Disturbed resting state EEG synchronization in bipolar disorder: A graph-theoretic analysis

Abstract

Disruption of functional connectivity may be a key feature of bipolar disorder (BD) which reflects disturbances of synchronization and oscillations within brain networks. We investigated whether the resting electroencephalogram (EEG) in patients with BD showed altered synchronization or network properties. Resting-state EEG was recorded in 57 BD type-I patients and 87 healthy control subjects. Functional connectivity between pairs of EEG channels was measured using synchronization likelihood (SL) for 5 frequency bands (δ, θ, α, β, and γ). Graph-theoretic analysis was applied to SL over the electrode array to assess network properties. BD patients showed a decrease of mean synchronization in the alpha band, and the decreases were greatest in fronto-central and centro-parietal connections. In addition, the clustering coefficient and global efficiency were decreased in BD patients, whereas the characteristic path length increased. We also found that the normalized characteristic path length and small-worldness were significantly correlated with depression scores in BD patients. These results suggest that BD patients show impaired neural synchronization at rest and a disruption of resting-state functional connectivity.

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults

“…[1][2][3][4][5][6][7][8]46 GTA is a network analysis tool that has been commonly used in functional neuroimaging to study brain connectivity and networks. [13][14][15]18,19 To date, however, atlas-DOT and GTA have not been used jointly to extract or derive large-scale brain connectivity and networks from the NIRS measurements because of computational challenges posed by atlas-DOT. Specifically, graph formation in GTA is a difficult and computationally expensive process for atlas-DOT because of the large amount of voxels in atlas-DOT images.…”

“…Increasingly, many neuroimaging techniques, such as fMRI, diffusion MRI, electroencephalographic (EEG), and DOT, have been recently used to investigate large-scale brain networks. [13][14][15][16][17] Accordingly, researchers have developed corresponding mathematical frameworks that can better model and analyze brain networks for a variety of imaging modalities. Graph theory analysis (GTA) is one of the analytical methods developed to examine largescale complex brain networks.…”

“…Graph theory analysis (GTA) is one of the analytical methods developed to examine largescale complex brain networks. [13][14][15]18,19 It can provide an uncomplicated and yet powerful mathematical means to characterize the brain networks' topological properties.…”

Disrupted Modular Architecture of Cerebellum in Schizophrenia: A Graph Theoretic Analysis

“…68 All mathematical details can be found in previous studies. 65,69,70 As noted in van Wijk et al, 71 the proportion of the total connections can be varied to investigate the network properties by varying a threshold (ie, removing the weaker connections based on their weighting). In this study, we constructed networks over a range from 5% (sparse matrix including only strong connections) to 50% (dense matrix including weak connections) of connection density.…”

Analysis of infant cortical synchrony is constrained by the number of recording electrodes and the recording montage

“…Recent studies have provided very useful tools to measure graph based network properties where spatial features may be extracted with post hoc, data-driven analysis of connectivity clusters. The latter approach has recently gained wide interest in neurophysiological studies of all age groups and in various neurocognitive disorders (Boersma et al, 2013;de Haan et al, 2009;Kim et al, 2013;Omidvarnia et al, 2014;Reijneveld et al, 2007).…”