) and a shortest path length (L, measure of overall network integration) were determined. In the depressed group, the mean SL was lower in the delta, theta and sigma frequency bands. Acutely depressed patients showed a significantly lower path length in the theta and delta frequency bands, whereas the cluster coefficient showed no significant changes. The present study provides further support that sleep functional brain networks exhibit "small-world" properties. Sleep neuronal functional networks in depressed patients are characterized by a functional reorganization with a lower mean level of global synchronization and loss of SWN characteristics. These results argue for considering an MDE as a problem of neuronal network organization and a problem of information processing.