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Disorders of consciousness due to severe hypoglycemia are rare but challenging to treat. The aim of this retrospective cohort study was to describe our multimodal neurological assessment of patients with hypoglycemic encephalopathy hospitalized in the intensive care unit and their neurological outcomes.Consecutive patients with disorders of consciousness related to hypoglycemia admitted for neuroprognostication from 2010 to 2020 were included. Multimodal neurological assessment included electroencephalography, somatosensory and cognitive event-related potentials, and morphological and quantitative magnetic resonance imaging (MRI) with quantification of fractional anisotropy. Neurological outcomes at 28 days, 3 months, 6 months, 1 year, and 2 years after hypoglycemia were retrieved.Twenty patients were included. After 2 years, 75% of patients had died, 5% remained in a permanent vegetative state, 10% were in a minimally conscious state, and 10% were conscious but with severe disabilities (Glasgow Outcome Scale-Extended scores 3 and 4). All patients showed pathologic electroencephalography findings with heterogenous patterns. Morphological brain MRI revealed abnormalities in 95% of patients, with various localizations including cortical atrophy in 65% of patients. When performed, quantitative MRI showed decreased fractional anisotropy affecting widespread white matter tracts in all patients.The overall prognosis of patients with severe hypoglycemic encephalopathy was poor, with only a small fraction of patients who slowly improved after intensive care unit discharge. Of note, patients who did not improve during the first 6 months did not recover consciousness. This study suggests that a multimodal approach capitalizing on advanced brain imaging and bedside electrophysiology techniques could improve diagnostic and prognostic performance in severe hypoglycemic encephalopathy.

Mind-wandering, a widespread mental phenomenon in which attention shifts from an ongoing task, varies in intentionality. Recent research highlights the importance of differentiating between intentional and unintentional mind-wandering, as the latter is uniquely linked to adverse outcomes such as psychopathologies. In this study, we explored the electrophysiological underpinnings of these distinct forms of mindwandering using a robust feature extraction tool adapted from research on neural signatures of consciousness. We conducted univariate and multivariate pattern analyses on 54 EEG markers obtained from recordings immediately before participants provided multidimensional reports of their thoughts during a sustained attention task. Our findings revealed distinct electrophysiological signatures for on-task, intentional, and unintentional mind-wandering states, particularly within the low-frequency spectrum. Specifically, normalized theta power demonstrated the highest discriminative power for discerning on- and off-task states, while alpha band features and theta permutation entropy were uniquely associated with intentional versus unintentional mind-wandering. These results challenge the prevailing notion that increased alpha band activity is a generic marker of mind-wandering and suggest that unique brain activity patterns underlie the various forms of mind-wandering. Our study lays the groundwork for developing reliable, real-time detection systems for identifying mind-wandering using EEG machine learning models in both clinical and practical settings.

The quest to decode the complex supraspinal mechanisms that integrate cutaneous thermal information in the central system is still ongoing. The dorsal horn of the spinal cord is the first hub that encodes thermal input which is then transmitted to brain regions via the spinothalamic and thalamo-cortical pathways. So far, our knowledge about the strength of the interplay between the brain regions during thermal processing is limited. To address this question, we imaged the brains of awake and freely-moving mice using Functional Ultrasound imaging during plantar exposure to constant and varying temperatures. Our study, a synchronous large field investigation of mice brains reveals for the first time the brain states and the specific dynamic interplay between key regions involved in thermal processing. Our study reveals: i) a dichotomy in the response of the somato-motor-cingulate cortices and the hypothalamus, which was never described before, due to the lack of appropriate tools to study such regions with both good spatial and temporal resolutions. ii) We infer that cingulate areas may be involved in the affective responses to temperature changes. iii) Colder temperatures (ramped down) reinforces the disconnection between the somato-motor-cingulate and hypothalamus networks. iv) Finally, we also confirm the existence in the mouse brain of a dynamic brain mode characterized by low cognitive strength, described previously only in non-human primates and humans. The present study points towards the existence of a common hub between somato-motor and cingulate regions, whereas hypothalamus functions are related to a secondary network.

Brain states are frequently represented using a unidimensional scale measuring the richness of subjective experience (level of consciousness). This description assumes a mapping between the high-dimensional space of whole-brain configurations and the trajectories of brain states associated with changes in consciousness, yet this mapping and its properties remain unknown. We combined whole-brain modelling, data augmentation and deep learning for dimensionality reduction to determine a mapping representing states of consciousness in a low-dimensional space, where distances parallel similarities between states. An orderly trajectory from wakefulness to brain injured patients is revealed in a latent space whose coordinates represent metrics related to functional modularity and structure-function coupling, both increasing alongside loss of consciousness. Finally, we investigated the effects of model perturbations, providing geometrical interpretation for the stability and reversibility of states. We conclude that conscious awareness depends on functional patterns encoded as a low-dimensional trajectory within the vast space of brain configurations.

Sleep has long been considered as a state of disconnection from the environment, with absent reactivity to external stimuli. Here, we questioned this sleep disconnection dogma by directly investigating behavioral responsiveness in 49 napping subjects (27 with narcolepsy and 22 healthy volunteers) engaged in a lexical decision task. Participants were instructed to frown or smile depending on the stimulus type (words vs pseudo-words). We found accurate behavioral responses, visible via contractions of the corrugator or zygomatic muscles, in all sleep stages in both groups (except slow-wave sleep for healthy volunteers). Stimuli presented during states with high (vs. low) values of neural markers indexing rich cognitive states more often yielded responses. Our findings suggest that transient windows of reactivity to external stimuli exist in all sleep stages, even in healthy individuals. Such windows of reactivity could be used to probe sleep-related mental and cognitive processes in real-time across all sleep stages.