Sara C. Mednick

Direct comparison of two actigraphy devices with polysomnographically recorded naps in healthy young adults.

The last 20 yrs have seen a marked increase in studies utilizing actigraphy in free-living environments. The aim of the present study is to directly compare two commercially available actigraph devices with concurrent polysomnography (PSG) during a daytime nap in healthy young adults. Thirty healthy young adults, ages 18–31 (mean 20.77 yrs, SD 3.14 yrs) simultaneously wore AW-64 and GT3X+ devices during a polysomnographically recorded nap. Mann-Whitney U (M-U) test, intraclass correlation coefficients, and Bland-Altman statistic were used to compare total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE) between the two actigraphs and PSG. Epoch-by-epoch (EBE) agreement was calculated to determine accuracy, sensitivity, specificity, predictive values for sleep (PVS) and wake (PVW), and kappa and prevalence- and bias-adjusted kappa (PABAK) coefficients. All frequency settings provided by the devices were examined. For both actigraphs, EBE analysis found accuracy, sensitivity, specificity, PVS, and PVW comparable to previous reports of other similar devices. Kappa and PABAK coefficients showed moderate to high agreement with PSG depending on device settings. The GT3X+ overestimated TST and SE, and underestimated SOL and WASO, whereas no significant difference was found between AW-64 and PSG. However, GT3X+ showed overall better EBE agreements to PSG than AW-64. We conclude that both actigraphs are valid and reliable devices for detecting sleep/wake diurnal patterns. The choice between devices should be based on several parameters as reliability, cost of the device, scoring algorithm, target population, experimental condition, and aims of the study (e.g., sleep and/or physical activity). (Author correspondence: smednick@ucr.edu)

Pharmacologically increasing sleep spindles enhances recognition for negative and high-arousal memories

Sleep affects declarative memory for emotional stimuli differently than it affects declarative memory for nonemotional stimuli. However, the interaction between specific sleep characteristics and emotional memory is not well understood. Recent studies on how sleep affects emotional memory have focused on rapid eye movement sleep (REM) but have not addressed non-REM sleep, particularly sleep spindles. This is despite the fact that sleep spindles are implicated in declarative memory as well as neural models of memory consolidation (e.g., hippocampal neural replay). Additionally, many studies examine a limited range of emotional stimuli and fail to disentangle differences in memory performance because of variance in valence and arousal. Here, we experimentally increase non-REM sleep features, sleep spindle density, and SWS, with pharmacological interventions using zolpidem (Ambien) and sodium oxybate (Xyrem) during daytime naps. We use a full spread of emotional stimuli to test all levels of valence and arousal. We find that increasing sleep spindle density increases memory discrimination (da) for highly arousing and negative stimuli without altering measures of bias (ca). These results indicate a broader role for sleep in the processing of emotional stimuli with differing effects based on arousal and valence, and they raise the possibility that sleep spindles causally facilitate emotional memory consolidation. These findings are discussed in terms of the known use of hypnotics in individuals with emotional mood disorders.

Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5–1.0Hz) and thalamic spindles (12–15Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

REM sleep rescues learning from interference.

Classical human memory studies investigating the acquisition of temporally-linked events have found that the memories for two events will interfere with each other and cause forgetting (i.e., interference; Wixted, 2004). Importantly, sleep helps consolidate memories and protect them from subsequent interference (Ellenbogen, Hulbert, Stickgold, Dinges, & Thompson-Schill, 2006). We asked whether sleep can also repair memories that have already been damaged by interference. Using a perceptual learning paradigm, we induced interference either before or after a consolidation period. We varied brain states during consolidation by comparing active wake, quiet wake, and naps with either non-rapid eye movement sleep (NREM), or both NREM and REM sleep. When interference occurred after consolidation, sleep and wake both produced learning. However, interference prior to consolidation impaired memory, with retroactive interference showing more disruption than proactive interference. Sleep rescued learning damaged by interference. Critically, only naps that contained REM sleep were able to rescue learning that was highly disrupted by retroactive interference. Furthermore, the magnitude of rescued learning was correlated with the amount of REM sleep. We demonstrate the first evidence of a process by which the brain can rescue and consolidate memories damaged by interference, and that this process requires REM sleep. We explain these results within a theoretical model that considers how interference during encoding interacts with consolidation processes to predict which memories are retained or lost.

Nocturnal Continuous Glucose and Sleep Stage Data in Adults with Type 1 Diabetes in Real-World Conditions

Background: Sleep plays an important role in health, and poor sleep is associated with negative impacts on diabetes management, but few studies have objectively evaluated sleep in adults with type 1 diabetes mellitus (T1DM). Nocturnal glycemia and sleep characteristics in T1DM were evaluated using body-worn sensors in real-world conditions. Methods: Analyses were performed on data collected by the Diabetes Management Integrated Technology Research Initiative pilot study of 17 T1DM subjects: 10 male, 7 female; age 19–61 years; T1DM duration 14.9 ± 11.0 years; hemoglobin A1c (HbA1c) 7.3% ± 1.3% (mean ± standard deviation). Each subject was equipped with a continuous glucose monitor and a wireless sleep monitor (WSM) for four nights. Sleep stages [rapid eye movement (REM), light, and deep sleep] were continuously recorded by the WSM. Nocturnal glycemia (mg/dl) was evaluated as hypoglycemia (<50 mg/dl), low (50–69 mg/dl), euglycemia (70–120 mg/dl), high (121–250 mg/dl), and hyperglycemia (>250 mg/dl) and by several indices of glycemic variability. Glycemia was analyzed within each sleep stage. Results: Subjects slept 358 ± 48 min per night, with 85 ± 27 min in REM sleep, 207 ± 42 min in light sleep, and 66 ± 30 min in deep sleep (mean ±standard deviation). Increased time in deep sleep was associated with lower HbA1c (R2 = 0.42; F = 9.37; p < .01). Nocturnal glycemia varied widely between and within subjects. Glycemia during REM sleep was hypoglycemia 5.5% ± 18.1%, low 6.6% ± 18.5%, euglycemia 44.6% ± 39.5%, high 37.9% ± 39.7%, and hyperglycemia 5.5% ± 21.2%; glycemia during light sleep was hypoglycemia 4.8% ± 12.4%, low 7.3% ± 12.9%, euglycemia 42.1% ± 33.7%, high 39.2% ± 34.6%, and hyperglycemia 6.5% ± 20.5%; and glycemia during deep sleep was hypoglycemia 0.5% ± 2.2%, low 5.8% ± 14.3%, euglycemia 48.0% ± 37.5%, high 39.5% ± 37.6%, and hyperglycemia 6.2% ± 19.5%. Significantly less time was spent in the hypoglycemic range during deep sleep compared with light sleep (p = .02). Conclusions: Increased time in deep sleep was associated with lower HbA1c, and less hypoglycemia occurred in deep sleep in T1DM, though this must be further evaluated in larger subsequent studies. Furthermore, the consumer-grade WSM device was useful for objectively studying sleep in a real-world setting.

Free-living cross-comparison of two wearable monitors for sleep and physical activity in healthy young adults

There is a growing need for free-living monitoring of the full 24 h spectrum of behaviors with a single or integrated set of sensors. The validity of field standard wearable monitors in sleep and physical activity have yet to be assessed for the complementary behavior in the context of 24 h continuous monitoring. We conducted a free-living comparison study of the Actigraph GT3X+ (GT3X+) to assess sleep parameters as compared with the Actiwatch-64 (AW-64) and concurrently, the AW-64 to assess sedentary and physical activity behaviors as compared with the GT3X+. Thirty young adults (15 female, 19.2±0.86 years) wore both monitors for 3 consecutive days and 2 consecutive nights. Agreement of sleep, sedentary, and physical activity metrics were evaluated using analyses of variance, intraclass correlation coefficients, Bland-Altman plots with associated confidence limits, mean absolute percentage of errors and equivalence tests. For sleep, the GT3X+ showed high agreement for total sleep time and sleep efficiency, but underestimated wakefulness after sleep onset and sleep onset latency relative to the AW-64. For sedentary behavior and physical activity, the AW-64 showed a moderate agreement for activity energy expenditure, but not for sedentary, light or moderate-vigorous physical activities relative to the GT3X+. Overall our results showed good agreement of the GT3X+ with AW-64 for assessing sleep but a lack of agreement between AW-64 and GT3X+ for physical activity and sedentary behaviors. These results are likely due to the monitor placement (wrist vs hip), as well as the algorithm employed to score the data. Future validation work of existing and emerging technologies that may hold promise for 24 h continuous monitoring is needed.

Nighttime temperature and human sleep loss in a changing climate

Analysis of reported sleep difficulties indicates that increases in nighttime temperatures reduce human sleep quality. Human sleep is highly regulated by temperature. Might climate change—through increases in nighttime heat—disrupt sleep in the future? We conduct the inaugural investigation of the relationship between climatic anomalies, reports of insufficient sleep, and projected climate change. Using data from 765,000 U.S. survey respondents from 2002 to 2011, coupled with nighttime temperature data, we show that increases in nighttime temperatures amplify self-reported nights of insufficient sleep. We observe the largest effects during the summer and among both lower-income and elderly respondents. We combine our historical estimates with climate model projections and detail the potential sleep impacts of future climatic changes. Our study represents the largest ever investigation of the relationship between sleep and ambient temperature and provides the first evidence that climate change may disrupt human sleep.

Autonomic activity during sleep predicts memory consolidation in humans

Significance We present the first evidence, to our knowledge, that the autonomic nervous system (ANS) plays a role in associative memory consolidation during sleep. Compared with a Quiet Wake control condition, performance improvement was associated with vagally mediated ANS activity [as measured by high-frequency (HF) heart rate variability (HRV)] during rapid eye movement (REM) sleep. In particular, up to 73% of the proportion of improvement in associative memory performance could be accounted for by considering both traditionally reported sleep features (i.e., minutes spent in sleep stages and sleep spindles) and HF HRV. We hypothesize that central nervous system processes that favor peripheral vagal activity during REM sleep may lead to increases in plasticity that promote associative processing. Throughout history, psychologists and philosophers have proposed that good sleep benefits memory, yet current studies focusing on the relationship between traditionally reported sleep features (e.g., minutes in sleep stages) and changes in memory performance show contradictory findings. This discrepancy suggests that there are events occurring during sleep that have not yet been considered. The autonomic nervous system (ANS) shows strong variation across sleep stages. Also, increases in ANS activity during waking, as measured by heart rate variability (HRV), have been correlated with memory improvement. However, the role of ANS in sleep-dependent memory consolidation has never been examined. Here, we examined whether changes in cardiac ANS activity (HRV) during a daytime nap were related to performance on two memory conditions (Primed and Repeated) and a nonmemory control condition on the Remote Associates Test. In line with prior studies, we found sleep-dependent improvement in the Primed condition compared with the Quiet Wake control condition. Using regression analyses, we compared the proportion of variance in performance associated with traditionally reported sleep features (model 1) vs. sleep features and HRV during sleep (model 2). For both the Primed and Repeated conditions, model 2 (sleep + HRV) predicted performance significantly better (73% and 58% of variance explained, respectively) compared with model 1 (sleep only, 46% and 26% of variance explained, respectively). These findings present the first evidence, to our knowledge, that ANS activity may be one potential mechanism driving sleep-dependent plasticity.

Same-Sex Sexual Attraction Does Not Spread in Adolescent Social Networks

Peers have a powerful effect on adolescents’ beliefs, attitudes, and behaviors. Here, we examine the role of social networks in the spread of attitudes towards sexuality using data from the National Longitudinal Study of Adolescent Health (Add Health). Although we found evidence that both sexual activity (ORxa0=xa01.79) and desire to have a romantic relationship (ORxa0=xa02.69) may spread from person to person, attraction to same sex partners did not spread (ORxa0=xa00.96). Analyses of comparable power to those that suggest positive and significant peer-to-peer influence in sexual behavior fail to demonstrate a significant relationship on sexual attraction between friends or siblings. These results suggest that peer influence has little or no effect on the tendency toward heterosexual or homosexual attraction in teens, and that sexual orientation is not transmitted via social networks.

Heart rate variability during daytime naps in healthy adults: Autonomic profile and short-term reliability.

In healthy individuals, a reduction in cardiovascular output and a shift to parasympathetic/vagal dominant activity is observed across nocturnal sleep. This cardiac autonomic profile, often measured by heart rate variability (HRV), has been associated with significant benefits for the cardiovascular system. However, little is known about the autonomic profile during daytime sleep. Here, we investigated the autonomic profile and short-term reliability of HRV during daytime naps in 66 healthy young adults. Participants took an 80-120 min polysomnographically recorded nap at 1:30 pm. Beat-by-beat RR interval values (RR), high (HF) and low frequency (LF) power, total power (TP), HF normalized units (HF(nu)), and the LF/HF ratio were obtained for 5 min during presleep wakefulness and during nap sleep stages (N2, N3, REM). A subsample of 37 participants took two additional naps with 2 weeks between recordings. We observed lengthening of the RR, higher HF and HF(nu), and lower LF/HF during NREM, compared with REM and wake, and a marked reduction of LF and TP during N3. Intraclass correlation coefficients highlighted a short-term stability of RR and HF ranging across sleep stages between 0.52-0.76 and 0.52-0.80, respectively. Our results suggest that daytime napping in healthy young adults is associated with dynamic changes in the autonomic profile, similar to those seen during nocturnal sleep. Moreover, a reliable intraindividual measure of autonomic cardiac activity can be obtained by just a single daytime nap depending on specific parameters and recording purposes. Nap methodology may be a new and promising tool to explore sleep-dependent, autonomic fluctuations in healthy and at-risk populations.