Abstract

One of the biggest challenges in cognitive neuroscience is developing diagnostic tools for Disorders of Consciousness (DoC). Detecting dynamical connectivity brain states seems promising, specifically those linked to transient moments of enhanced cognitive states in patients. A growing body of evidence indicates that fMRI brain states properties are strongly modulated by the level of consciousness , as theoretically predicted by whole brain modeling. fMRI-based brain states, however, have very limited practical application due to methodological constraints. In this work we defined EEG-based brain states and explored their potential as a bedside, real-time tool to detect transient windows of enhanced brain states. We analysed data from 237 individual patients with chronic and acute DoCs -100 Unresponsive Wakefulness Syndrome (UWS), 96 Minimally Conscious State (MCS) and 41 acute- and 101 healthy controls obtained in three independent research centers (Fudan hospital in Shanghai, Pitié Salpêtrière in Paris and Purpan hospital in Toulouse). We determined five EEG functional connectivity brain states, and show that their probability of occurrence is strongly related to the level of consciousness. Distinctively, high entropy brain states are exclusively found in healthy subjects, while low-entropy brain states increase their probability with DoC’s severity, spanning from acute unarousable comatose state, to more chronic DoC’s patients, who are awake but show fluctuating (MCS) or absent awareness (VS). Furthermore, the brain state probability distribution of each individual subject —and even the presence of certain key brain states— significantly vary with the patients’ outcome. We also tested whether our procedure has an actual potential for real-time, bedside brain state detection, and proved that we can reliably estimate the concurrent brain state of a patient in real time, paving the way for a broad application of this tool for DoC patients’ diagnosis, follow-up, and neuroprognostication.