Key result
Dynamic resting-state functional connectivity demonstrates lower variability within regions of interest than between them.
Why the study?
There are few dynamic resting state functional connectivity studies based on functional near infrared spectroscopy despite its advantages for studying temporal brain function evolution.
Population
20 young adults
Comparison
Resting-state brain fluctuations across different brain regions using fNIRS-EEG simultaneous recording
Design
Cross-sectional study with sliding-window and time-resolved k-means clustering analysis
Authors
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fNIRS-dRSFC extracts consistent dominant networks with EEG correlations in young adults; leaves open validation in clinical populations before wider use.
Cross-Sectional (n=20)
No
p-value: p=<0.001
This study demonstrates the feasibility of using fNIRS to extract dominant functional brain networks based on resting-state functional connectivity dynamics.
Zhang et al. (2020) conducted a cross-sectional in Healthy (n=20). Resting-state fNIRS-EEG was evaluated on Variability of dynamic resting-state functional connectivity (dRSFC) within vs between regions of interest (p=<0.001). The variability of dynamic resting-state functional connectivity within any region of interest was significantly lower than the connections between regions of interest (p < 0.001).
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