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Introduction Insufficient sleep is pervasive in U.S. Navy (USN) sailors and has been associated with increased risk of injury and mood disturbances. As such, monitoring sleep and identifying modifiable targets that influence sleep in this population is essential. We examined the sleep of USN sailors during 9-months in port and explored the influence of different lifestyle behaviors on sleep. Methods Sailors (n = 101, 31 ± 7 years old [mean ± SD], 21% female) wore a commercial wearable sleep-tracking device (Oura Ring, Gen2) during a 9-month home port maintenance period (September 2021 – May 2022). During the study, the sailors slept at home and had periods working on the ship (on-hull; higher demands) and off the ship (off-hull; lower demands). Participants also completed 5 self-report surveys that assessed sleep quality (Pittsburgh Sleep Quality Index; PSQI) and multiple lifestyle behaviors including: hours of natural light exposure, hours of moderate/vigorous physical activity, and intake of caffeine, nicotine, and alcohol. Sleep outcome measures from the wearable device included total sleep time (TST), standard deviation of TST (SD TST), and sleep efficiency (SE). Linear mixed models were used to examine the effects of lifestyle behaviors on sleep. Timepoint and on/off-hull condition were also included as fixed effects, while participant was included as a random effect. Results Participants slept 6.5 ± 0.7 hours a night (6.2 ± 0.9 on-hull; 6.4 ± 0.8 off-hull; p > .05) and had slightly elevated PSQI scores that were higher on-hull (8.3 ± 4.6) than off-hull (6.5 ± 3.5; B = 1.83, Std. Error = 0.71, p = .01). Lifestyle behaviors were not significant predictors of PSQI, TST, SD TST, or SE (p > .05). Conclusion Lifestyle behaviors had weak relationships with self-reported and objective sleep outcomes in this exploratory analysis. Therefore, modifying lifestyle behaviors may not significantly influence sleep in USN sailors during home port periods. Still, additional behavioral targets (e.g., diet), specific aspects of behavioral outcomes (e.g., light exposure timing, exercise intensity), and other work-related factors (e.g., workload, schedule) that can affect sleep should be explored in future efforts. Support (if any) Military Operational Medicine Research Program (work unit no. N2010).

Study Objectives Sleep spindles are waxing and waning EEG waves exemplifying the main fast oscillatory activity occurring during NREM sleep. Several recent studies have established that sleep spindle abnormalities are present in schizophrenia spectrum disorders, including in early-course and first-episode patients, and those spindle deficits are associated with some of the cognitive impairments commonly observed in these patients. Cognitive deficits are often observed before the onset of psychosis and seem to predict poor functional outcomes in individuals at clinical high-risk for psychosis (CHR). Yet, the presence of spindle abnormalities and their relationship with cognitive dysfunction has not been investigated in CHR. Methods In this study, overnight high-density (hd)-EEG recordings were collected in 24 CHR and 24 healthy control (HC) subjects. Spindle density, duration, amplitude, and frequency were computed and compared between CHR and HC. Furthermore, WM was assessed for both HC and CHR, and its relationship with spindle parameters was examined. Results CHR had reduced spindle duration in centro-parietal and prefrontal regions, with the largest decrease in the right prefrontal area. Moderation analysis showed that the relation between spindle duration and spindle frequency was altered in CHR relative to HC. Furthermore, CHR had reduced WM performance compared to HC, which was predicted by spindle frequency, whereas in HC spindle frequency, duration, and density all predicted working memory performance. Conclusion Altogether, these findings indicate that sleep spindles are altered in CHR individuals, and spindle alterations are associated with their cognitive deficits, thus representing a sleep-specific putative neurophysiological biomarker of cognitive dysfunction in psychosis risk.

Introduction Despite exposure to operational stressors (e.g., sleep loss, caloric restriction), military personnel must maintain different aspects of neurobehavioral function (i.e., subjective alertness, behavioral alertness, perception-action coupling) to operate safely within military environments. It is unclear whether perception-action coupling, which refers to the ability to ‘read and react’ to ever-changing circumstances, reflects a distinct aspect of neurobehavioral resilience from subjective and behavioral alertness. Further, prior sleep may enhance resilience during subsequent exposure to operational stressors. Therefore, we examined resilience across different neurobehavioral tasks during exposure to simulated military operational stress (SMOS) and examined differences in baseline sleep between resilient and vulnerable participants. Methods Forty-nine military personnel (11 females, 26.6 ± 5.8 years) completed a 5-day SMOS protocol that included two days of sleep restriction and disruption (sleep opportunities: 01:00-03:00 and 05:00-07:00) accompanied by caloric restriction (50% caloric need). Participants completed tasks of subjective alertness (Profile of Mood States Vigor subscale, POMS), behavioral alertness (Psychomotor Vigilance Task) and perception-action coupling (Perception-Action Coupling Task) at baseline and at 04:00 across the two nights of sleep disruption. For each neurobehavioral outcome, a two-step decision-making process defined resilient and vulnerable participants: resilient participants demonstrated high alertness/performance during sleep disruption and minimal change from baseline during sleep disruption. Kappa coefficients were calculated to determine agreement in resilience classification across different neurobehavioral outcomes. Further, differences between resilient and vulnerable participants in baseline sleep questionnaires (Pittsburgh Sleep Quality Index; Epworth Sleepiness Scale) and polysomnography (sleep efficiency; sleep fragmentation; and slow wave activity, SWA) were examined with independent t-tests. Results Classification of participants as resilient or vulnerable differed across neurobehavioral outcomes, as indicated by kappa values Conclusion Subjective alertness, behavioral alertness, and perception-action coupling reflect distinct aspects of neurobehavioral resilience, highlighting the importance of understanding the operational relevance of different neurobehavioral measures when assessing fatigue risk. Further, more baseline SWA, indicating higher baseline sleep need, may reflect vulnerability to SMOS and subsequent sleep loss. Support (If Any) Department of Defense Award #W81XWH-17-2-0070

Introduction Alertness, essential for optimal performance, may be modulated by acute stressors including: sleep loss, caloric restriction, cognitive load, and physical exertion. Prior sleep may attenuate sleep loss-related alertness decrements, thereby influencing performance and safety. We examined the effects of prior sleep and changes in alertness throughout the day and across days during a simulated military operational stress (SMOS) protocol. Methods As part of a 5-day SMOS protocol, fifty-eight active-duty or recently-separated military personnel (45 men; 26±6 years) completed subjective (Profile of Mood States, Vigor subscale) and objective (3-minute Psychomotor Vigilance Task; PVT) alertness assessments each morning (~0900) and evening (~2200). PVT outcomes included median reaction time (RT) and lapses. Day 2 (D2) reflected baseline testing, in which participants received an 8-hour sleep opportunity (2300-0700) and 100% of their estimated caloric need. Day 4 (D4) reflected peak stress, after two nights of participants receiving two 2-hour sleep opportunities (0100-0300, 0500-0700) and 50% of their estimated caloric need. Mixed effects ANOVAs were used to assess the effects of day (D2, D4) and time (Morning, Evening) on alertness. D2 and D4 reflected alertness at baseline and peak stress, respectively. Separate ANOVAs were performed to assess the effects of prior sleep: the Pittsburgh Sleep Quality Index (PSQI) assessed at intake, baseline polysomnography-measured sleep efficiency (SE), and baseline frontal slow wave activity (SWA; 0.5-4Hz). All analyses controlled for age. Results No significant interaction or main effects of day and time were found for Vigor or PVT lapses. Participants with higher PSQI scores reported lower Vigor (p=.01, η_p^2=.11). A significant interaction was found for PVT RT (p=.04, η_p^2=.07); morning RT was slower on D4 than D2, while evening RT did not differ across days. SE and SWA did not significantly influence alertness. Conclusion SMOS led to objective alertness deficits in the morning but not evening. Subjective alertness did not change during SMOS but was influenced by prior sleep quality (PSQI). Thus, both circadian and prior sleep-related factors influence performance during operational stress. Fatigue mitigation strategies delivered before and during military operations may support performance and safety. Support (if any) Department of Defense Award #W81XWH-17-2-0070

Introduction Individuals with post-traumatic stress disorder (PTSD) experience altered sleep and daytime function, including deficits in working memory (WM), the ability to store and manipulate information over short timeframes. As sleep contributes to WM, understanding how sleep parameters influence changes in WM may provide insight into potential intervention targets to improve or restore daytime function. Here, we investigated the relationship between sleep and WM improvement in Veterans with and without PTSD. Methods Forty-eight post-911 Veterans without PTSD (Control) and 37 with PTSD (PTSD) completed a 48-hour lab stay during which WM was assessed using a n-back task. Nighttime polysomnography, using high-density (64-channels) electroencephalography, quantified time spent in non-REM and REM sleep and log-transformed spectral activity for non-REM sleep in delta (.5-4Hz), theta (4-8Hz), alpha (8-12Hz), sigma (12-16Hz), and beta (16-32Hz) bands. Pearson’s correlations were used to assess associations between baseline sleep and baseline WM on 1-back trials. Within control and PTSD groups, independent samples t-tests were used to compare changes in sleep across nights between improvers and non-improvers categorized by 1-back accuracy changes across days. Results Proportions of improvers and non-improvers were similar between groups (χ 2 = .023, p = .880). Within either group, baseline sleep did not relate to baseline WM and changes in time spent in each sleep stage did not differ between improvers and non-improvers. Within the control group, improvers (n = 15; 3.67 ± 3.56) had a greater increase (t = -2.826, p = .007) in delta activity than non-improvers (n = 33; .77 ± 3.20), but this relationship was not observed in the PTSD group (11 improvers, 26 non-improvers). Conclusion Increased delta activity related to improved WM in the Control but not PTSD group. This suggests individuals with PTSD do not improve WM through non-REM sleep but that it may be a useful intervention target. Support USAMRMC MOMRP PT-130572 (PI: Reifman)

Introduction The ability to adapt actions to perceptions of environmental constraints, perception-action coupling, may be compromised by military operational stress (caloric restriction, sleep disruption, physical exertion). Differences in sleep may influence susceptibility to these stressors. We investigated perception-action coupling during simulated military operational stress and the influence of sleep on perception-action coupling. Methods During a 5-day simulated military operational stress protocol, thirty-six (6 female) service members (25.8 ± 4.7 years) completed three trials of a perception-action coupling task (PACT) in the evening after a night of baseline sleep (BASE), two nights of sleep restriction (T1) and a night of recovery sleep (T2). Participants had 8-hr for baseline and recovery sleep (2300-0700) and 4-hr disturbed sleep on sleep restriction nights (0100-0300 and 0500-0700). Polysomnography was used to determine time spent in different sleep stages: stage 2 (N2), slow wave (SWS) and rapid-eye movement (REM). The tablet-based PACT requires participants make quick, accurate perceptual judgments and responses about the ability of virtual balls to fit through virtual apertures. Linear mixed models were used to assess interaction and main effects of study day and prior sleep on PACT response time (RT) and accuracy (ACC). Results No significant sleep x time interactions or significant main effect of time were found for RT or ACC. A significant main effect of SWS was found for RT (F1,88.307 = 4.331, p = .04). Higher SWS was related to lower (faster) RT. No significant main effects of other sleep stages were found. Conclusion Perception-action coupling was maintained during simulated military operational stress. Participants with more SWS across the study responded faster during the PACT but N2 and REM sleep did not relate to perception-action coupling performance, suggesting a specific effect of SWS on perception-action coupling abilities and behaviors. Support Department of Defense Award #W81XWH-17-2-0070 (PI: Nindl)