Interdependent scaling exponents in the human brain
Disordered Systems and Neural Networks2024-11-15v1Statistical MechanicsAdaptation and Self-Organizing SystemsData Analysis, Statistics and ProbabilityNeurons and Cognition
We apply the phenomenological renormalization group to resting-state fMRI time series of brain activity in a large population. By recursively coarse-graining the data, we compute scaling exponents for the series variance, log probability of silence, and largest covariance eigenvalue. The exponents clearly exhibit linear interdependencies, which we derive analytically in a mean-field approach. We find a significant correlation of exponent values with the gray matter volume and cognitive performance. Akin to scaling relations near critical points in thermodynamics, our findings suggest scaling interdependencies are intrinsic to brain organization and may also exist in other complex systems.
Cite
@article{arxiv.2411.09098,
title = {Interdependent scaling exponents in the human brain},
author = {Daniel M. Castro and Ernesto P. Raposo and Mauro Copelli and Fernando A. N. Santos},
journal= {arXiv preprint arXiv:2411.09098},
year = {2024}
}