Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans.

STUDY OBJECTIVES: Given the established racial disparities in both sleep health and dementia risk for African American populations, we assess cross-sectional and longitudinal associations of self-report sleep duration (SRSD) and daytime sleepiness with plasma amyloid beta (Aß) and cognition in an African American (AA) cohort. METHODS: In a cognitively unimpaired sample drawn from the African Americans Fighting Alzheimer's in Midlife (AA-FAiM) study, data on SRSD, Epworth Sleepiness Scale, demographics, and cognitive performance were analyzed. Aß40, Aß42, and the Aß42/40 ratio were quantified from plasma samples. Cross-sectional analyses explored associations between baseline predictors and outcome measures. Linear mixed-effect regression models estimated associations of SRSD and daytime sleepiness with plasma Aß and cognitive performance levels and change over time. RESULTS: One hundred and forty-seven participants comprised the cross-sectional sample. Baseline age was 63.2 ±â€…8.51 years. 69.6% self-identified as female. SRSD was 6.4 ±â€…1.1 hours and 22.4% reported excessive daytime sleepiness. The longitudinal dataset included 57 participants. In fully adjusted models, neither SRSD nor daytime sleepiness is associated with cross-sectional or longitudinal Aß. Associations with level and trajectory of cognitive test performance varied by measure of sleep health. CONCLUSIONS: SRSD was below National Sleep Foundation recommendations and daytime sleepiness was prevalent in this cohort. In the absence of observed associations with plasma Aß, poorer self-reported sleep health broadly predicted poorer cognitive function but not accelerated decline. Future research is necessary to understand and address modifiable sleep mechanisms as they relate to cognitive aging in AA at disproportionate risk for dementia. CLINICAL TRIAL INFORMATION: Not applicable.

Sleep Health, Individual Characteristics, Lifestyle Factors, and Marathon Completion Time in Marathon Runners: A Retrospective Investigation of the 2016 London Marathon.

Despite sleep health being critically important for athlete performance and well-being, sleep health in marathoners is understudied. This foundational study explored relations between sleep health, individual characteristics, lifestyle factors, and marathon completion time. Data were obtained from the 2016 London Marathon participants. Participants completed the Athlete Sleep Screening Questionnaire (ASSQ) along with a brief survey capturing individual characteristics and lifestyle factors. Sleep health focused on the ASSQ sleep difficulty score (SDS) and its components. Linear regression computed relations among sleep, individual, lifestyle, and marathon variables. The analytic sample (N = 943) was mostly male (64.5%) and young adults (66.5%). A total of 23.5% of the sample reported sleep difficulties (SDS ≥ 8) at a severity warranting follow-up with a trained sleep provider. Middle-aged adults generally reported significantly worse sleep health characteristics, relative to young adults, except young adults reported significantly longer sleep onset latency (SOL). Sleep tracker users reported worse sleep satisfaction. Pre-bedtime electronic device use was associated with longer SOL and longer marathon completion time, while increasing SOL was also associated with longer marathon completion. Our results suggest a deleterious influence of pre-bedtime electronic device use and sleep tracker use on sleep health in marathoners. Orthosomnia may be a relevant factor in the relationship between sleep tracking and sleep health for marathoners.

Sleep and Performance in Professional Athletes.

Purpose of Review: Sleep is an essential human behavior that plays a key role in proper biopsychosocial development as well as short- and long-term biological, physical, psychological, and cognitive health. Sleep plays a key role in athletic performance, influencing an athlete's ability to train, recover, and perform, as well as their overall wellness. Over the recent decade, the awareness of sleep's import has penetrated just about every professional sport domain. The purpose of the review was to identify and synthesize the literature published within the past 5 years (2018-2022) that relates to sleep and performance in professional athletes. Literature related to nonprofessional, high-level athletes (e.g., collegiate; Olympic) was omitted as well as those associated with non-traditional professional sports (e.g., eSports). Recent Findings: Results from 38 articles were incorporated into this review, which covered (1) the sleep's role in the training, physical injury prevention and recovery, competitive performance, and mental health of professional athletes, (2) common sleep problems and disorders in professional athletes, and (3) the impact of unique challenges from training, travel, competition, and other factors on sleep health. Additionally, we provide an orientation to utilized strategies and interventions to assist with sleep health in professional athletes, as well as conclude with a commentary on critical steps forward. Summary: Sleep plays a critically important role in the training, recovery, performance, and overall wellness of professional athletes. Professional athletes are vulnerable to a variety of sleep-related problems and disorders, due to unique factors related to training, travel, and competition, among other factors. Improved, standardized research methodology and partnerships between professional athletes, coaches, teams, and organizations and researchers are necessary to advance the knowledge of sleep and performance in professional athletes, including identifying sport-specific differences and variation across individual characteristics, as well as developing individualizable, dynamic, and appropriate interventions for improving sleep health among professional athletes.

Associations between time zone changes, travel distance and performance: A retrospective analysis of 2013-2020 National Hockey League Data.

OBJECTIVES: Many studies have investigated the role that travel plays in athletic performance. However, these studies lacked a holistic representation of travel. For instance, they do not consider travel distance and uniquely focuses on travel direction. DESIGN: An open source (www.evolving-hockey.com) provided NHL (2013-2020) game data. In total, this resulted in 17,088 regular season games. METHODS: Linear and quadratic versions of time zone change (TZΔ) and adjusted jet lag (AJL) were formulated. TZΔ captured circadian delay/advance based on travel for a game, with each TZ going eastward and westward reflected by -1 and +1, respectively. AJL advances TZΔ by allowing TZ acclimation, with each day resulting in a 1-unit change towards circadian neutral. AJL is a season-long rolling summation, which was computed using two different travel approaches: Approach A (AJL_A) assumes travel the day before each game, whereas Approach B (AJL_B) was designed to prioritize being home. A standardized flight tracker determined travel distance for each game. Team ability differences, characterized as difference in total season points, served as an analytic covariate. Outcome variables included goal differential, difference between actual and expected Fenwick save percentage (dFSv%), and goals saved above average (GSAA). RESULTS: GameDistance (ß = -0.14, p = 0.0007), AJL_B2 (ß = -0.15, p = 0.0006), and their interaction (p = 0.0004) associated with GoalDifferential. GameDistance (ß = -0.18, p = 0.02) and AJL_B2 (ß = 0.12, p = 0.03) associated with dFSv%, whereas only AJL_B2 (ß = 0.03, p = 0.05) associated with GSAA. CONCLUSIONS: Results suggest that circadian change, in both direction, and greater traveled distance can negatively impact NHL athletes.

Associations of circadian change, travel distance, and their interaction with basketball performance: a retrospective analysis of 2014-2018 National Basketball Association data.

This investigation aimed to clarify the influence of circadian change and travel distance on National Basketball Association (NBA) team performance using a dataset from the 2014-2018 seasons. Data from 9,840 games were acquired from an open-access source. Game point differential and team free-throw percentage served as outcome variables. Time zone change (TZΔ) captured raw circadian delay/advance based on travel for a game and adjusted TZΔ (AdjTZΔ) evolved TZΔ by allowing acclimation to a novel TZ. We also further categorized AdjTZΔ into AdjTZΔ_A, which assumed travel the day before each game and AdjTZΔ_B, which assumed teams spent as many days in their home city as possible. Travel distance for each game was calculated. Linear mixed-effects modeling estimated associations, with games nested within team and year. Adjusted associations accounted for differences in team ability, whether the game was home or away, and whether the game occurred on the second half of a back-to-back game sequence. Greater circadian misalignment, regardless of delay or advance, and increasing travel distance negatively influenced NBA game performance. Yet, results suggest that performance outcomes may be more influenced by travel distance than circadian misalignment. Moreover, circadian misalignment and travel distance interacted to significantly influence game point differential. Furthermore, differences in results across analyses were observed between AdjTZΔ_A and AdjTZΔ_B, which suggests that subtle differences in constructed travel schedules can have notable impact on NBA performance outcomes. Lastly, playing on the second half of a back-to-back sequence emerged as a robust predictor of performance disadvantage, which corroborates the existing literature and provides further support for NBA schedule changes purposed to enhance competitive equity by reducing the number of back-to-back games across a season. These findings can help guide NBA teams on key strategies for reducing travel-related disadvantages and inform schedule makers on critical factors to prioritize across future schedules to attenuate competitive inequity from travel. Furthermore, they can help direct teams towards scenarios that are best to target for load management purposes due to the cumulative disadvantage arising from travel-related factors, opponent quality, game location, and game sequence.

PAX8/PAX8-AS1 DNA methylation levels are associated with objective sleep duration in persons with unexplained hypersomnolence using a deep phenotyping approach.

STUDY OBJECTIVES: Patients with unexplained hypersomnolence have significant impairment related to daytime sleepiness and excessive sleep duration, the biological bases of which are poorly understood. This investigation sought to examine relationships between objectively measured hypersomnolence phenotypes and epigenetic modification of candidate hypersomnolence genes to advance this line of inquiry. METHODS: Twenty-eight unmedicated clinical patients with unexplained hypersomnolence were evaluated using overnight ad libitum polysomnography, multiple sleep latency testing, infrared pupillometry, and the psychomotor vigilance task. DNA methylation levels on CpG sites annotated to 11 a priori hypersomnolence candidate genes were assessed for statistical association with hypersomnolence measures using independent regression models with adjusted local index of significance (aLIS) P-value threshold of 0.05. RESULTS: Nine CpG sites exhibited significant associations between DNA methylation levels and total sleep time measured using ad libitum polysomnography (aLIS p-value < .05). All nine differentially methylated CpG sites were annotated to the paired box 8 (PAX8) gene and its related antisense gene (PAX8-AS1). Among these nine differentially methylated positions was a cluster of five CpG sites located in the body of the PAX8 gene and promoter of PAX8-AS1. CONCLUSIONS: This study demonstrates that PAX8/PAX8-AS1 DNA methylation levels are associated with total sleep time in persons with unexplained hypersomnolence. Given prior investigations that have implicated single nucleotide polymorphisms in PAX8/PAX8-AS1 with habitual sleep duration, further research that clarifies the role of DNA methylation levels on these genes in the phenotypic expression of total sleep time is warranted.

Multimodal assessment increases objective identification of hypersomnolence in patients referred for multiple sleep latency testing.

STUDY OBJECTIVES: The multiple sleep latency test (MSLT) has limitations when evaluating disorders of hypersomnolence with unknown etiology. Alternative measures of hypersomnolence may objectively identify pathology in patients with complaints of daytime sleepiness that may not be captured by the MSLT alone. This study evaluated the impact of a multimodal hypersomnolence assessment relative to MSLT in patients with unexplained hypersomnolence. METHODS: Seventy-five patients with unexplained hypersomnolence were included in the analyzed sample. Polysomnography was performed without prescribed wake time, and the psychomotor vigilance task and pupillographic sleepiness test were completed between MSLT nap opportunities. Presence or absence of hypersomnolence for each assessment was defined using a priori cutpoints. Proportions of patients identified as hypersomnolent using the multimodal assessment relative to MSLT alone were evaluated, as well as the sensitivity and specificity of ancillary hypersomnolence measures relative to MSLT as a gold standard. RESULTS: The multimodal assessment more than doubled the proportion of patients identified as having objective deficits relative to MSLT ≤ 8 minutes alone. The combination of excessive sleep duration, lapses on the psychomotor vigilance task, and impairments on the pupillographic sleepiness test also had perfect sensitivity in identifying all patients identified as sleepy by the MSLT across 3 different MSLT cutpoints (5, 8, and 10 minutes). CONCLUSIONS: These data demonstrate the insufficiency of the MSLT as a singular tool to identify objective pathology in persons with unexplained hypersomnolence. Further efforts to refine and standardize multimodal assessments will likely improve diagnostic acumen and research into the causes of these disorders.

Development and validation of the Hypersomnia Severity Index (HSI): A measure to assess hypersomnia severity and impairment in psychiatric disorders.

Hypersomnia is common in psychiatric disorders, yet there are few self-report measures that adequately characterize this sleep disturbance. The objective of this study was to validate the Hypersomnia Severity Index (HSI), a tool designed to measure severity, distress and impairment of hypersomnia in psychiatric populations. Psychometric properties were evaluated in an undergraduate Scale Development sample (N = 381) and two psychiatric Scale Validation samples: euthymic bipolar participants with a range of sleep complaints (N = 89), and unmedicated unipolar depressed participants (N = 21) meeting operational criteria for hypersomnolence disorder. Exploratory factor analysis and confirmatory factor analysis in the Scale Development and Validation samples, respectively, suggested a two-factor structure representing Hypersomnia Symptoms and Distress/Impairment best fit the data. Convergent validity was established by significant associations with the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), and the Sheehan Disability Scale in both samples. Construct validity was further supported by significant correlations between the Scale Validation sample and two weeks of diary- and actigraphy-determined total sleep time and time in bed. A cutoff score of 10 maximally discriminated between those with hypersomnia and those without. The HSI shows promise as a measure of hypersomnia that is commonly seen in psychiatric disorders, and may be of use to both researchers and clinicians. SUPPORT: This work is supported by grants from the American Sleep Medicine Foundation (76-JF-12), the Brain and Behavior Research Foundation (19193), and NIMHK23MH099234 (DTP); National Science Foundation Graduate Research Fellowship Program and Stanford Child Health Research Institute (KAK); and R34MH080958 and R01MH105513 (AGH).

Optimizing Actigraphic Estimation of Sleep Duration in Suspected Idiopathic Hypersomnia.

STUDY OBJECTIVES: To determine the optimal Actiwatch 2 setting configuration for the estimation of total sleep time (TST) in persons with suspected idiopathic hypersomnia. METHODS: Thirty-three patients with a diagnosis of idiopathic hypersomnia (28 female; mean age = 33.7 ± 10.5) underwent ad libitum polysomnography with concurrent use of the Actiwatch 2. Actiwatch 2 sleep-wake activity threshold (SWAT; Low, Medium, and High) and sleep immobility onset and offset (SIOO; 5, 10, 15, 20, 25, and 30 epoch) duration were modified during data processing. The resultant 18 unique setting combinations were subsequently evaluated using Bland-Altman and epoch comparison analyses to determine optimal settings relative to polysomnography. RESULTS: Low SWAT + 25 Epoch SIOO displayed the least divergence from polysomnography (mean difference 3.4 minutes). Higher SWAT and lower SIOO increased sensitivity and accuracy, but at the expense of reducing specificity and the ability to accurately estimate TST. CONCLUSIONS: These results demonstrate that actigraphic settings should be carefully considered when estimating sleep duration. The Low + 25 Epoch configuration is indicated as most optimal for estimating TST in persons with suspected idiopathic hypersomnia. COMMENTARY: A commentary on this article appears in this issue on page 539.

Establishing the objective sleep phenotype in hypersomnolence disorder with and without comorbid major depression.

STUDY OBJECTIVES: To clarify whether hypersomnolence disorder is associated with a specific sleep phenotype and altered neurophysiological function in persons with and without hypersomnolence disorder and major depressive disorder (MDD). METHODS: Eighty-three unmedicated persons with and without hypersomnolence disorder and/or MDD underwent ad libitum high-density EEG polysomnography. Clinical and sleep architecture variables were compared between groups. Topographic patterns of slow-wave activity (SWA) relative to healthy controls were compared, with correlations between topographic SWA and daytime sleepiness assessed. Reductions in SWA in hypersomnolence disorder were mapped to specific cortical areas using source localization. RESULTS: Regardless of the presence or absence of comorbid MDD, persons with hypersomnolence disorder had increased sleep duration relative to both controls and persons with MDD without hypersomnolence. Participants with hypersomnolence disorder also demonstrated reduced bilateral centroparietal low-frequency activity during nonrapid eye movement sleep relative to controls, a pattern not observed in persons with MDD but without hypersomnolence. SWA in these regions was negatively correlated with subjective measures of daytime sleepiness. Source localization demonstrated reductions in SWA in the supramarginal gyrus, somatosensory, and transverse temporal cortex in participants with hypersomnolence disorder. CONCLUSIONS: Hypersomnolence disorder is characterized by increased sleep duration with normal sleep continuity, regardless of the presence or absence of comorbid depression. Reduced local SWA may be a specific neurophysiological finding in hypersomnolence disorder. Further research is warranted to elucidate the mechanisms through which these cortical changes are related to clinical complaints of daytime sleepiness.

Utility of the Compensatory Tracking Task for Objective Differentiation of Hypersomnolence in Depression: A High-Density EEG Investigation.

Hypersomnolence is a common and debilitating symptom in mood disorders. However, objective differentiation of excessive daytime sleepiness (EDS) from non-EDS in depression has not yet been achieved. This study compared performance on the Compensatory Tracking Task (CTT) and concurrently-recorded high-density (hd)EEG theta power in 22 patients with major depressive disorder (MDD) and co-occurring EDS against 22 age- and sex-matched patients with MDD but no EDS, as well as 22 age- and sex-matched healthy controls. Though depressed hypersomnolent participants endorsed feeling sleepier than depressed non-hypersomnolent and healthy control participants prior to starting the CTT, no group differences in CTT performance were observed. Average hdEEG theta power was higher during periods of high error on the CTT compared to periods of low error, but did not differ between the groups. Though the CTT still holds promise as an objective neurobehavioral measure, these results do not indicate a capability to differentiate EDS from non-EDS in mood disorders.

Ability of the Fitbit Alta HR to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: A comparison against polysomnography.

Measuring sleep duration and early onset rapid eye movement sleep (REMS) is critical in the assessment of suspected central disorders of hypersomnolence (CDH). Current multi-sensor activity trackers that integrate accelerometry and heart rate are purported to accurately quantify sleep time and REMS; however, their utility in suspected CDH has not been established. This investigation aimed to determine the ability of a current, multi-sensor tracker, Fitbit Alta HR (FBA-HR), to quantify and classify sleep in patients with suspected CDH relative to polysomnography (PSG). Forty-nine patients (46 female; mean age, 30.3 ± 9.84 years) underwent ad libitum PSG with concurrent use of the FBA-HR. FBA-HR sleep variable quantification was assessed using Bland-Altman analysis. FBA-HR all sleep (AS), light sleep (LS; PSG N1 + N2), deep sleep (DS; PSG N3) and REMS classification was evaluated using epoch-by-epoch comparisons. FBA-HR-detected sleep-onset rapid eye movement periods (SOREMPs) were compared against PSG SOMREMPs. FBA-HR displayed significant overestimation of total sleep time (11.6 min), sleep efficiency (1.98%) and duration of deep sleep (18.2 min). FBA-HR sensitivity and specificity were as follows: AS, 0.96, 0.58; LS, 0.73, 0.72;DS, 0.67, 0.92; REMS, 0.74, 0.93. The device failed to detect any nocturnal SOREMPs. Device performance did not differ appreciably among diagnostic subgroups. These results suggest FBA-HR cannot replace EEG-based measurements of sleep and wake in the diagnostic assessment of suspected CDH, and that improvements in device performance are required prior to adoption in clinical or research settings.

Ability of the Multisensory Jawbone UP3 to Quantify and Classify Sleep in Patients With Suspected Central Disorders of Hypersomnolence: A Comparison Against Polysomnography and Actigraphy.

STUDY OBJECTIVES: To evaluate the ability of a multisensory fitness tracker, the Jawbone UP3 (JB3), to quantify and classify sleep in patients with suspected central disorders of hypersomnolence. METHODS: This study included 43 patients who completed polysomnography (PSG) and a Multiple Sleep Latency Test (MSLT) with concurrent wrist-worn JB3 and Actiwatch 2 (AW2) recordings for comparison. Mean differences in nocturnal sleep architecture variables were compared using Bland-Altman analysis. Sensitivity, specificity, and accuracy were derived for both devices relative to PSG. Ability of the JB3 to detect sleep onset rapid eye movement periods (SOREMPs) during MSLT naps was also quantified. RESULTS: JB3 demonstrated a significant overestimation of total sleep time (39.6 min, P < .0001) relative to PSG, but performed comparably to AW2. Although the ability of the JB3 to detect epochs of sleep was relatively good (sensitivity = 0.97), its ability to distinguish light, deep, and REM sleep was poor. Similarly, the JB3 did not correctly identify a single SOREMP during any MSLT nap opportunity. CONCLUSIONS: The JB3 did not accurately quantify or classify sleep in patients with suspected central disorders of hypersomnolence, and was particularly poor at identifying REM sleep. Thus, this device cannot be used as a surrogate for PSG or MSLT in the assessment of patients with suspected central disorders of hypersomnolence.

Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: A comparison against polysomnography and wrist-worn actigraphy.

BACKGROUND: Sleep disturbance is a common and important component of affective illness. Fitness activity trackers are emerging as alternative means to estimate sleep in psychiatric patients; however, their ability to quantify sleep in mood disorders has not been empirically evaluated. Thus, this study sought to evaluate the utility of the Fitbit Flex (FBF) to estimate sleep in patients with major depressive disorder (MDD) relative to gold standard polysomnography (PSG) and a widely-used actigraph (Actiwatch-2; AW-2). METHODS: Twenty-one patients with unipolar MDD wore the FBF and AW-2 during in-laboratory PSG. Bland-Altman analysis compared sleep variables among devices. Epoch-by-epoch analysis further evaluated sensitivity, specificity, and accuracy for the FBF and AW-2 relative to PSG. RESULTS: The FBF demonstrated significant limitations in quantifying sleep and wake, relative to PSG. In the normal setting, the FBF significantly overestimated sleep time and efficiency, and displayed poor ability to correctly identify wake epochs (i.e. low specificity). In the sensitive setting, the FBF significantly underestimated sleep time and efficiency relative to PSG. Performance characteristics of the FBF were more similar to the AW-2 in the normal compared to sensitive setting. LIMITATIONS: Participants were young to middle aged and predominantly female, which may limit generalizability of findings. Study design also precluded ability to assess longitudinal performance of FBF. CONCLUSIONS: The FBF is not an adequate substitute for PSG when quantifying sleep in MDD, and the settings of the device sizably impact its performance relative to PSG and other standard actigraphs. The limitations and capabilities of the FBF should be carefully considered prior to clinical and research implementation.

Objective measures of sleep duration and continuity in major depressive disorder with comorbid hypersomnolence: a primary investigation with contiguous systematic review and meta-analysis.

Hypersomnolence plays an important role in the presentation, treatment and course of mood disorders. However, there has been relatively little research that examines objective measures of sleep duration and continuity in patients with depression and hypersomnolence, despite the use of these factors in sleep medicine nosological systems. This study compared total sleep time and efficiency measured by naturalistic actigraphic recordings followed by ad libitum polysomnography (PSG; without prescribed wake time) in 22 patients with major depressive disorder and co-occurring hypersomnolence against age- and sex-matched healthy sleeper controls. The major depressive disorder and co-occurring hypersomnolence group demonstrated significantly longer sleep duration compared with healthy sleeper controls quantified by sleep diaries, actigraphy and ad libitum PSG. No between-group differences in sleep efficiency (SE), latency to sleep or wake after sleep onset were observed when assessed using objective measures. To further contextualize these findings within the broader scientific literature, a systematic review was performed to identify other comparable investigations. A meta-analysis of pooled data demonstrated patients with mood disorders and co-occurring hypersomnolence have significantly greater sleep duration and similar SE compared with healthy controls when assessed using ad libitum PSG. These results suggest current sleep medicine nosology that distinguishes hypersomnia associated with psychiatric disorders primarily as a construct characterized by low SE and increased time in bed may not be accurate. Future studies that establish the biological bases hypersomnolence in mood disorders, as well as clarify the accuracy of nosological thresholds to define excessive sleep duration, are needed to refine the diagnosis and treatment of these disorders.

Effects of partial sleep deprivation on slow waves during non-rapid eye movement sleep: A high density EEG investigation.

OBJECTIVE: Changes in slow waves during non-rapid eye movement (NREM) sleep in response to acute total sleep deprivation are well-established measures of sleep homeostasis. This investigation utilized high-density electroencephalography (hdEEG) to examine topographic changes in slow waves during repeated partial sleep deprivation. METHODS: Twenty-four participants underwent a 6-day sleep restriction protocol. Spectral and period-amplitude analyses of sleep hdEEG data were used to examine changes in slow wave energy, count, amplitude, and slope relative to baseline. RESULTS: Changes in slow wave energy were dependent on the quantity of NREM sleep utilized for analysis, with widespread increases during sleep restriction and recovery when comparing data from the first portion of the sleep period, but restricted to recovery sleep if the entire sleep episode was considered. Period-amplitude analysis was less dependent on the quantity of NREM sleep utilized, and demonstrated topographic changes in the count, amplitude, and distribution of slow waves, with frontal increases in slow wave amplitude, numbers of high-amplitude waves, and amplitude/slopes of low amplitude waves resulting from partial sleep deprivation. CONCLUSIONS: Topographic changes in slow waves occur across the course of partial sleep restriction and recovery. SIGNIFICANCE: These results demonstrate a homeostatic response to partial sleep loss in humans.

The 5α-reductase inhibitor finasteride is not associated with alterations in sleep spindles in men referred for polysomnography.

OBJECTIVE: Endogenous neurosteroids that potentiate the gamma-aminobutyric acid type A (GABAA ) receptor are thought to enhance the generation of sleep spindles. This study tested the hypothesis that the 5α-reductase inhibitor finasteride, an agent associated with reductions in neurosteroids, would be associated with reduced sleep spindles in men referred for polysomnography. METHODS: Spectral analysis and spindle waveform detection were performed on electroencephalographic (EEG) sleep data in the 11-16 Hz sigma band, as well as several subranges, from 27 men taking finasteride and 27 matched comparison patients (ages 18 to 81 years). RESULTS: No significant differences between groups were observed for spectral power or sleep spindle morphology measures, including spindle density, amplitude, duration, and integrated spindle activity. CONCLUSIONS: Contrary to our hypothesis, these findings demonstrate that finasteride is not associated with alterations in sleep spindle range activity or spindle morphology parameters.