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Resting-State Functional Connectivity: Signal Origins and Analytic Methods.

Kai Chen1, Azeezat Azeez2, Donna Y Chen2

  • 1The 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 Clinics of North America
|November 25, 2019
PubMed
Summary

Resting state functional connectivity (RSFC) using fMRI reveals temporal correlations in brain signals. Understanding the biophysical and cognitive origins of these signals and their age-related changes remains an active area of research.

Keywords:
BOLD signalBrain connectivityFunctional MRIFunctional connectivityPsychoradiologyResting stateResting-state functional connectivity

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Area of Science:

  • Neuroimaging
  • Functional Magnetic Resonance Imaging (fMRI)
  • Brain Connectivity

Background:

  • Resting state functional connectivity (RSFC) is characterized by temporal correlations in spontaneous low-frequency signal fluctuations (SLFs).
  • The precise biophysical and cognitive origins of SLFs and their role in RSFC are not fully understood.
  • RSFC studies have indicated an 'age-related compensation' phenomenon.

Purpose of the Study:

  • To explore the current understanding of resting state functional connectivity (RSFC) in fMRI.
  • To discuss the ongoing debate regarding the origins of spontaneous low-frequency signal fluctuations (SLFs).
  • To highlight findings related to age-related changes in RSFC.

Main Methods:

  • Analysis of resting state functional magnetic resonance imaging (fMRI) data.
  • Review of various RSFC data analysis techniques, including time domain analysis, seed-based correlation, regional homogeneity, and principal and independent component analyses.
  • Examination of hypotheses concerning the biophysical and cognitive origins of RSFC.

Main Results:

  • RSFC is defined by temporal correlations of spontaneous low-frequency signal fluctuations (SLFs) within and across brain hemispheres.
  • Evidence suggests an 'age-related compensation' phenomenon in RSFC.
  • The exact role and origin of SLFs in RSFC are still under investigation.

Conclusions:

  • While RSFC is a widely studied fMRI metric, its underlying mechanisms and implications, particularly concerning aging, require further research.
  • Methodological challenges, including head motion and analytical limitations, persist in RSFC studies.
  • Continued investigation into RSFC is crucial for a comprehensive understanding of brain function.