Alterations of neural network organisation during rapid eye movement sleep and slow-wave sleep in major depression: Implications for diagnosis, classification, and treatment.

The aim of this study was to empirically investigate the network organisation during rapid eye movement sleep (REMS) and slow-wave sleep (SWS) using the effective connectivity measured using the Granger causality to identify new potential biomarkers for the diagnosis, classification, and potential favourable response to treatment in major depression. Polysomnographic data were analysed from 24 healthy individuals and 16 major depressed individuals recruited prospectively. To obtain the 19×19 connectivity matrix of all possible pairwise combinations of electrodes by the Granger causality method from our electroencephalographic data, we used the Toolbox MVGC multivariate Granger causality. The computation of network measures was realised by importing these connectivity matrices into the EEGNET Toolbox. Major depressed individuals (versus healthy individuals) and those with endogenous depression (versus those with neurotic depression) present alterations of small-world network organisation during REMS, whereas major depressed individuals with potential favourable response to electroconvulsive therapy (versus those with potential unfavourable response) have a less efficient small-world network organisation during SWS. Thus, alterations in network organisation during REMS could be biomarkers for the diagnosis and classification of major depressive episodes, whereas alterations of network organisation during SWS could be a biomarker to predict potential favourable response to treatment by electroconvulsive therapy.