Stationary EEG pattern relates to large-scale resting state networks - An EEG-fMRI study connecting brain networks across time-scales.

Daniel Arzate-Mena, J; Abela, Eugenio; Olguín-Rodríguez, Paola V; Ríos-Herrera, Wady; Alcauter, Sarael; Schindler, Kaspar; Wiest, Roland; Müller, Markus F; Rummel, Christian (2022). Stationary EEG pattern relates to large-scale resting state networks - An EEG-fMRI study connecting brain networks across time-scales. NeuroImage, 246(118763), p. 118763. Elsevier 10.1016/j.neuroimage.2021.118763

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Relating brain dynamics acting on time scales that differ by at least an order of magnitude is a fundamental issue in brain research. The same is true for the observation of stable dynamical structures in otherwise highly non-stationary signals. The present study addresses both problems by the analysis of simultaneous resting state EEG-fMRI recordings of 53 patients with epilepsy. Confirming previous findings, we observe a generic and temporally stable average correlation pattern in EEG recordings. We design a predictor for the General Linear Model describing fluctuations around the stationary EEG correlation pattern and detect resting state networks in fMRI data. The acquired statistical maps are contrasted to several surrogate tests and compared with maps derived by spatial Independent Component Analysis of the fMRI data. By means of the proposed EEG-predictor we observe core nodes of known fMRI resting state networks with high specificity in the default mode, the executive control and the salience network. Our results suggest that both, the stationary EEG pattern as well as resting state fMRI networks are different expressions of the same brain activity. This activity is interpreted as the dynamics on (or close to) a stable attractor in phase space that is necessary to maintain the brain in an efficient operational mode. We discuss that this interpretation is congruent with the theoretical framework of complex systems as well as with the brain's energy balance.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology

UniBE Contributor:

Schindler, Kaspar Anton, Wiest, Roland Gerhard Rudi, Rummel, Christian

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1053-8119

Publisher:

Elsevier

Language:

English

Submitter:

Chantal Kottler

Date Deposited:

17 Dec 2021 16:01

Last Modified:

02 Mar 2023 23:35

Publisher DOI:

10.1016/j.neuroimage.2021.118763

PubMed ID:

34863961

Uncontrolled Keywords:

Complexity and criticality Default mode network Electroencephalogram Executive control network Functional magnetic resonance imaging Independent component analysis Salience network

BORIS DOI:

10.48350/162039

URI:

https://boris.unibe.ch/id/eprint/162039

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