scholarly journals Neonatal Sleep Restriction Increases Nociceptive Sensitivity in Adolescent Mice

2018 ◽  
Vol 1 (21;1) ◽  
pp. E137-E148
Author(s):  
Monica L Andersen
Keyword(s):  
Sleep Deprivation ◽  
Neuronal Activity ◽  
Periaqueductal Gray ◽  
Sleep Loss ◽  
Brain Maturation ◽  
Sleep Restriction ◽  
Nociceptive Response ◽  
Structural Development ◽  
Nociceptive Sensitivity ◽  
Neonatal Mice

Background: Sleep loss in infants may have a negative effect on the functional and structural development of the nociceptive system. We tested the hypothesis that neonatal sleep restriction induces a long-term increase of pain-related behaviors in mice and that this hypersensitivity occurs due to changes in the neuronal activity of nociceptive pathways. Objectives: We aim to investigate the effects of sleep loss in neonatal mice on pain behaviors of adolescent and adult mice in a sex-dependent manner. We also analyzed neuroanatomical and functional changes in pain pathways associated with behavioral changes. Study Design: An experimental animal study. Setting: A basic sleep research laboratory at Universidade Federal de São Paulo in Brazil. Methods: Neonatal mice at postnatal day (PND) 12 were randomly assigned to either control (CTRL), maternal separation (MS), or sleep restriction (SR) groups. MS and SR were performed 2 hours a day for 10 days (PND 12 until PND 21). The gentle handling method was used to prevent sleep. At PND 21, PND 35, or PND 90, the mice were tested for pain-related behaviors. Their brains were harvested and immunohistochemically stained for c-Fos protein in the anterior cingulate cortex, primary somatosensory cortex, and periaqueductal gray (PAG). Results: Neonatal SR significantly increased nociceptive sensitivity in the hot plate test in adolescent mice (-23.5% of pain threshold). This alteration in nociceptive response was accompanied by a decrease in c-Fos expression in PAG (-40% of c-Fos positive cells compared to the CTRL group). The hypersensitivity found in adolescent mice was not present in adult animals, and all mice showed a comparable nociceptive response. Limitations: Even using a mild manipulation method, in which a minimal amount of handling was applied to maintain wakefulness, sleep deprivation was a stressful event evidenced by higher corticosterone levels. Conclusion: Repeated exposures to sleep loss during early life were able to induce changes in the nociceptive response associated with alterations in neural activity in descending control of pain. Key words: Brain maturation, hypersensitivity, neuronal activity, nociception, pain, periaqueductal gray, postnatal development, sleep, sleep deprivation

scholarly journals Residual, differential neurobehavioral deficits linger after multiple recovery nights following chronic sleep restriction or acute total sleep deprivation

SLEEP ◽  
2020 ◽  
Author(s):  
Erika M Yamazaki ◽  
Caroline A Antler ◽  
Charlotte R Lasek ◽  
Namni Goel
Keyword(s):  
Sleep Deprivation ◽  
Response Speed ◽  
Sleep Loss ◽  
Sleep Restriction ◽  
Total Sleep Deprivation ◽  
Psychomotor Vigilance Test ◽  
Recovery Sleep ◽  
Time In Bed ◽  
Neurobehavioral Deficits ◽  
Chronic Sleep

Abstract Study Objectives The amount of recovery sleep needed to fully restore well-established neurobehavioral deficits from sleep loss remains unknown, as does whether the recovery pattern differs across measures after total sleep deprivation (TSD) and chronic sleep restriction (SR). Methods In total, 83 adults received two baseline nights (10–12-hour time in bed [TIB]) followed by five 4-hour TIB SR nights or 36-hour TSD and four recovery nights (R1–R4; 12-hour TIB). Neurobehavioral tests were completed every 2 hours during wakefulness and a Maintenance of Wakefulness Test measured physiological sleepiness. Polysomnography was collected on B2, R1, and R4 nights. Results TSD and SR produced significant deficits in cognitive performance, increases in self-reported sleepiness and fatigue, decreases in vigor, and increases in physiological sleepiness. Neurobehavioral recovery from SR occurred after R1 and was maintained for all measures except Psychomotor Vigilance Test (PVT) lapses and response speed, which failed to completely recover. Neurobehavioral recovery from TSD occurred after R1 and was maintained for all cognitive and self-reported measures, except for vigor. After TSD and SR, R1 recovery sleep was longer and of higher efficiency and better quality than R4 recovery sleep. Conclusions PVT impairments from SR failed to reverse completely; by contrast, vigor did not recover after TSD; all other deficits were reversed after sleep loss. These results suggest that TSD and SR induce sustained, differential biological, physiological, and/or neural changes, which remarkably are not reversed with chronic, long-duration recovery sleep. Our findings have critical implications for the population at large and for military and health professionals.

137 Recovery Dynamics in a Biomathematical Model of Fatigue

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A56-A56
Author(s):  
Mark McCauley ◽  
Peter McCauley ◽  
Hans Van Dongen
Keyword(s):  
Sleep Deprivation ◽  
Goodness Of Fit ◽  
Sleep Loss ◽  
Sleep Restriction ◽  
Commercial Aviation ◽  
Circadian Misalignment ◽  
Total Sleep Deprivation ◽  
Homeostatic Process ◽  
Recovery Sleep

Abstract Introduction In commercial aviation and other operational settings where biomathematical models of fatigue are used for fatigue risk management, accurate prediction of recovery during rest periods following duty periods with sleep loss and/or circadian misalignment is critical. The recuperative potential of recovery sleep is influenced by a variety of factors, including long-term, allostatic effects of prior sleep/wake history. For example, recovery tends to be slower after sustained sleep restriction versus acute total sleep deprivation. Capturing such dynamics has proven to be challenging. Methods Here we focus on the dynamic biomathematical model of McCauley et al. (2013). In addition to a circadian process, this model features differential equations for sleep/wake regulation including a short-term sleep homeostatic process capturing change in the order of hours/days and a long-term allostatic process capturing change in the order of days/weeks. The allostatic process modulates the dynamics of the homeostatic process by shifting its equilibrium setpoint, which addresses recently observed phenomena such as reduced vulnerability to sleep loss after banking sleep. It also differentiates the build-up and recovery rates of fatigue under conditions of chronic sleep restriction versus acute total sleep deprivation; nonetheless, it does not accurately predict the disproportionately rapid recovery seen after total sleep deprivation. To improve the model, we hypothesized that the homeostatic process may also modulate the allostatic process, with the magnitude of this effect scaling as a function of time awake. Results To test our hypothesis, we added a parameter to the model to capture modulation by the homeostatic process of the allostatic process build-up during wakefulness and dissipation during sleep. Parameter estimation using previously published laboratory datasets of fatigue showed this parameter as significantly different from zero (p<0.05) and yielding a 10%–20% improvement in goodness-of-fit for recovery without adversely affecting goodness-of-fit for pre-recovery days. Conclusion Inclusion of a modulation effect of the allostatic process by the homeostatic process improved prediction accuracy in a variety of sleep loss and circadian misalignment scenarios. In addition to operational relevance for duty/rest scheduling, this finding has implications for understanding mechanisms underlying the homeostatic and allostatic processes of sleep/wake regulation. Support (if any) Federal Express Corporation

scholarly journals O039 Differential effects of sleep deprivation and sleep restriction on error awareness

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A17-A17
Author(s):  
J Boardman ◽  
M Bravo ◽  
T Andrillon ◽  
C Anderson ◽  
S Drummond
Keyword(s):  
Sleep Deprivation ◽  
Real Time ◽  
Error Rate ◽  
Sleep Loss ◽  
Healthy Adults ◽  
Sleep Restriction ◽  
Button Press ◽  
Safety Critical ◽  
Error Awareness ◽  
Occupational Settings

Abstract Introduction The ability to detect and subsequently correct errors is important in preventing the detrimental consequences of sleep loss. We report the first study to compare the effects of total sleep deprivation (TSD) and sleep restriction (SR) on error awareness. Methods Thirteen healthy adults (11F, age=26.8±3.4y) underwent a 34h TSD protocol, completing the Error Awareness Task (EAT: a combined Stroop/1-back/GoNogo task) at 4h and 27h post-wake. Twenty healthy adults (11F, age=27.4±5.3y) were studied both well-rested (WR: 9h sleep) and following SR (3 nights of 3h sleep), completing the EAT once/day (8-9h post-habitual wake). The EAT required participants to withhold responding to “nogo” stimuli and signal, via a button press, whenever they realised they made an error on these nogo trials. Results TSD did not significantly affect error rate (p=.712) or error awareness rate (p=.517), however, participants were slower to recognise errors after TSD (p=.004). In contrast, SR increased error rate (p<.001), decreased error awareness (p<.001), and slowed recognition of errors (p<.01). Discussion Three nights SR impaired the ability to recognise errors in real-time, despite a greater number of errors being made. Thus, impaired error awareness may be one mechanism underlying increased sleep loss-related accidents and errors in occupational settings, as well as at home. Interestingly, 1-night TSD did not lead to more, or impaired recognition of errors. TSD participants were slower to recognise errors, which may be problematic in safety critical settings. Technological and/or operational solutions may be needed to reduce the risk of errors going unrecognised.

scholarly journals The Effect of Sleep Deprivation and Restriction on Mood, Emotion, and Emotion Regulation: Three Meta-Analyses in One

SLEEP ◽  
2020 ◽  
Author(s):  
Cara C Tomaso ◽  
Anna B Johnson ◽  
Timothy D Nelson
Keyword(s):  
Emotion Regulation ◽  
Sleep Deprivation ◽  
Negative Mood ◽  
Sleep Loss ◽  
Sleep Restriction ◽  
Affective Functioning ◽  
Negative Effect ◽  
Regulation G ◽  
G 11 ◽  
Meta Analyses

Abstract Study objectives New theory and measurement approaches have facilitated nuanced investigation of how sleep loss impacts dimensions of affective functioning. To provide a quantitative summary of this literature, three conceptually related meta-analyses examined the effect of sleep restriction and sleep deprivation on mood, emotion, and emotion regulation across the lifespan (i.e., from early childhood to late adulthood). Method A total of 241 effect sizes from 64 studies were selected for inclusion, and multilevel meta-analytic techniques were used when applicable. Results There was a moderate, positive effect of sleep loss on negative mood (g = .45), which was stronger for studies with younger samples, as well as a large, negative effect of sleep loss on positive mood (g = -.93); type of sleep manipulation (i.e., restriction or deprivation) did not moderate either effect. After correcting for publication bias, a modest but significant negative effect emerged for the effect of sleep on emotion (g = .11); the valence of emotional stimuli did not change the direction of this effect, and type of sleep manipulation was also not a significant moderator. Finally, sleep restriction had a small, negative effect on adaptive emotion regulation (g = -.32), but no significant impact on maladaptive emotion regulation (g = .14); all studies on adaptive emotion regulation were conducted with youth samples. Conclusions Sleep loss compromises optimal affective functioning, though the magnitude of effects varies across components. Findings underscore the importance of sleep for healthy affective outcomes.

122 Different Duration Psychomotor Vigilance Tests Show Robust Stable Relationships Across Sleep Loss That Deteriorate in Recovery

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A50-A50
Author(s):  
Caroline Antler ◽  
Erika Yamazaki ◽  
Courtney Casale ◽  
Tess Brieva ◽  
Namni Goel
Keyword(s):  
Sleep Deprivation ◽  
Repeated Measures ◽  
Response Speed ◽  
Sleep Loss ◽  
Sleep Restriction ◽  
Psychomotor Vigilance Test ◽  
Time In Bed ◽  
Psychomotor Vigilance ◽  
The Relationship ◽  
Time Point

Abstract Introduction The Psychomotor Vigilance Test (PVT), a behavioral attention measure widely used to capture sleep loss deficits, is available in 10-minute (PVT10) and 3-minute (PVT3) versions. The PVT3 is a briefer and presumably comparable assessment to the more commonly used PVT10 yet the relationship between the measures from the two versions across specific time points and in recovery after sleep loss has not been investigated. Repeated measures correlation (rmcorr) evaluated within-individual associations between measures on the PVT10 and PVT3 throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (ages 21-49; mean±SD, 33.9±8.9y; 18 females) participated in a 13-night experiment consisting of 2 baseline nights (10h-12h time in bed, TIB) followed by 5 sleep restriction (SR1-5) nights (4h TIB), 4 recovery nights (R1-R4; 12h TIB), and 36h total sleep deprivation (TSD). A neurobehavioral test battery, including the PVT10 and PVT3 was completed every 2h during wakefulness. Rmcorr compared PVT10 and PVT3 lapses (reaction time [RT] >355ms [PVT3] or >500ms [PVT10]) and response speed (1/RT) by examining correlations by day (e.g., baseline day 2) and by time point (e.g., 1000h-2000h). Rmcorr ranges were as follows: 0.1-0.3, small; 0.3-0.5, moderate; 0.5-0.7, large; 0.7-0.9, very large. Results All time point correlations (1000h-2000h) were significant (moderate to large for lapses; large to very large for 1/RT). Lapses demonstrated large correlations during R1, moderate correlations during SR1-SR5 and TSD, and small correlations during R2 and R4, and showed no significant correlations during baseline or R3. 1/RT correlations were large for SR1-SR4 and TSD, moderate for SR5 and R1-R4, and small for baseline. Conclusion The various PVT relationships were consistently strong at specific times of day throughout the study. In addition, higher correlations observed for 1/RT relative to lapses and during SR and TSD relative to baseline and recovery suggest that the PVT10 and PVT3 are most similar and best follow performance when most individuals are experiencing behavioral attention deficits during sleep loss. Both measures track SR and TSD performance well, with 1/RT presenting as more comparable between the PVT10 and PVT3. Support (if any) ONR Award N00014-11-1-0361; NIH UL1TR000003; NASA NNX14AN49G and 80NSSC20K0243; NIHR01DK117488

121 Behavioral Attention Relationships Vary Between Demographic Groups Across Sleep Loss and Recovery

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A49-A50
Author(s):  
Caroline Antler ◽  
Erika Yamazaki ◽  
Tess Brieva ◽  
Courtney Casale ◽  
Namni Goel
Keyword(s):  
Sleep Deprivation ◽  
Repeated Measures ◽  
Age Groups ◽  
Response Speed ◽  
Sleep Loss ◽  
Demographic Groups ◽  
Time In Bed ◽  
Median Split ◽  
The Relationship ◽  
High Bmi

Abstract Introduction The Psychomotor Vigilance Test (PVT) is a behavioral attention measure widely used to describe sleep loss deficits. Although there are reported differences in PVT performance for various demographic groups, no study has examined the relationship between measures on the 10-minute PVT (PVT10) and the 3-minute PVT (PVT3) within sex, age, and body mass index (BMI) groups throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (mean±SD ages, 33.9±8.9y) participated in a 13-night experiment [2 baseline nights (10h-12h time in bed, TIB) followed by 5 sleep restriction (SR1-5) nights (4h TIB), 4 recovery nights (R1-R4; 12h TIB), and 36h total sleep deprivation (TSD)]. A neurobehavioral test battery, including the PVT10 and PVT3 was completed every 2h during wakefulness. Repeated measures correlation (rmcorr) compared PVT10 and PVT3 lapses (reaction time [RT] >355ms [PVT3] and >500ms [PVT10]) and response speed (1/RT) by examining correlations by day (e.g., baseline day 2) and time point (e.g., 1000h-2000h) within sex groups (18 females), within age groups defined by a median split (median=32, range=21-49y), and within BMI groups defined by a median split (median=25, range=17-31). Results PVT10 and PVT3 1/RT was significantly correlated at all study days and time points excluding at baseline for the younger group and at R2 for the higher BMI group. PVT10 and PVT3 lapses showed overall lower correlations across the study relative to 1/RT. Lapses were not significantly correlated at baseline for any group, for males across recovery (R1-R4), for the high BMI group at R2-R4, for the older group at R2-R3, or for the younger group at SR5 or R3. Conclusion Differentiating participants based on age, sex, or BMI revealed important variation in the relationship between PVT10 and PVT3 measures across the study. Surprisingly, lapses were not significantly correlated at baseline for any demographic group or across recovery for males or the high BMI or older group. Thus, PVT10 and PVT3 lapses may be less comparable in certain populations when well-rested. These findings add to a growing literature suggesting demographic factors may be important factors to consider when evaluating the effects of sleep loss. Support (if any) ONR Award N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243; NIHR01DK117488

293 Predictive utility of a brief scale to identify U.S. Army Soldiers who are genetically vulnerable and resilient to sleep loss

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A117-A117
Author(s):  
Janna Mantua ◽  
Carolyn Mickelson ◽  
Jacob Naylor ◽  
Bradley Ritland ◽  
Alexxa Bessey ◽  
...  
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Sleep Deprivation ◽  
Cognitive Performance ◽  
Response Inhibition ◽  
Sleep Loss ◽  
Cutoff Score ◽  
Cognitive Subscale ◽  
Army Soldiers ◽  
Psychomotor Vigilance

Abstract Introduction Sleep loss that is inherent to military operations can lead to cognitive errors and potential mission failure. Single Nucleotide Polymorphisms (SNPs) allele variations of several genes (COMT, ADORA2A, TNFa, CLOCK, DAT1) have been linked with inter-individual cognitive resilience to sleep loss through various mechanisms. U.S. Army Soldiers with resilience-related alleles may be better-suited to perform cognitively-arduous duties under conditions of sleep loss than those without these alleles. However, military-wide genetic screening is costly, arduous, and infeasible. This study tested whether a brief survey of subjective resilience to sleep loss (1) can demarcate soldiers with and without resilience-related alleles, and, if so, (2) can predict cognitive performance under conditions of sleep loss. Methods Six SNPs from the aforementioned genes were sequenced from 75 male U.S. Army special operations Soldiers (age 25.7±4.1). Psychomotor vigilance, response inhibition, and decision-making were tested after a night of mission-driven total sleep deprivation. The Iowa Resilience to Sleeplessness Test (iREST) Cognitive Subscale, which measures subjective cognitive resilience to sleep loss, was administered after a week of recovery sleep. A receiver operating characteristic (ROC) curve was used to determine whether the iREST Cognitive Subscale can discriminate between gene carriers, and a cutoff score was determined. Cognitive performance after sleep deprivation was compared between those below/above the cutoff score using t-tests or Mann-Whitney U tests. Results The iREST discriminated between allele variations for COMT (ROC=.65,SE=.07,p=.03), with an optimal cutoff score of 3.03 out of 5, with 90% sensitivity and 51.4% specificity. Soldiers below the cutoff score had significantly poorer for psychomotor vigilance reaction time (t=-2.39,p=.02), response inhibition errors of commission (U=155.00,W=246.00,p=.04), and decision-making reaction time (t=2.13,p=.04) than Soldiers above the cutoff score. Conclusion The iREST Cognitive Subscale can discriminate between those with and without specific vulnerability/resilience-related genotypes. If these findings are replicated, the iREST Cognitive Subscale could be used to help military leaders make decisions about proper personnel placement when sleep loss is unavoidable. This would likely result in increased safety and improved performance during military missions. Support (if any) Support for this study came from the Military Operational Medicine Research Program of the United States Army Medical Research and Development Command.

Hugin+ neurons provide a link between sleep homeostat and circadian clock neurons

2021 ◽  
Vol 118 (47) ◽  
pp. e2111183118
Author(s):  
Jessica E. Schwarz ◽  
Anna N. King ◽  
Cynthia T. Hsu ◽  
Annika F. Barber ◽  
Amita Sehgal
Keyword(s):  
Locomotor Activity ◽  
Sleep Deprivation ◽  
Circadian Clock ◽  
Sleep Loss ◽  
Daily Cycle ◽  
Shaped Body ◽  
Recovery Sleep ◽  
Sleep Homeostat ◽  
Central Clock ◽  
Homeostatic Mechanisms

Sleep is controlled by homeostatic mechanisms, which drive sleep after wakefulness, and a circadian clock, which confers the 24-h rhythm of sleep. These processes interact with each other to control the timing of sleep in a daily cycle as well as following sleep deprivation. However, the mechanisms by which they interact are poorly understood. We show here that hugin+ neurons, previously identified as neurons that function downstream of the clock to regulate rhythms of locomotor activity, are also targets of the sleep homeostat. Sleep deprivation decreases activity of hugin+ neurons, likely to suppress circadian-driven activity during recovery sleep, and ablation of hugin+ neurons promotes sleep increases generated by activation of the homeostatic sleep locus, the dorsal fan-shaped body (dFB). Also, mutations in peptides produced by the hugin+ locus increase recovery sleep following deprivation. Transsynaptic mapping reveals that hugin+ neurons feed back onto central clock neurons, which also show decreased activity upon sleep loss, in a Hugin peptide–dependent fashion. We propose that hugin+ neurons integrate circadian and sleep signals to modulate circadian circuitry and regulate the timing of sleep.

Sleep Deprivation Induces Neuroinflammation and Depressive-like Behaviors by Impairing the Regulation of Circadian Clock Genes Expression in Rats

2020 ◽  
Author(s):  
Chen Xing ◽  
Yanzhao Zhou ◽  
Huan Xu ◽  
Mengnan Ding ◽  
Yifan Zhang ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Circadian Clock ◽  
Glial Cell ◽  
Hpa Axis ◽  
Calcium Binding ◽  
Cell Activation ◽  
Clock Genes ◽  
Sleep Loss ◽  
Genes Expression ◽  
Circadian Clock Genes

Abstract Background: Sleep loss leads to a spectrum of mood disorders such as anxiety, cognitive dysfunction and motor coordination impairment in many individuals. However, the underlying mechanisms are largely unknown. Methods: In this study, we examined the effects of sleep deprivation (SD) on depression and the mechanism by subjecting rats to a slowly rotating platform for 3 days to mimic the process of sleep loss. Sleep-deprived animals were tested behaviorally for anxiety- and depressive-like behaviors. We further studied the effects of SD on hypothalamic-pituitary-adrenal (HPA) axis activity, and at the end of the experiment, brains were collected to measure the circadian clock genes expression in the hypothalamus, glial cell activation and inflammatory cytokine alterations. Results: Our results indicated that SD for 3 days resulted in anxiety- and depressive-like behaviors. SD exaggerated cortisol response to HPA axis, significantly altered the mRNA profile of circadian clock genes, and induced neuroinflammation by increasing the expression of glial cell markers, including the microglial marker ionized calcium-binding adapter molecule 1 (Iba1) and the astroglial marker glial fibrillary acidic protein (GFAP). The expression of M1 and M2 microglial markers (Arg-1 and CD206, respectively) and pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) were increased in the brain. Conclusion: These results indicated that SD for 3 days induced anxiety- and depression-like behaviors in rats by impairing the regulation of circadian clock genes and inducing neuroinflammation, ultimately resulting in brain injury.

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