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001034747 0247_ $$2doi$$a10.1101/2024.05.30.596582
001034747 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-07504
001034747 037__ $$aFZJ-2024-07504
001034747 1001_ $$0P:(DE-HGF)0$$aManasova, Dragana$$b0
001034747 245__ $$aDynamics of EEG Microstates Change Across the Spectrum of Disorders of Consciousness
001034747 260__ $$c2024
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001034747 520__ $$aAs a response to the environment and internal signals, brain networks reorganize on asub-second scale. To capture this reorganization in patients with disorders ofconsciousness and understand their residual brain activity, we investigated thedynamics of electroencephalography (EEG) microstates. We analyze EEG microstatemarkers to quantify the periods of semi-stable topographies and the large-scalecortical networks they may reflect. To achieve this, EEG samples are clustered intofour groups and then fit back into each time sample. We then obtain a time series ofmaps with different frequencies of occurrence and duration. One such occurrence of amap with a given duration is called a microstate. The goal of this work is to study thedynamics of these topographical patterns across patients with disorders ofconsciousness. Using the microstate time series, we calculate static and dynamicmarkers. In contrast to the static, the dynamic metrics depend on the specific temporalsequences of the maps. The static measure Ratio of Total Time covered (RTT) showsdifferences between healthy controls and patients, however, no differences wereobserved between the groups of patients. In contrast, some dynamic markers captureinter-patient group differences. The dynamic markers we investigated are MeanMicrostate Durations (MMD), Microstate Duration Variances (MDV), MicrostateTransition Matrices (MTM), and Entropy Production (EP). The MMD and MDVdecrease with the state of consciousness, whereas the MTM non-diagonal transitionsand EP increase. In other words, DoC patients have slower and closer to equilibrium(time-reversible) brain dynamics. In conclusion, static and dynamic EEG microstatemetrics differ across consciousness levels, with the latter capturing the subtitlerdifferences between groups of patients with disorders of consciousness.
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001034747 7001_ $$0P:(DE-HGF)0$$aSanz Perl, Yonatan$$b1
001034747 7001_ $$0P:(DE-HGF)0$$aBruno, Nicolas Marcelo$$b2
001034747 7001_ $$0P:(DE-HGF)0$$aValente, Melanie$$b3
001034747 7001_ $$0P:(DE-HGF)0$$aRohaut, Benjamin$$b4
001034747 7001_ $$0P:(DE-HGF)0$$aTagliazucchi, Enzo$$b5
001034747 7001_ $$0P:(DE-HGF)0$$aNaccache, Lionel$$b6
001034747 7001_ $$0P:(DE-Juel1)185083$$aRaimondo, Federico$$b7
001034747 7001_ $$0P:(DE-HGF)0$$aSitt, Jacobo D.$$b8$$eCorresponding author
001034747 773__ $$a10.1101/2024.05.30.596582
001034747 8564_ $$uhttps://juser.fz-juelich.de/record/1034747/files/Manasova%20et%20al.%20-%202024%20-%20Dynamics%20of%20EEG%20Microstates%20Change%20Across%20the%20Spec.pdf$$yOpenAccess
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001034747 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Paris 75013, France$$b8
001034747 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a jacobo.sitt@icm-institute.org$$b8
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