Capturing the non-stationarity of whole-brain dynamics underlying human brain states

J. A. Galadí; S. Silva Pereira; Y. Sanz Perl; M. L. Kringelbach; I. Gayte; H. Laufs; E. Tagliazucchi; J. A. Langa; G. Deco

doi:10.1016/j.neuroimage.2021.118551

Capturing the non-stationarity of whole-brain dynamics underlying human brain states

J. A. Galadí, S. Silva Pereira, Y. Sanz Perl, M. L. Kringelbach, I. Gayte, H. Laufs, E. Tagliazucchi, J. A. Langa, G. Deco

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Brain dynamics depicts an extremely complex energy landscape that changes over time, and its characterisation is a central unsolved problem in neuroscience. We approximate the non-stationary landscape sustained by the human brain through a novel mathematical formalism that allows us characterise the attractor structure, i.e. the stationary points and their connections. Due to its time-varying nature, the structure of the global attractor and the corresponding number of energy levels changes over time. We apply this formalism to distinguish quantitatively between the different human brain states of wakefulness and different stages of sleep, as a step towards future clinical applications.

Original language	English
Article number	118551
Journal	NeuroImage
Volume	244
DOIs	https://doi.org/10.1016/j.neuroimage.2021.118551
State	Published - 1 Dec 2021
Externally published	Yes

Keywords

Attractors
Brain dynamics
Consciousness
Energy levels
Model transform
Sleep

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10.1016/j.neuroimage.2021.118551

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abstract = "Brain dynamics depicts an extremely complex energy landscape that changes over time, and its characterisation is a central unsolved problem in neuroscience. We approximate the non-stationary landscape sustained by the human brain through a novel mathematical formalism that allows us characterise the attractor structure, i.e. the stationary points and their connections. Due to its time-varying nature, the structure of the global attractor and the corresponding number of energy levels changes over time. We apply this formalism to distinguish quantitatively between the different human brain states of wakefulness and different stages of sleep, as a step towards future clinical applications.",

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AU - Galadí, J. A.

AU - Silva Pereira, S.

AU - Sanz Perl, Y.

AU - Kringelbach, M. L.

AU - Gayte, I.

AU - Laufs, H.

AU - Tagliazucchi, E.

AU - Langa, J. A.

AU - Deco, G.

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Y1 - 2021/12/1

N2 - Brain dynamics depicts an extremely complex energy landscape that changes over time, and its characterisation is a central unsolved problem in neuroscience. We approximate the non-stationary landscape sustained by the human brain through a novel mathematical formalism that allows us characterise the attractor structure, i.e. the stationary points and their connections. Due to its time-varying nature, the structure of the global attractor and the corresponding number of energy levels changes over time. We apply this formalism to distinguish quantitatively between the different human brain states of wakefulness and different stages of sleep, as a step towards future clinical applications.

AB - Brain dynamics depicts an extremely complex energy landscape that changes over time, and its characterisation is a central unsolved problem in neuroscience. We approximate the non-stationary landscape sustained by the human brain through a novel mathematical formalism that allows us characterise the attractor structure, i.e. the stationary points and their connections. Due to its time-varying nature, the structure of the global attractor and the corresponding number of energy levels changes over time. We apply this formalism to distinguish quantitatively between the different human brain states of wakefulness and different stages of sleep, as a step towards future clinical applications.

KW - Attractors

KW - Brain dynamics

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Capturing the non-stationarity of whole-brain dynamics underlying human brain states

Abstract

Keywords

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