Predicting the loss of responsiveness when falling asleep in humans

• Published in: NeuroImage (Orlando, Fla.) Vol. 251; p. 119003
• Main Authors: Strauss, Mélanie, Sitt, Jacobo D., Naccache, Lionel, Raimondo, Federico
• Format: Journal Article Web Resource
• Language: English
• Published: United States Elsevier Inc 01.05.2022; Elsevier Limited; Elsevier; Academic Press Inc
• Subjects: Acoustic Stimulation; Acoustic Stimulation - methods; Activity patterns; Auditory evoked potentials; Classification; Cognitive Neuroscience; Consciousness; Drowsiness; EEG; Electroencephalography; Electroencephalography - methods; External stimuli; Health care; Human health sciences; Humans; Life Sciences; MEG; Micro-sleep; N1 sleep; Neural networks; Neurology; Neurons and Cognition; Neurosciences & behavior; Neurosciences & comportement; P300; Physiology; Radiologie, médecine & imagerie nucléaire; Radiology, nuclear medicine & imaging; Sciences de la santé humaine; Sciences sociales & comportementales, psychologie; Sleep; Sleep - physiology; Sleep and wakefulness; Sleep onset; Sleep Stages; Sleep Stages - physiology; Social & behavioral sciences, psychology; Software; Vigilance; Wakefulness; Wakefulness - physiology; Drowsiness; N1 sleep; Micro-sleep; P300; MEG; Sleep onset
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2022.119003

Falling asleep is a dynamical process that is poorly defined. The period preceding sleep, characterized by the progressive alteration of behavioral responses to the environment, which may last several minutes, has no electrophysiological definition, and is embedded in the first stage of sleep (N1). We aimed at better characterizing this drowsiness period looking for neurophysiological predictors of responsiveness using electro and magneto-encephalography. Healthy participants were recorded when falling asleep, while they were presented with continuous auditory stimulations and asked to respond to deviant sounds. We analysed brain responses to sounds and markers of ongoing activity, such as information and connectivity measures, in relation to rapid fluctuations of brain rhythms observed at sleep onset and participants’ capabilities to respond. Results reveal a drowsiness period distinct from wakefulness and sleep, from alpha rhythms to the first sleep spindles, characterized by diverse and transient brain states that come on and off at the scale of a few seconds and closely reflects, mainly through neural processes in alpha and theta bands, decreasing probabilities to be responsive to external stimuli. Results also show that the global P300 was only present in responsive trials, regardless of vigilance states. A better consideration of the drowsiness period through a formalized classification and its specific brain markers such as described here should lead to significant advances in vigilance assessment in the future, in medicine and ecological environments.