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Related Experiment Video

Updated: Jan 14, 2026

Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS
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Resting-State Functional MRI Analyses for Brain Activity Characterization: A Narrative Review of Features and

Alejandro Amador-Tejada1,2, Bhanu Sharma2,3,4, Ethan Danielli2,5

  • 1School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.

The European Journal of Neuroscience
|October 23, 2025
PubMed
Summary

This review explores various resting-state fMRI (rsfMRI) analyses beyond functional connectivity (FC). It details methods like ALFF, ReHo, Hurst exponent, and entropy to better understand brain activity and guide research choices.

Keywords:
blood‐oxygen‐level‐dependent (BOLD) signalfunctional magnetic resonance imaging (fMRI)global brain activitylocal brain activitylow‐frequency fluctuationsneuroimagingresting state

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Area of Science:

  • Neuroimaging
  • Brain Activity Analysis
  • Resting-state functional Magnetic Resonance Imaging (rsfMRI)

Background:

  • Resting-state fMRI (rsfMRI) measures spontaneous brain activity using the blood-oxygen-level-dependent (BOLD) signal.
  • Functional connectivity (FC) is a common rsfMRI analysis, but other methods offer complementary insights into brain function.

Purpose of the Study:

  • To provide a comprehensive investigation of common rsfMRI analyses beyond FC.
  • To explain the concepts, mathematical underpinnings, and significance of various rsfMRI metrics.

Main Methods:

  • A narrative review of studies employing common rsfMRI analyses.
  • Description of five key rsfMRI analyses: FC, Amplitude of Low-Frequency Fluctuations (ALFF)/fractional ALFF (fALFF), Regional Homogeneity (ReHo), Hurst exponent (H), and entropy.
  • Summary of common rsfMRI data processing steps.

Main Results:

  • Five distinct rsfMRI analyses were detailed, each capturing different aspects of BOLD signal characteristics.
  • FC reflects global connectivity, ALFF/fALFF indicate signal intensity, ReHo measures local connectivity, H depicts signal autocorrelation, and entropy shows signal predictability.

Conclusions:

  • Selecting the appropriate rsfMRI analysis is crucial for effectively exploring brain function.
  • This review serves as a catalog of standard rsfMRI analyses to aid researchers and clinicians in making informed decisions.