Type 1 narcolepsy (NT1) involves the loss of hypocretin/orexin transmission, causing daytime sleepiness and abnormal mixing of REM sleep with wakefulness, leading to cataplexy, sleep paralysis, and dream-like hallucinations. Using deep learning of nocturnal sleep polysomnography signals (EEG, EMG, EOG), the study found that NT1 patients show abnormally short wake-to-REM transitions and mixing of wake, N1, and REM sleep stages. This mixing fluctuated across cortical locations, strongest in frontal and central regions, particularly the left hemisphere. The strongest discriminator was N1-REM mixing across central electrodes, with 4.3-fold higher dissociation in NT1 patients (Cohen’s d = 0.61). Local dissociations correlated with CSF orexin/hypocretin levels and MSLT severity. Hypnagogic hallucinations correlated with occipital dissociations, aligning with visual content. Orexin deficiency likely destabilizes REM sleep organization across cortical areas.
Parasomnias, including disorders of arousal and REM sleep behavior disorder, are increasingly diagnosed using home devices such as actigraphy, EEG headbands, and 2D infrared or 3D time-of-flight cameras with automatic analysis. Traditional video-polysomnographic criteria are becoming more accurate, and deep learning methods classify abnormal polysomnographic signals. Big data from clinical, cognitive, brain imaging, DNA, and polysomnography collections reveal factors associated with parasomnias and, for RBD, may predict individual risk of conversion to overt neurodegenerative disease. Dream engineering, targeted memory reactivation, image repetition therapy, and lucid dreaming help alleviate nightmares. RBD has united movement disorder and sleep neurologists; research into nightmares and sleep-wake dissociations has brought together sleep and consciousness scientists.