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Rosenblum, Y.

Publications and source records attributed to Rosenblum, Y..

3 recordsLinked to original sources

Fractal cycles of sleep: a new aperiodic activity-based definition of sleep cycles

Nocturnal human sleep consists of 4 - 6 ninety-minute cycles defined as episodes of non-rapid eye movement (non-REM) sleep followed by an episode of REM sleep. While sleep cycles are considered fundamental components of sleep, their functional significance largely remains unclear. One of the reasons for a lack of research progress in this field is the absence of a data-driven definition of sleep cycles. Here, we proposed to base such a definition on fractal (aperiodic) neural activity, a well-established marker of arousal and sleep stages. We explored temporal dynamics of fractal activity during nocturnal sleep using electroencephalography. Based on the observed pattern of fractal fluctuations, we introduced a new concept of fractal activity-based cycles of sleep or "fractal cycles" for short, defined as a time interval during which fractal activity descends from its local maximum to its local minimum and then leads back to the next local maximum. Next, we assessed correlations between fractal and classical (i.e., non-REM - REM) sleep cycle durations. We also studied cycles with skipped REM sleep, i.e., the cycles where the REM phase is expected to appear except that it does not, being replaced by lightening of sleep. Regarding the sample, we examined fractal cycles in healthy adults (age range: 18 - 75 years, n = 205) as well as in children and adolescents (range: 8 - 17 years, n = 21), the group characterized by deeper sleep and a higher frequency of cycles with skipped REM sleep. Further, we studied fractal cycles in major depressive disorder (n = 111), the condition characterized by altered REM sleep (in addition to its clinical symptoms). We found that fractal and classical cycle durations (89 {+/-} 34 min vs 90 {+/-} 25 min) correlated positively (r = 0.5, p < 0.001). Cycle-to-cycle overnight dynamics showed an inverted U-shape of both fractal and classical cycle durations and a gradual decrease in absolute amplitudes of the fractal descents and ascents from early to late cycles. In adults, the fractal cycle duration and participants age correlated negatively (r = -0.2, p = 0.006). Children and adolescents had shorter fractal cycles compared to young adults (76 {+/-} 34 vs 94 {+/-} 32 min, p < 0.001). The fractal cycle algorithm detected cycles with skipped REM sleep in 91 - 98% of cases. Medicated patients with depression showed longer fractal cycles compared to their own unmedicated state (107 {+/-} 51 min vs 92 {+/-} 38 min, p < 0.001) and age-matched controls (104 {+/-} 49 vs 88 {+/-} 31 min, p < 0.001). In conclusion, fractal cycles are an objective, quantifiable, continuous and biologically plausible way to display sleep neural activity and its cycles. They are useful in healthy adult and pediatric populations as well as in patients with major depressive disorder. Fractal cycles should be extensively studied to advance theoretical research on sleep structure. Highlights- Fractal activity-based cycles of sleep or "fractal cycles" for short is a new concept based on cyclic changes in fractal (aperiodic) neural activity during sleep. - Durations of fractal and classical cycles correlate, and both show an inverted U-shape when seen from early to late cycles. - The fractal cycle algorithm is effective in detecting cycles with skipped REM sleep. - Older healthy adults shower shorter fractal - but not classical - cycle durations. - Fractal cycle duration is shorter in children and adolescents compared to young adults. - In major depressive disorder, antidepressant medication is associated with longer fractal cycles.

neuroscience↗

Sustained polyphasic sleep restriction abolishes human growth hormone release

Voluntary sleep restriction is a common phenomenon in industrialized societies aiming to increase time spent awake and thus productivity. We explored how restricting sleep to a radically polyphasic schedule affects neural, cognitive, and endocrine characteristics. Ten young healthy participants were restricted to one 30-min nap opportunity at the end of every 4 hours (i.e., 6 sleep episodes per 24 hours) without any extended core sleep window, which resulted in a cumulative sleep amount of just 2 hours per day (i.e., [~]20 min per bout). All but one participant terminated this schedule during the first three weeks. The remaining participant (a 25-year-old male) succeeded to adhere to a polyphasic schedule for 5 weeks with no apparent impairments in cognitive and psychiatric measures except for psychomotor vigilance. While in-blood cortisol or melatonin release pattern and amounts were unaltered by the polyphasic as compared to monophasic sleep, growth hormone seemed almost entirely abolished (>95% decrease), with the residual release showing a considerably changed polyphasic secretional pattern. While coarse sleep structure appeared intact during polyphasic sleep, REM sleep showed decreased oscillatory and increased aperiodic EEG activity compared to monophasic sleep. Considering the decreased vigilance, abolished growth hormone release, and neurophysiological changes observed, it is doubtful that radically polyphasic sleep schedules can subserve the different functions of sleep to a sufficient degree.

neuroscience↗

Divergent associations of slow-wave sleep vs. REM sleep with plasma amyloid-beta

BackgroundRecent evidence shows that during slow-wave sleep (SWS), the brain is cleared from potentially toxic metabolites, such as the amyloid-beta protein. Poor sleep or elevated cortisol levels can worsen amyloid-beta clearance, potentially leading to the formation of amyloid plaques, a neuropathological hallmark of Alzheimers disease. Here, we explore how nocturnal neural and endocrine activity affects amyloid-beta fluctuations in the peripheral blood as a reflection of cerebral clearance. MethodsSimultaneous polysomnography and all-night blood sampling were acquired in 60 healthy volunteers aged 20-68 years old. Nocturnal plasma concentrations of two amyloid-beta species (amyloid-beta-40 and amyloid-beta-42), cortisol, and growth hormone were assessed every 20 minutes from 23:00-7:00. Amyloid-beta fluctuations were modeled with sleep stages, (non)-oscillatory power, and hormones as predictors while controlling for age and multiple comparisons. Time lags between the predictors and amyloid-beta ranged from 20 to 120min. FindingsThe amyloid-beta-40 and amyloid-beta-42 levels correlated positively with growth hormone concentrations, SWS proportion, slow-wave (0.3-4Hz) oscillatory and high-band (30-48Hz) non-oscillatory power, but negatively with cortisol concentrations and rapid eye movement sleep (REM) proportion measured 40-100min before (all t-values>|3|, p-values<0.003). Older participants showed higher amyloid-beta-40 levels. InterpretationSlow-wave oscillations are associated with higher plasma amyloid-beta levels, reflecting their contribution to cerebral amyloid-beta clearance across the blood-brain barrier. REM sleep is related to decreased amyloid-beta plasma levels; however, this link may reflect passive aftereffects of SWS and not REMs effects per se. Strong associations between cortisol, growth hormone, and amyloid-beta presumably reflect the sleep-regulating role of the corresponding releasing hormones. A positive association between age and amyloid-beta-40 may indicate that peripheral clearance becomes less efficient with age. Our study provides important insights into the specificity of different sleep features effects on brain clearance and suggests that cortisol nocturnal fluctuations may serve as a new marker of clearance efficiency.

neuroscience↗