Unifying turbulent dynamics framework distinguishes different brain states

Escrichs, Anira; Perl, Yonatan Sanz; Uribe, Carme; Càmara, Estela; Türker, Bașak; Pyatigorskaya, Nadya; López-González, Ane; Pallavicini, Carla; Panda, Rajanikant; Annen, Jitka; Gosseries, Olivia; Laureys, Steven; Naccache, Lionel; Sitt, Jacobo; Laufs, Helmut; Tagliazucchi, Enzo; Kringelbach, Morten L.; Deco, Gustavo

doi:10.1038/s42003-022-03576-6

“…This scenario is very close to that of the Benjamin-Feir instability in the Ginzburg-Landau system, which was studied by Kuramoto as a main route to turbulence in chemical reaction systems [48, 49, 56]. Our findings thus align with recent studies that remark the prominence of turbulent dynamics as signature of brain states [8, 98–101].…”

Section: Discussionsupporting

confidence: 91%

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Clusella

¹

,

Deco

²

,

Kringelbach

³

et al. 2022

Preprint

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Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next-generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.

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“…The emergence of high-dimensional chaos in large-scale brain networks is in line with recent studies that highlight the prominence of turbulent dynamics as a signature of healthy brain activity [ 8 , 71 , 101 – 103 ]. These complex fluctuations are observed in blood-oxygen-level-dependent (BOLD) signals obtained from fMRI scans, which are characterized by slow (below 1Hz) fluctuations.…”

Section: Discussionsupporting

confidence: 84%

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Clusella

¹

,

Deco

²

,

Kringelbach

³

et al. 2023

Self Cite

View full text Add to dashboard Cite

Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next-generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.

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“…Another interpretation could be that certain connections with the subcortical areas remain and the activation of the Visual network was related to some unconscious emotional processing [86–88]. The joint differential activation of the Visual, Somatomotor and the DMN, following the decrease in the level of consciousness, is certainly a key characteristic that has been discovered through different methodologies in previous experiments [60,89–92].…”

Section: Discussionmentioning

confidence: 99%

“…We included a total of 31 patients in MCS (11 females, mean age ± s.d., 47.25 ± 20.76 years), 24 in UWS (10 females, mean age ± s.d., 39.25 ± 16.30 years) and 13 healthy controls (seven females, mean age ± s.d., 42.54 ± 13.64 years) described in our previous study [60]. Trained clinicians carried out the clinical assessment and CRS-R scoring to determine their level of consciousness.…”

Section: Methodsmentioning

confidence: 99%

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The lack of temporal brain dynamics asymmetry as a signature of impaired consciousness states

G-Guzmán

¹

,

Perl

²

,

Vohryzek

³

et al. 2023

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Life is a constant battle against equilibrium. From the cellular level to the macroscopic scale, living organisms as dissipative systems require the violation of their detailed balance, i.e. metabolic enzymatic reactions, in order to survive. We present a framework based on temporal asymmetry as a measure of non-equilibrium. By means of statistical physics, it was discovered that temporal asymmetries establish an arrow of time useful for assessing the reversibility in human brain time series. Previous studies in human and non-human primates have shown that decreased consciousness states such as sleep and anaesthesia result in brain dynamics closer to the equilibrium. Furthermore, there is growing interest in the analysis of brain symmetry based on neuroimaging recordings and since it is a non-invasive technique, it can be extended to different brain imaging modalities and applied at different temporo-spatial scales. In the present study, we provide a detailed description of our methodological approach, paying special attention to the theories that motivated this work. We test, for the first time, the reversibility analysis in human functional magnetic resonance imaging data in patients suffering from disorder of consciousness. We verify that the tendency of a decrease in the asymmetry of the brain signal together with the decrease in non-stationarity are key characteristics of impaired consciousness states. We expect that this work will open the way for assessing biomarkers for patients' improvement and classification, as well as motivating further research on the mechanistic understanding underlying states of impaired consciousness.

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Unifying turbulent dynamics framework distinguishes different brain states

Cited by 29 publications

References 94 publications

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

The lack of temporal brain dynamics asymmetry as a signature of impaired consciousness states

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