Dynamics of Sleep Stage Transitions in Health and Disease

摘要

Sleep dynamics emerges from complex interactions between neuronal populations in many brain regions [1, 2, 3, 4, 5]. Annotated sleep stages from electroencephalography (EEG) recordings could potentially provide a non-invasive way to obtain valuable insights into the mechanisms of these interactions [6], and ultimately into the very nature of sleep regulation. However, to date, sleep stage analysis has been restricted, only very recently expanding the scope of the traditional descriptive statistics to more dynamical concepts of the duration of and transitions between vigilance states [7, 8, 9] and temporal evaluation of transition probabilities among different stages [10]. Physiological and/or pathological implications of the dynamics of sleep stage transitions have, to date, not been investigated. Here, we study detailed duration and transition statistics among sleep stages in healthy humans and patients with chronic fatigue syndrome [11], known to be associated with disturbed sleep [12]. We find that the durations of waking and non-REM sleep, in particular deep sleep (Stages III and IV), during the nighttime, follow a power-law probability distribution function, while REM sleep durations follow an exponential function, suggestive of complex underlying mechanisms governing the onset of light sleep. We also find a substantial number of REM to non-REM transitions in humans, while this transition is reported to be virtually non-existent in rats [7]. Interestingly, the probability of this REM to non-REM transition is significantly lower in the patients than in controls, resulting in a significantly greater REM to awake, together with Stage I to awake, transition probability. This might potentially account for the reported poor sleep quality in the patients [12] because the normal continuation of sleep after either the lightest or REM sleep is disrupted. We conclude that the dynamical transition analysis of sleep stages is useful for elucidating yet-to-be-determined human sleep regulation mechanisms with a pathophysiological implication.