Journal of Neuroscience MethodsNeurosciencePeer-reviewed journal article
Self-similarity and multifractality in human brain activity: a wavelet-based analysis of scale-free brain dynamics
Daria La RoccaiD, Nicolas Zilber, Patrice AbryiD, Virginie van WassenhoveiD, Philippe CiuciuiD
Abstract
BackgroundThe temporal structure of macroscopic brain activity displays both oscillatory and scale-free dynamics. While the functional relevance of neural oscillations has been largely investigated, both the nature and the role of scale-free dynamics in brain processing have been disputed.\n\nNew MethodHere, we offer a novel method to rigorously enrich the characterization of scale-free brain activity using a robust wavelet-based assessment of self-similarity and multifractality. For this, we analyzed human brain activity recorded with magnetoencephalography (MEG) while participants were at rest or performing a task.\n\nResultsFirst, we report consistent infraslow (from 0.1 to 1.5 Hz) scalefree dynamics (i.e., self-similarity and multifractality) in resting-state and task data. Second, we observed a fronto-occipital gradient of self-similarity reminiscent of the known hierarchy of temporal scales from sensory to higherorder cortices; the anatomical gradient was more pronounced in task than in rest. Third, we observed a significant increase of multifractality during task as compared to rest. Additionally, the decrease in self-similarity and the increase in multifractality from rest to task were negatively correlated in regions involved in the task, suggesting a shift from structured global temporal dynamics in resting-state to locally bursty and non Gaussian scalefree structures during task.\n\nComparison with Existing Method(s)We showed that the wavelet leader based multifractal approach extends power spectrum estimation methods in the way of characterizing finely scale-free brain dynamics.\n\nConclusionsAltogether, our approach provides novel fine-grained characterizations of scale-free dynamics in human brain activity.\n\nHighlightsO_LIWe estimated scale-free human brain dynamics using wavelet-leader formalism.\nC_LIO_LIHigh-to-low self-similarity defined a fronto-occipital gradient.\nC_LIO_LIThe gradient was enhanced in task compared to resting-state.\nC_LIO_LIScale-free brain dynamics showed multifractal properties.\nC_LIO_LISelf-similarity decreased whereas multifractality increased from rest to task.\nC_LI
- organism: human
- assay: electronic health records
- approach: statistical model
- approach: transformer / foundation model
- Citations
- 52
- FWCI
- 2.82
- Field percentile
- top 9%
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