• Kai Chen, Azeezat Azeez, Donna Y Chen, and Bharat B Biswal.
• The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, Sichuan 611731, China.
• Neuroimaging Clin. N. Am. 2020 Feb 1; 30 (1): 15-23.

AbstractResting state functional connectivity (RSFC) has been widely studied in functional magnetic resonance imaging (fMRI) and is observed by a significant temporal correlation of spontaneous low-frequency signal fluctuations (SLFs) both within and across hemispheres during rest. Different hypotheses of RSFC include the biophysical origin hypothesis and cognitive origin hypothesis, which show that the role of SLFs and RSFC is still not completely understood. Furthermore, RSFC and age studies have shown an "age-related compensation" phenomenon. RSFC data analysis methods include time domain analysis, seed-based correlation, regional homogeneity, and principal and independent component analyses. Despite advances in RSFC, the authors also discuss challenges and limitations, ranging from head motion to methodological limitations.Copyright © 2019 Elsevier Inc. All rights reserved.

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