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Functional connectivity-based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI

Authors

  • Dae-Jin Kim,

    1. Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana
    2. Department of Nuclear Medicine and Radiology, and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Korea
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  • Bumhee Park,

    1. Department of Nuclear Medicine and Radiology, and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Korea
    2. Brain Korea 21 Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • Hae-Jeong Park

    Corresponding author
    1. Department of Nuclear Medicine and Radiology, and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Korea
    2. Brain Korea 21 Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea
    • Department of Diagnostic Radiology, Psychiatry, Yonsei University College of Medicine, 134 Shinchon-Dong, Seodaemoon-Ku, Seoul 120-749, Korea
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Abstract

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.

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