Dynamic changes of ICA‐derived EEG functional connectivity in the resting state

Abstract

An emerging issue in neuroscience is how to identify baseline state(s) and accompanying networks termed "resting state networks" (RSNs). Although independent component analysis (ICA) in fMRI studies has elucidated synchronous spatiotemporal patterns during cognitive tasks, less is known about the changes in EEG functional connectivity between eyes closed (EC) and eyes open (EO) states, two traditionally used baseline indices. Here we investigated healthy subjects (n = 27) in EC and EO employing a four-step analytic approach to the EEG: (1) group ICA to extract independent components (ICs), (2) standardized low-resolution tomography analysis (sLORETA) for cortical source localization of IC network nodes, followed by (3) graph theory for functional connectivity estimation of epochwise IC band-power, and (4) circumscribing IC similarity measures via hierarchical cluster analysis and multidimensional scaling (MDS). Our proof-of-concept results on alpha-band power demonstrate five statistically clustered groups with frontal, central, parietal, occipitotemporal, and occipital sources. Importantly, during EO compared with EC, graph analyses revealed two salient functional networks with frontoparietal connectivity: a more medial network with nodes in the mPFC/precuneus which overlaps with the "default-mode network" (DMN), and a more lateralized network comprising the middle frontal gyrus and inferior parietal lobule, coinciding with the "dorsal attention network" (DAN). Furthermore, a separate MDS analysis of ICs supported the emergence of a pattern of increased proximity (shared information) between frontal and parietal clusters specifically for the EO state. We propose that the disclosed component groups and their source-derived EEG functional connectivity maps may be a valuable method for elucidating direct neuronal (electrophysiological) RSNs in healthy people and those suffering from brain disorders.

Encephalography Connectivity on Sources in Male Nonsmokers after Nicotine Administration during the Resting State

“…Checking the literature further, we can confirm that the 13 ROIs suggested in Chen et al [39] are in line with previous fMRI literature investigating the resting-state network during EO and EC conditions [40,41,42]. Furthermore, the interhemispheric asymmetry present in Chen et al [39] is also present in other articles studying the resting-state networks during EO and EC [40]. …”

“…Regions of Interest (ROIs) were chosen according to Chen et al [39] who identified 13 brain regions that show increased connectivity in the alpha band in an EO state with respect to an EC resting-state. Checking the literature further, we can confirm that the 13 ROIs suggested in Chen et al [39] are in line with previous fMRI literature investigating the resting-state network during EO and EC conditions [40,41,42].…”

“…The 13 time series were then used as input for either rPDC or VL analyses. Since the areas in Chen et al [39] were in Talairach coordinates, a conversion to MNI coordinates was conducted [43] using ‘tal2icbm_spm.m' (see http://www.brainmap.org/). Furthermore, SPM12 recognized some MNI coordinates as outside the brain, therefore a slight modification of the MNI coordinates produced by ‘tal2icbm_spm.m' was necessary.…”

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer’s Disease Detected Using Quantitative Electroencephalography

“…The authors found six components related to the ERP and show how the neuronal sources found using gICA can also be found applying ICA to each subject. A study of the "resting state networks", obtained by EEG during eyes closed and eyes open, was done by Chen et al [32], finding connectivity patterns between thirteen neuronal sources comparable with those found by fMRI. The analysis was based in gICA, to extract the neuronal sources related to resting state, and inverse solution methods to locate the neuronal sources in the brain cortex.…”

Creativity Is Enhanced by Long-Term Mindfulness Training and Is Negatively Correlated with Trait Default-Mode-Related Low-Gamma Inter-Hemispheric Connectivity

“…An early electrophysiological study (Martindale 1977) reported no consistent relationship between creativity and resting-state EEG alpha power, an EEG measure which was shown by several studies to be positively related to DMN activity (Chen et al 2008(Chen et al , 2013Laufs et al 2003;Mantini et al 2007). Yet, in a later study, resting-state EEG alpha power was only weakly positively correlated with divergent thinking scores, while coherence measures in all frequency bands-including alpha-negatively correlated with divergent thinking scores (Jaušovec and Jaušovec 2000).…”