4.7 Review

Monofractal analysis of functional magnetic resonance imaging: An introductory review

Journal

HUMAN BRAIN MAPPING
Volume 43, Issue 8, Pages 2693-2706

Publisher

WILEY
DOI: 10.1002/hbm.25801

Keywords

complexity; fractal analysis; functional magnetic resonance imaging; Hurst exponent; neuroimaging; scale-free dynamics

Funding

  1. BC Children's Hospital Research Institute
  2. British Columbia Children's Hospital Research Institute

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This review provides an overview of scale-free dynamics and monofractal analysis in neuroscience research, specifically in functional magnetic resonance imaging (fMRI). It emphasizes the use of the Hurst exponent to measure the complexity and scale-invariance of brain signaling. The article highlights the advantages, challenges, and future directions of fMRI monofractal analysis, aiming to promote its understanding, discussion, and application in the field.
The following review will aid readers in providing an overview of scale-free dynamics and monofractal analysis, as well as its applications and potential in functional magnetic resonance imaging (fMRI) neuroscience and clinical research. Like natural phenomena such as the growth of a tree or crashing ocean waves, the brain expresses scale-invariant, or fractal, patterns in neural signals that can be measured. While neural phenomena may represent both monofractal and multifractal processes and can be quantified with many different interrelated parameters, this review will focus on monofractal analysis using the Hurst exponent (H). Monofractal analysis of fMRI data is an advanced analysis technique that measures the complexity of brain signaling by quantifying its degree of scale-invariance. As such, the H value of the blood oxygenation level-dependent (BOLD) signal specifies how the degree of correlation in the signal may mediate brain functions. This review presents a brief overview of the theory of fMRI monofractal analysis followed by notable findings in the field. Through highlighting the advantages and challenges of the technique, the article provides insight into how to best conduct fMRI fractal analysis and properly interpret the findings with physiological relevance. Furthermore, we identify the future directions necessary for its progression towards impactful functional neuroscience discoveries and widespread clinical use. Ultimately, this presenting review aims to build a foundation of knowledge among readers to facilitate greater understanding, discussion, and use of this unique yet powerful imaging analysis technique.

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