Unifying turbulent dynamics framework distinguishes different brain states.

Area of Science:

• Neuroscience
• Complex Systems Theory

Background:

• Previous research linked brain state synchrony to consciousness levels.
• Conscious states are typically asynchronous, while non-conscious states are synchronous.

Purpose of the Study:

• To investigate dissociable spatiotemporal dynamics underlying different brain states.
• To extend the understanding of brain dynamics beyond the synchrony/asynchrony dichotomy.

Main Methods:

• Analysis of human neuroimaging data from resting state, meditation, deep sleep, and disorders of consciousness.
• Application of Kuramoto's turbulence framework using coupled oscillators (model-free).
• Extension with information cascade measures across spatial scales.
• In silico perturbations of whole-brain models (model-based) to assess information encoding.

Main Results:

• Different brain states are characterized by distinct spatiotemporal dynamics.
• Turbulence theory effectively describes and differentiates between various brain states.
• Information cascade measures provide insights into spatial information flow.

Conclusions:

• Spatiotemporal dynamics, informed by turbulence theory, offer a novel framework for characterizing brain states.
• This approach moves beyond simple synchrony measures to reveal nuanced differences.
• The findings have implications for understanding consciousness and neurological disorders.