Elizabeth A. McDevitt

The critical role of sleep spindles in hippocampal-dependent memory: a pharmacology study

An important function of sleep is the consolidation of memories, and features of sleep, such as rapid eye movement (REM) or sleep spindles, have been shown to correlate with improvements in discrete memory domains. Because of the methodological difficulties in modulating sleep, however, a causal link between specific sleep features and human memory consolidation is lacking. Here, we experimentally manipulated specific sleep features during a daytime nap via direct pharmacological intervention. Using zolpidem (Ambien), a short-acting GABAA agonist hypnotic, we show increased sleep spindle density and decreased REM sleep compared with placebo and sodium oxybate (Xyrem). Naps with increased spindles produced significantly better verbal memory and significantly worse perceptual learning but did not affect motor learning. The experimental spindles were similar to control spindles in amplitude and frequency, suggesting that the experimental intervention enhanced normal sleep processes. Furthermore, using statistical methods, we demonstrate for the first time a critical role of spindles in human hippocampal memory performance. The gains in memory consolidation exceed sleep-alone or control conditions and demonstrate the potential for targeted, exceptional memory enhancement in healthy adults with pharmacologically modified sleep.

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)

Personality and Healthy Sleep: The Importance of Conscientiousness and Neuroticism

Although previous research has shown personality and sleep are each substantial predictors of health throughout the lifespan, little is known about links between personality and healthy sleep patterns. This study examined Big Five personality traits and a range of factors related to sleep health in 436 university students (M age = 19.88, SD = 1.50, 50% Male). Valid self-report measures of personality, chronotype, sleep hygiene, sleep quality, and sleepiness were analyzed. To remove multicollinearity between personality factors, each sleep domain was regressed on relevant demographic and principal component-derived personality factors in multiple linear regressions. Results showed that low conscientiousness and high neuroticism were the best predictors of poor sleep (poor sleep hygiene, low sleep quality, and increased sleepiness), consistent with other research on predictors of poor health and mortality risk. In this first comprehensive study of the topic, the findings suggest that personality has a significant association with sleep health, and researchers could profitably examine both personality and sleep in models of health and well-being.

The role of sleep and practice in implicit and explicit motor learning

Sleep is hypothesized to play a functional role in the consolidation of memory, with more robust findings for implicit, than explicit memory. Previous studies have observed improvements on an explicit motor task after a sleep period. We examined the role of massed practice and sleep on implicit and explicit learning within a motor task. Controlling for non-sleep factors (e.g. massed practice, circadian confounds) eliminated both explicit and implicit learning effects that have been attributed to sleep.

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.

The effect of nap frequency on daytime sleep architecture

It is well documented that the quality and quantity of prior sleep influence future sleep. For instance, nocturnal sleep restriction leads to an increase in slow wave sleep (SWS) (i.e. SWS rebound) during a subsequent sleep period. However, few studies have examined how prior napping affects daytime sleep architecture. Because daytime naps are recommended for management of disrupted sleep, understanding the impact of napping on subsequent sleep may be important. We monitored sleep-wake patterns for one week with actigraphy followed by a 75-minute polysomnographically-recorded nap. We found that greater nap frequency was correlated with increased Stage 1 and decreased SWS. We categorized subjects based on nap frequency during the prior week (0 nap, 1 to 2 naps, and 3 to 4 naps) and found differences in Stage 1, Stage 2, and SWS between groups. Subjects who took no naps had the greatest amount of SWS, those who took 1 to 2 naps had the most Stage 2 sleep, and those who took 3 to 4 naps had the most Stage 1. While correlations were not found between nap frequency and nocturnal sleep measures, frequent napping was associated with increased subjective sleepiness. Therefore, frequent napping appears to be associated with lighter daytime sleep and increased sleepiness during the day. Speculatively, low levels of daytime sleepiness and increased SWS in non-nappers may help explain why these individuals choose not to nap.

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.

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.

Sex differences in sleep-dependent perceptual learning

Sex differences in learning and memory suggest differences between men and women in mechanisms of neural plasticity. Such differences have been reported in a variety of explicit memory tasks, but implicit memory has not been studied in this context. We investigated differences between men and women in offline consolidation of perceptual learning (PL) of motion direction discrimination. Initially, discrimination thresholds were measured for two opposite directions of motion, followed by approximately 40 minutes of training on one of the directions. During a post-training consolidation period, subjects either took a nap or remained awake. Thresholds were then reassessed for both directions of motion. We found that rapid eye movement (REM) sleep facilitates consolidation of PL but that the pattern of specificity in the REM condition differed between men and women. PL for men whose naps contained REM sleep was highly specific to the trained direction of motion, whereas REM sleep in women resulted in generalized learning to the untrained direction as well as to a novel direction that was not previously tested. Moreover, for subjects in the REM condition, men exhibited greater PL than women for the trained direction. Our findings provide the first evidence of sex differences in the magnitude and specificity of PL and in the role of REM sleep in implicit learning. Our results have important implications for optimization of educational and training strategies designed for males and females.