Unifying turbulent dynamics framework distinguishes different brain states

Abstract

Recently, significant advances have been made by identifying the levels of synchronicity of the underlying dynamics of a given brain state. This research has demonstrated that unconscious dynamics tend to be more synchronous than those found in conscious states, which are more asynchronous. Here we go beyond this dichotomy to demonstrate that the different brain states are always underpinned by spatiotemporal chaos but with dissociable turbulent dynamics. We investigated human neuroimaging data from different brain states (resting state, meditation, deep sleep, and disorders of consciousness after coma) and were able to distinguish between them using complementary model-free and model-based measures of turbulent information transmission. Our model-free approach used recent advances describing a measure of information cascade across spatial scales using tools from turbulence theory. Complementarily, our model-based approach used exhaustive in silico perturbations of whole-brain models fitted to the empirical neuroimaging data, which allowed us to study the information encoding capabilities of the brain states. Overall, the current framework demonstrates that different levels of turbulent dynamics are fundamental for describing and differentiating between brain states.

The Menstrual Cycle Modulates Whole-Brain Turbulent Dynamics

“…LC-MS, Liquid Chromatography-Mass Spectrometry. (A–D) adapted from Deco and Kringelbach ( 2020 ), Deco et al ( 2021a ) and Escrichs et al ( 2021 )…”

“…Therefore, the novelty of the method is that it allows analyzing the brain's information processing across spacetime scales, given that the size of rotational vortices determines various scales of information transmission. This framework has been successfully applied to characterize turbulent behavior in the brain's information processing during rest and different cognitive tasks (Deco and Kringelbach, 2020 ), demonstrated that different levels of turbulent dynamics describe and differentiate between unconscious and conscious brain states (Escrichs et al, 2021 ), and showed how large-scale connections enhance the transmission of information across the whole-brain network (Deco et al, 2021b ). Therefore, the turbulent framework may advance our understanding of the effect of the two main phases of the menstrual cycle (i.e., follicular and luteal) on large-scale brain network communication.…”

“…Here, we applied the turbulent framework (Deco and Kringelbach, 2020 ; Deco et al, 2021b ; Escrichs et al, 2021 ) to the same deep-sampling datasets used in Pritschet et al ( 2020 ) and Mueller et al ( 2021 ) to investigate the brain's information processing across spacetime scales during the follicular and luteal phases of a woman's menstrual cycle. First, we applied a turbulent dynamic analysis while the participant, scanned daily over an entire menstrual cycle ( N = 30 days), was freely cycling (NaturalMenstrualCycle Study).…”

Neural mass modelling for the masses: Democratising access to whole-brain biophysical modelling with FastDMF

“…This application could lead to promising novel insights about brain dynamics and evoked responses. 38,[48][49][50][51] .…”

Disruption in structural–functional network repertoire and time-resolved subcortical fronto-temporoparietal connectivity in disorders of consciousness

“…Dynamic connectivity analysis has also recently been applied to EEG data, revealing a loss of network integration and increased network segregation in DoC patients ( Rizkallah et al, 2019 ). Spatiotemporal properties of networks have been explored using whole brain modelling, which shows reduction in stability, heterogeneity, and information flow in loss of consciousness ( Escrichs et al, 2021 ; López-González et al, 2021 ; Panda et al, 2021 ). Despite the importance of the previously published work, the role of the well-known resting-state networks and especially thalamo-cortical functional connections ( Monti et al, 2015 ) within the context of time-resolved connectivity and DoC has so far not been fully explored.…”