Open AccessFunctional connectivity‐based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI
Author(s) -
Kim DaeJin,
Park Bumhee,
Park HaeJeong
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.21517
Subject(s) - basal ganglia , thalamus , neuroscience , functional magnetic resonance imaging , resting state fmri , cerebral cortex , independent component analysis , brain mapping , psychology , cortex (anatomy) , biology , central nervous system , artificial intelligence , computer science
This study aimed to identify subunits of the basal ganglia and thalamus and to investigate the functional connectivity among these anatomically segregated subdivisions and the cerebral cortex in healthy subjects. For this purpose, we introduced multilevel independent component analysis (ICA) of the resting‐state functional magnetic resonance imaging (fMRI). After applying ICA to the whole brain gray matter, we applied second‐level ICA restrictively to the basal ganglia and the thalamus area to identify discrete functional subunits of those regions. As a result, the basal ganglia and the thalamus were parcelled into 31 functional subdivisions according to their temporal activity patterns. The extracted parcels showed functional network connectivity between hemispheres, between subdivisions of the basal ganglia and thalamus, and between the extracted subdivisions and cerebral functional components. Grossly, these findings correspond to cortico‐striato‐thalamo‐cortical circuits in the brain. This study also showed the utility of multilevel ICA of resting state fMRI in brain network research. Hum Brain Mapp, 2013. © 2012 Wiley Perodicals, Inc.