Altered sleep brain functional connectivity in acutely depressed patients

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.

Topologically Convergent and Divergent Structural Connectivity Patterns between Patients with Remitted Geriatric Depression and Amnestic Mild Cognitive Impairment

“…However, several topological properties, including network strength, global efficiency, and absolute path length, were significantly altered in the RGD and aMCI groups compared with controls. These findings were consistent with previous neuroimaging studies using graph analysis to study depression (Leistedt et al, 2009) and AD (Stam et al, 2007;He et al, 2008;Supekar et al, 2008;Lo et al, 2010). Lower network strength was related to the sparse connectivity of the brain networks, which suggests a reduced WM integrity in the RGD and aMCI patients.…”

A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

“…Similar conclusions have been mentioned in the study of brain functional networks. In sleep neuronal functional networks of depressed patients, Leistedt et al [63] indicated the functional reorganization of depressed patients lost "small-world network" (SWN) characteristics. Zhang et al [64] and Li et al [7] teams also indicated the MDD patients showed a shift toward randomization in MDD brain networks compared with the healthy controls.…”

EEG Power Asymmetry and Functional Connectivity as a Marker of Treatment Effectiveness in DBS Surgery for Depression

“…Furthermore, these studies have used different approaches and methodologies to investigate differences in brain dynamics between depressed patients and healthy controls making it difficult to compare outcomes. For example, Lee et al (2011) used correlations between power series of channel pairs as a measure of connectivity; Leistedt et al (2009) used synchronization likelihood (Stam et al, 2003); whereas Fingelkurts et al (2007) used an in-house synchronization measure termed index of structural synchronization (Fingelkurts and Kahkonen, 2005). Although these and other EEG/MEG measures of connectivity (phase coherency, phase lag index, imaginary coherency, etc) have been shown to capture aspects of correlations/synchronization between two time series, they are known to perform differently.…”