Wave Turbulence and Cortical Dynamics

TL;DR

This paper applies wave turbulence theory to cortical EEG and MEG signals, proposing a kinetic equation framework that explains complex spectral features and state transitions in brain activity.

Contribution

It introduces a novel kinetic equation for neural activity based on wave turbulence, linking spectral features to nonlinear wave interactions in the brain.

Findings

Power-law spectral behavior consistent with turbulence.

Cortical dynamics involve both single and dual cascades.

Spectral features shaped by 3-wave and 4-wave interactions.

Abstract

Cortical activity recorded through EEG and MEG reflects complex dynamics that span multiple temporal and spatial scales. Spectral analyses of these signals consistently reveal power-law behaviour, a hallmark of turbulent systems. In this paper, we derive a kinetic equation for neural field activity based on wave turbulence theory, highlighting how quantities such as energy and pseudo-particle density flow through wave-space (k-space) via direct and inverse cascades. We explore how different forms of nonlinearity, particularly 3-wave and 4-wave interactions, shape spectral features, including harmonic generation, spectral dispersion, and transient dynamics. While the observed power-law decays in empirical data are broadly consistent with turbulent cascades, variations across studies, such as the presence of dual decay rates or harmonic structures, point to a diversity of underlying mechanisms. We argue that although no single model fully explains all spectral observations, key constraints emerge: namely, that cortical dynamics exhibit features consistent with turbulent wave systems involving both single and dual cascades and a mixture of 3- and 4-wave interactions. This turbulence-based framework offers a principled and unifying approach to interpreting large-scale brain activity, including state transitions and seizure dynamics.