Title
Group independent component analysis of resting state EEG in large normative samplesGroup independent component analysis of resting state EEG in large normative samples
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Research group
Translational Neurosciences (TNW)
Publication type
article
Publication
Amsterdam,
Subject
Psychology
Human medicine
Source (journal)
International journal of psychophysiology. - Amsterdam
Volume/pages
78(2010):2, p. 89-99
ISSN
0167-8760
ISI
000283962800001
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
EEG (Electroencephalography) resting state was studied by means of group blind source separation (gBSS), employing a testretest strategy in two large-sample normative databases (N = 57 and N = 84). Using a BSS method in the complex Fourier domain and a model-driven distributed inverse solution we closely replicate both the spatial distribution and spectral pattern of seven source components. Norms were then constructed for their spectral power so as to allow testing patients against the norms. As compared to existing normative databases based on scalp spectral measures, the resulting tool defines a smaller number of features with very little inter-correlation. Furthermore, these features are physiologically meaningful as they relate the activity of several brain regions, forming a total of seven patterns, each with a peculiar spatial distribution and spectral profile. This new tool, that we name normative independent component analysis (NICA), may serve as an adjunct to diagnosis and assessment of abnormal brain functioning and aid in research on normal resting state networks.
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