Altered electrophysiological meta-state dynamics in disorders of consciousness
Pablo Núñez1, Prejaas Tewarie2, Víctor Rodríguez-González3
1Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium; NeuroRehab & Consciousness Clinic, Neurology Department, University Hospital of Liège, Liège, Belgium; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain.
Background:
This multi-centric study aimed to explore differences in brain activity patterns in patients with disorders of consciousness (DoC), including unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS).
Methods:
Using high-density electroencephalographic (EEG) recordings from 368 DoC patients, 39 who emerged from MCS (eMCS), and 73 healthy controls, we examined instantaneous functional connectivity-based meta-states acting as attractors in a dynamical system, extracted by means of community detection algorithms and recurrence analysis. We analyzed data from two patient cohorts and included resting-state and auditory processing tasks in four frequency bands (delta, theta, alpha, beta) and from three perspectives, namely: (i) discrete activation of dominant states, (ii) a dynamical system composed of attractor states and (iii) the correlation and anticorrelation patterns of the active states.
Results:
Findings revealed that while the overall structure of brain connectivity remained stable after injury, patients with DoC and those who emerged showed notable differences in the speed and consistency of how their brain states activated. Specifically, in higher frequencies, UWS patients exhibited faster, and less stable dynamics, shorter dwell times and decreased meta-state anticorrelation compared to those in MCS and eMCS. Moreover, a four-way combined learning classification analysis showed that the measures were able to distinguish the UWS and MCS subgroups.
Significance:
These brain state dynamics could serve as valuable markers for assessing states of consciousness. Our results highlight the potential of using high-temporal resolution dynamic brain activity patterns to improve the understanding of altered consciousness and their application to clinical settings.
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