Scale-Free Neurodynamics as Functional Fingerprint of Brain Regions

This study investigates the ongoing electrical activity of local neural networks-referred to as neurodynamics-across 37 anatomically defined brain regions. We analyzed stereotactic intracranial EEG (sEEG) recordings from 106 subjects during wakeful rest, focusing on scale-free (power-law) properties to determine whether distinct brain regions exhibit unique neurodynamic signatures. Results revealed a power-law regime in two frequency ranges (approximately 0.5-4 Hz and 33-80 Hz). Notably, the power-law exponent (slope) in the high-frequency band differed significantly between cortical and subcortical areas (<i>p</i> < 0.01). These findings suggest that local neurodynamics, as reflected in scale-free characteristics, may serve as a functional "fingerprint" for brain region classification. This approach may contribute to functional brain parcellation efforts and offer new insights into the intrinsic organization of neuronal networks as revealed by resting-state activity analysis.