Resting-State Quantitative Electroencephalography Reveals Increased Neurophysiologic Connectivity in Depression

Abstract

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–20 Hz) frequency bands. The frontopolar region contained the greatest number of “hub nodes” (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD.

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

“…It may be due to the limited number of individual electrodes or the improper measurement method. For the increased global coherence of the MDD group, some researchers interpreted it as adaptive and compensatory mechanisms aimed to overcome the deficient semantic integration [55]. Our findings further support this adaptive and compensatory mechanism.…”

“…Fingelkurts et al [54] reported the increased synchronization was observed in the EEG alpha and theta bands in the patients with MDD. And an increased topographic EEG coherence in the frontal brain areas in the MDD group in the EEG alpha, beta, and theta bands was reported by Leuchter's team [55]. However, the findings in the previous studies are inconsistent and sometimes even contradictory to each other.…”

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

“…More recent studies used a huge variety of connectivity measures like partial directed coherence, Granger causality, structural synchrony index and phase synchrony index. Some found decreased EEG connectivity in MDD [122,132,133,134] while others report of increased EEG connectivity in MDD, mainly in the alpha band [135,136,137,138]. More studies are needed to disentangle the complex relationship between the different connectivity measures and their physiological interpretation and to estimate the value for treatment prediction.…”

Chronic deep brain stimulation of the rat ventral medial prefrontal cortex disrupts hippocampal–prefrontal coherence

“…Previous work using electroencephalograms (EEGs) to examine inter-region coherence in depressed versus control patients have yielded complex results, with differences found in the proximity of electrode pairs, their hemisphere, and frequency bands (Fingelkurts et al, 2007;Leuchter et al, 2012). The effects on EEG of treatment with SCG DBS are also complex, although generally appear to make depressed brains appear more similar to nondepressed controls (Broadway et al, 2012;Quraan et al, 2014).…”