Analysis of power law behavior of local cortical neurodynamics

•High frequency spectra of different cortical areas show distinct power-law exponents.•The wake/sleep state does not impact the power-law behavior in the three areas.•Power-law exponent might constitute a signature of a cortical area for possible cortical parcellation. Growing evidence suggests that...

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Bibliographic Details
Published inPhysica. D Vol. 477; p. 134733
Main Authors Armonaite, Karolina, Conti, Livio, Balsi, Marco, Paulon, Luca, Tecchio, Franca
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.07.2025
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Summary:•High frequency spectra of different cortical areas show distinct power-law exponents.•The wake/sleep state does not impact the power-law behavior in the three areas.•Power-law exponent might constitute a signature of a cortical area for possible cortical parcellation. Growing evidence suggests that neuronal electrical activity, the neurodynamics, contains specific signatures for distinct cortical parcels of the brain, potentially enabling cortex classification based on it, even in resting states. However, existing algorithms for extracting specific characteristics may succeed only in specific cases, or well selected groups, but often fail to identify stable features across the general populations. Our study examines intracranial stereotactic-electroencephalographic (sEEG) recordings, assessing power-law behavior in power spectral density during wakefulness and sleep stages across three gyri: precentral, postcentral and superior temporal, in 55 subjects. Results indicate the presence of a power-law behavior, implying scale-free dynamics in investigated areas. Notably, power-law exponent in high frequency range distinguishes cortical parcels both in wakefulness and sleep and suggests a stable scale-free pattern within each region possibly regardless of the state. This insight offers valuable guidance for evaluating physiological aspects of local neurodynamics and supports population-level functional cortex parceling.
ISSN:0167-2789
DOI:10.1016/j.physd.2025.134733