Resting-State Functional Connectivity: Signal Origins and Analytic Methods

Kai Chen; Azeezat Azeez; Donna Y. Chen; Bharat B. Biswal

doi:10.1016/j.nic.2019.09.012

Resting-State Functional Connectivity: Signal Origins and Analytic Methods

Kai Chen, Azeezat Azeez, Donna Y. Chen, Bharat B. Biswal

Research output: Contribution to journal › Review article › peer-review

28 Scopus citations

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.

Original language	English (US)
Pages (from-to)	15-23
Number of pages	9
Journal	Neuroimaging Clinics of North America
Volume	30
Issue number	1
DOIs	https://doi.org/10.1016/j.nic.2019.09.012
State	Published - Feb 2020

All Science Journal Classification (ASJC) codes

Radiology Nuclear Medicine and imaging
Clinical Neurology

Keywords

BOLD signal
Brain connectivity
Functional MRI
Functional connectivity
Psychoradiology
Resting state
Resting-state functional connectivity

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10.1016/j.nic.2019.09.012

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title = "Resting-State Functional Connectivity: Signal Origins and Analytic Methods",

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.",

keywords = "BOLD signal, Brain connectivity, Functional MRI, Functional connectivity, Psychoradiology, Resting state, Resting-state functional connectivity",

author = "Kai Chen and Azeezat Azeez and Chen, {Donna Y.} and Biswal, {Bharat B.}",

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T2 - Signal Origins and Analytic Methods

AU - Chen, Kai

AU - Azeez, Azeezat

AU - Chen, Donna Y.

AU - Biswal, Bharat B.

PY - 2020/2

Y1 - 2020/2

N2 - 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.

AB - 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.

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KW - Brain connectivity

KW - Functional MRI

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KW - Psychoradiology

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Resting-State Functional Connectivity: Signal Origins and Analytic Methods

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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