Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data

Vecchio, Fabrizio; Miraglia, Francesca; Gorgoni, Maurizio; Ferrara, Michele; Iberite, Francesco; Bramantı, Placido; Gennaro, Luigi De; Rossini, Paolo Maria

doi:10.1002/hbm.23736

Cited by 54 publications

(48 citation statements)

References 41 publications

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“…Indeed, during this particular period of wakefulness, there is a gradual decrease in the high-frequency EEG bands (β and α) and a gradual increase in the low-frequency EEG bands (δ) in order to prepare the sleep-wake transition [73]. However, the presence of these modifications in the frequency bands during this period preceding sleep onset seems to be associated with a more efficient antero-posterior cerebral communication favouring a more marked SWN organization in both men and women [74]. Furthermore, we demonstrated that compared to men, women had a greater sleep latency and a shorter sleep period time which seems to indicate the presence of reduced sleep duration in women.…”

Section: Discussionmentioning

confidence: 99%

Alterations of neural network organization during REM sleep in women: implication for sex differences in vulnerability to mood disorders

et al. 2020

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Background: Sleep plays an important role in vulnerability to mood disorders. However, despite the existence of sex differences in vulnerability to mood disorders, no study has yet investigated the sex effect on sleep network organization and its potential involvement in vulnerability to mood disorders. The aim of our study was to empirically investigate the sex effect on network organization during REM and slow-wave sleep using the effective connectivity measured by Granger causality. Methods: Polysomnographic data from 44 healthy individuals (28 men and 16 women) recruited prospectively were analysed. To obtain the 19 × 19 connectivity matrix of all possible pairwise combinations of electrodes by Granger causality method from our EEG data, we used the Toolbox MVGC multivariate Granger causality. The computation of the network measures was realized by importing these connectivity matrices into EEGNET Toolbox. Results: In men and women, all small-world coefficients obtained are compatible with a small-world network organization during REM and slow-wave sleep. However, compared to men, women present greater small-world coefficients during REM sleep as well as for all EEG bands during this sleep stage, which indicates the presence of a small-world network organization less marked during REM sleep as well as for all EEG bands during this sleep stage in women. In addition, in women, these small-world coefficients during REM sleep as well as for all EEG bands during this sleep stage are positively correlated with the presence of subclinical symptoms of depression. Conclusions: Thus, the highlighting of these sex differences in network organization during REM sleep indicates the presence of differences in the global and local processing of information during sleep between women and men. In addition, this small-world network organization less marked during REM sleep appears to be a marker of vulnerability to mood disorders specific to women, which opens up new perspectives in understanding sex differences in the occurrence of mood disorders.

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Section: Discussionmentioning

confidence: 99%

Alterations of neural network organization during REM sleep in women: implication for sex differences in vulnerability to mood disorders

et al. 2020

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“…One strength is the use of PLI to measure FC, since it reduces the bias due to volume conduction and activity from common sources (Stam et al, ). Another strong point is that when we compared the differences of global PLI and MST measures between groups, age, sex and the power of each frequency band were taken into consideration as covariates (Vecchio et al, ).…”

Section: Discussionmentioning

confidence: 99%

Random topology organization and decreased visual processing of internet addiction: Evidence from a minimum spanning tree analysis

Wang

Sun

et al. 2019

Brain and Behavior

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Objectives Internet addiction (IA) has been associated with widespread brain alterations. Functional connectivity (FC) and network analysis results related to IA are inconsistent between studies, and how network hubs change is not known. The aim of this study was to evaluate functional and topological networks using an unbiased minimum spanning tree (MST) analysis on electroencephalography (EEG) data in IA and healthy control (HC) college students. Methods In this study, Young's internet addiction test was used as an IA severity measure. EEG recordings were obtained in IA ( n = 30) and HC participants ( n = 30), matched for age and sex, during rest. The phase lag index (PLI) and MST were applied to analyze FC and network topology. We expected to obtain evidence of underlying alterations in functional and topological networks related to IA. Results IA participants showed higher delta FC between left‐side frontal and parieto‐occipital areas compared to the HC group ( p < 0.001), global MST measures revealed a more star‐like network in IA participants in the upper alpha and beta bands, and the occipital brain region was relatively less important in the IA relative to the HC group in the lower band. The correlation results were consistent with the MST results: higher IA severity correlated with higher Max degree and kappa, and lower eccentricity and diameter. Conclusions Functional networks of the IA group were characterized by increased FC, a more random organization, and a decrease of relative functional importance of the visual processing area. Taken together, these alterations can help us understand the influence of IA to brain mechanism.

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“…Functional connectivity was computed by eLORETA software (available at http://www.uzh.ch/keyinst/loreta) on 84 regions of interest (ROIs) de ned according to the 42 Brodmann areas (BAs) in the left and right hemispheres. The signal at each ROI was the average electrical neuron activity of all voxels in the ROI [32]. Among the eLORETA current density time series of the 84 ROIs, lagged linear connectivity [33] was computed between all possible pairs of the 84 ROIs for the alpha band for each subject.…”

Section: Functional Connectivity Analysismentioning

confidence: 99%

Decreased resting-state alpha-band activation and functional connectivity after sleep deprivation

Zhou

Chen

et al. 2020

Preprint

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BackgroundCognitive abilities are impaired by sleep deprivation and can be recovered when sufficient sleep is obtained. Changes in alpha-band oscillations are considered to be highly related to sleep deprivation. The effect of sleep deprivation on brain activation and functional connectivity in the resting-state alpha band remains unclear. The purpose of this study was to investigate how sleep deprivation and recovery sleep could change resting-state alpha-band neural oscillations.MethodsIn this study, thirty young, healthy participants obtained approximately 8 h of normal sleep, followed by 36 h of sleep deprivation. On the following recovery night, subjects underwent recovery sleep. Resting-state EEG after normal sleep, sleep deprivation and recovery sleep was recorded. Power spectrum, source localization and functional connectivity analyses were used to investigate the changes in resting-state alpha-band activity after normal sleep, sleep deprivation and recovery sleep.ResultsThe results showed that the global alpha power spectrum decreased and source activation was notably reduced in the precuneus, posterior cingulate cortex, cingulate gyrus, and paracentral lobule after sleep deprivation. Functional connectivity analysis after sleep deprivation showed a weakened functional connectivity pattern in a widespread network with the precuneus and posterior cingulate cortex as the key nodes. Furthermore, the changes caused by sleep deprivation were reversed to a certain extent but not significantly after one night of sleep recovery, which may be due to inadequate time for recovery sleep.ConclusionsIn conclusion, large-scale resting-state alpha-band activation and functional connectivity were weakened after sleep deprivation, and the inhibition of default mode network function with the precuneus and posterior cingulate cortex as the pivotal nodes may be an important cause of cognitive impairment. These findings provide new insight into the physiological response of sleep deprivation and determine how sleep deprivation disrupts brain alpha-band oscillations.

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Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data

Cited by 54 publications

References 41 publications

Alterations of neural network organization during REM sleep in women: implication for sex differences in vulnerability to mood disorders

Alterations of neural network organization during REM sleep in women: implication for sex differences in vulnerability to mood disorders

Random topology organization and decreased visual processing of internet addiction: Evidence from a minimum spanning tree analysis

Decreased resting-state alpha-band activation and functional connectivity after sleep deprivation

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