Open AccessDynamic changes of ICA‐derived EEG functional connectivity in the resting state
Author(s) -
Chen JeanLon,
Ros Tomas,
Gruzelier John H.
Publication year - 2013
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.21475
Subject(s) - default mode network , precuneus , resting state fmri , neuroscience , task positive network , independent component analysis , electroencephalography , psychology , power graph analysis , brain mapping , pattern recognition (psychology) , clustering coefficient , computer science , functional connectivity , cognition , artificial intelligence , graph , cluster analysis , theoretical computer science
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. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.