Resting-State Functional Connectivity: Signal Origins and Analytic Methods
Document Type
Article
Publication Date
2-1-2020
Abstract
Resting 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.
Identifier
85075215246 (Scopus)
Publication Title
Neuroimaging Clinics of North America
External Full Text Location
https://doi.org/10.1016/j.nic.2019.09.012
e-ISSN
15579867
ISSN
10525149
PubMed ID
31759568
First Page
15
Last Page
23
Issue
1
Volume
30
Grant
R01AT009829
Recommended Citation
Chen, Kai; Azeez, Azeezat; Chen, Donna Y.; and Biswal, Bharat B., "Resting-State Functional Connectivity: Signal Origins and Analytic Methods" (2020). Faculty Publications. 5493.
https://digitalcommons.njit.edu/fac_pubs/5493
