Complexity synchronization analysis of neurophysiological data: Theory and methods.

ABSTRACT:

Introduction

We present a theoretical foundation based on the spontaneous self-organized temporal criticality (SOTC) and multifractal dimensionality μ to model complex neurophysiological and behavioral systems to infer the optimal empirical transfer of information among them. We hypothesize that heterogeneous time series characterizing the brain, heart, and lung organ-networks (ONs) are necessarily multifractal, whose level of complexity and, therefore, their information content is measured by their multifractal dimensions.

Methods

We apply modified diffusion entropy analysis (MDEA) to assess multifractal dimensions of ON time series (ONTS), and complexity synchronization (CS) analysis to infer information transfer among ONs that are part of a network-of-organ-networks (NoON

SUBMITTER: Schizas I 

PROVIDER: S-EPMC12116615 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature