Resting‐State Functional MRI Analyses for Brain Activity Characterization: A Narrative Review of Features and Methods

TL;DR

This paper reviews different resting-state fMRI analyses to understand brain activity, focusing on features like connectivity, signal intensity, and complexity.

Contribution

The paper provides a comprehensive review of standard resting-state fMRI analyses beyond functional connectivity.

Findings

Five common rsfMRI analyses are described, including functional connectivity and entropy.

Each analysis offers unique insights into brain activity, such as regional connectivity and signal predictability.

The review emphasizes the importance of selecting the right analysis based on the research question.

Abstract

Resting‐state fMRI (rsfMRI) is a widely used neuroimaging technique that measures spontaneous fluctuations in brain activity in the absence of specific external cognitive, motor, emotional, and sensory tasks or stimuli, based on the blood‐oxygen‐level‐dependent (BOLD) signal. Functional connectivity (FC) is a popular rsfMRI analysis examining BOLD signal correlations between brain regions. Nevertheless, there are alternative analyses that provide different but collectively informative characteristics of the BOLD signal and, thus, brain activity. This narrative review aimed to provide a comprehensive conceptual, mathematical, and significance investigation of common rsfMRI analyses in addition to FC. To achieve this, a narrative review was conducted on studies using the most common rsfMRI analysis to investigate global and local brain activity. Five rsfMRI analyses were described, summarizing the common initial steps of rsfMRI data processing and explaining the main characteristics and how each metric is calculated. The rsfMRI analyses described are (1) FC, reflecting BOLD global connectivity; (2) the amplitude of low‐frequency fluctuations (ALFF) and fractional ALFF (fALFF), representing the intensity of the BOLD signal; (3) regional homogeneity (ReHo), which reflects BOLD local connectivity; (4) Hurst exponent (H), depicting autocorrelation of the BOLD signal; and (5) entropy, depicting the BOLD signal predictability. As rsfMRI is a vital tool for exploring brain function, selecting an analysis that aligns with the research question is essential. This review offers an initial catalog of standard rsfMRI analyses, highlighting their key features, concepts, and considerations to support informed decisions by researchers and clinicians.

Functional connectivity is a popular resting‐state functional MRI analysis. Nevertheless, there are alternative approaches that can be used to characterize the BOLD signal differently, which allow for indirect characterization of brain activity, focusing on regional connectivity, intensity, and complexity. This review offers an initial core set of standard analyses, highlighting their key features, concepts, and considerations to support informed decisions by researchers and clinicians.

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