Active Wakefulness Research Articles

Fetal ECG-based analysis reveals the impact of fetal movements and maternal respiration on maternal-fetal heart rate synchronization

Identifying and understanding prenatal developmental disorders at an early stage are crucial as fetal brain development has long-term effects on an individual’s life. The maturation of the fetal autonomic nervous system (ANS) is believed to influence the coordination and direction of maternal-fetal heartbeat synchronization. Fetal behavioral states (FBSes) include quiet sleep (1F), active sleep (2F), quiet awake (3F), and active awake (4F). In this study, the focus is on fetal movements, leading to the grouping of 1F and 3F into a quiet state, while 2F and 4F are combined to form an active state. Thus, the FBSes discussed in this article consist of fetal quiet and active states. Here, we explore the relationship between FBSes and the coupling of maternal and fetal heartbeats. We also seek to understand how maternal breathing patterns influence this coupling while considering FBSes. The study involved 105 healthy fetuses with gestational ages (GA) from 20 to 40 weeks. Non-invasive electrocardiogram (ECG) signals were recorded for 3 to 10 minutes. The ECG samples were separated into three gestational groups (Early: 16 ≤ GA < 25, Mid: 25 ≤ GA < 32, and Late: 32 ≤ GA < 40 weeks). Maternal respiration rate and coupling strength parameters were calculated for various maternal-fetal heartbeat coupling ratios. The findings of the study indicated that FBSes influenced maternal-fetal HR coupling strength during late gestation but not during early and mid-gestation. The changes in maternal-fetal HR synchronization or communication as gestation progresses occur in both FBSes. Furthermore, we noticed a significantly higher level of maternal-fetal heartbeat synchronization during periods of higher respiratory rates when the fetus was in a quiet state. These results emphasize how FBSes impact the synchronization of maternal-fetal HR and contribute to the understanding of fetal growth and health.

The Role of Occlusal Appliances in Reducing Masseter Electromyographic Activity in Bruxism

Background/Objectives: Bruxism is a masticatory muscle activity, phasic or tonic, with/without teeth contact, that appears in sleep or an awake state. An instrumental technique used to measure the surface electromyographic (sEMG) activity of the masseter muscle is used to diagnose bruxism activity during sleep and while awake. The objective of this study was to compare the variation in bruxism (sleep and awake) indices and masseter activity indices in low sleep bruxism and moderate sleep bruxism before and after wearing an occlusal appliance (OA) for 3 months each night. Methods: A clinical interventional study was designed in which subjects diagnosed with sleep bruxism were randomly selected to be included in the study. After the first sEMG recording, two groups were formed: a low sleep-bruxism group (number of sleep-bruxism events/h between 2 and 4) and a moderate sleep-bruxism group (number of sleep-bruxism events/h equal or higher than 4). All subjects received treatment with a 3D-printed occlusal appliance and wore it each night for 3 months, at which point the second sEMG recording was performed. For each participant of this study, a chart was created that included anamnestic data, clinical data, and sEMG data. The data were statistically analyzed with SPSS, using the Mann–Whitney U and Wilcoxon signed-rank tests. Results: A total of 21 participants were included in the final analysis, 18 women and 3 men, with a mean age of 24.5 ± 2.7 years. The OA lowered all bruxism indices in the whole group, but clusters analysis showed a significant reduction in sleep-bruxism indices in the moderate sleep-bruxism group, while in the low-bruxism group, the sleep and awake indices varied insignificantly, and the number of sleep-bruxism events/h remained constant. Conclusions: The 3D-printed occlusal appliances significantly lowered the sleep-bruxism indices and sleep masseter activity indices recorded with a portable sEMG device in the moderate sleep-bruxism group. The OA lowered the awake-bruxism indices and awake masseter activity indices in the moderate sleep-bruxism group.

Interleukin-12 modulates sleep–wake activity and improves performance in a memory task

BackgroundCytokines, known for their pro- and anti-inflammatory roles, are also key regulators of sleep–wake cycles. Classical pro-inflammatory cytokines, such as interleukin-1 (IL-1) and tumor necrosis factor-alpha (TNF-α), are associated with increased sleep, particularly slow-wave sleep (SWS), while anti-inflammatory cytokines, like interleukin-10 (IL-10), generally reduce sleep duration. Given the essential role of sleep in memory consolidation, this study aimed to investigate whether interleukin-12 (IL-12), a pro-inflammatory cytokine, could increase sleep duration following a memory acquisition task and subsequently improve memory performance. Male Swiss mice were surgically implanted with electrodes for electrocorticogram (ECoG) and electromyogram (EMG) recordings to track their sleep–wake cycles. After a recovery period, baseline sleep–wake activity was recorded. The mice were then randomly assigned to two groups and treated with either IL-12 (0.5 µg, i.p.) or a phosphate-buffered saline (PBS, i.p.) control, administered immediately before the multiple-trial inhibitory avoidance (MTIA) task, a behavioral test used to assess memory performance. Following the memory acquisition session, sleep–wake activity was immediately recorded for a continuous 24-h period.ResultsMice treated with IL-12 exhibited longer latency to cross into the dark compartment during the MTIA test, indicating improved memory retention compared to the control group. Interestingly, this improved performance was associated with prolonged wakefulness, particularly in the first three hours after task acquisition.ConclusionThe study shows that IL-12 can improve memory retention through prolonged wake episodes rather than increased sleep. This finding challenges the conventional understanding that sleep is the primary state for memory consolidation, suggesting that under specific conditions, wakefulness may also play a key role in supporting memory processes. Further research is needed to explore the underlying mechanisms of IL-12's cognitive effects.

Coupling of Slow Oscillations in the Prefrontal and Motor Cortex Predicts Onset of Spindle Trains and Persistent Memory Reactivations.

Sleep is known to drive the consolidation of motor memories. During nonrapid eye movement (NREM) sleep, the close temporal proximity between slow oscillations (SOs) and spindles ("nesting" of SO-spindles) is known to be essential for consolidation, likely because it is closely associated with the reactivation of awake task activity. Interestingly, recent work has found that spindles can occur in temporal clusters or "trains." However, it remains unclear how spindle trains are related to the nesting phenomenon. Here, we hypothesized that spindle trains are more likely when SOs co-occur in the prefrontal and motor cortex. We conducted simultaneous neural recordings in the medial prefrontal cortex (mPFC) and primary motor cortex (M1) of male rats training on the reach-to-grasp motor task. We found that intracortically recorded M1 spindles are organized into distinct temporal clusters. Notably, the occurrence of temporally precise SOs between mPFC and M1 was a strong predictor of spindle trains. Moreover, reactivation of awake task patterns is much more persistent during spindle trains in comparison with that during isolated spindles. Together, our work suggests that the precise coupling of SOs across mPFC and M1 may be a potential driver of spindle trains and persistent reactivation of motor memory during NREM sleep.

Local sleep in songbirds: different simultaneous sleep states across the avian pallium.

Wakefulness and sleep have often been treated as distinct and global brain states. However, an emerging body of evidence on the local regulation of sleep stages challenges this conventional view. Apart from unihemispheric sleep, the current data that support local variations of neural oscillations during sleep are focused on the homeostatic regulation of local sleep, i.e., the role preceding awake activity. Here, to examine local differences in brain activity during natural sleep, we recorded the electroencephalogram and the local field potential across multiple sites within the avian pallium of zebra finches without perturbing the previous awake state. We scored the sleep stages independently in each pallial site and found that the sleep stages are not pallium-wide phenomena but rather deviate widely across electrode sites. Importantly, deeper electrode sites had a dominant role in defining the temporal aspects of sleep state congruence. Altogether, these findings show that local regulation of sleep oscillations also occurs in the avian brain without prior awake recruitment of specific pallial circuits and in the absence of mammalian cortical neural architecture.

Massive perturbation of sound representations by anesthesia in the auditory brainstem.

Anesthesia modifies sensory representations in the thalamo-cortical circuit but is considered to have a milder impact on peripheral sensory processing. Here, tracking the same neurons across wakefulness and isoflurane or ketamine medetomidine anesthesia, we show that the amplitude and sign of single neuron responses to sounds are massively modified by anesthesia in the cochlear nucleus of the brainstem, the first relay of the auditory system. The reorganization of activity is so profound that decoding of sound representation under anesthesia is not possible based on awake activity. However, population-level parameters, such as average tuning strength and population decoding accuracy, are weakly affected by anesthesia, explaining why its effect has previously gone unnoticed when comparing independently sampled neurons. Together, our results indicate that the functional organization of the auditory brainstem largely depends on the network state and is ill-defined under anesthesia. This demonstrates a remarkable sensitivity of an early sensory stage to anesthesia, which is bound to disrupt downstream processing.

Sleep Abnormalities in SLC13A5 Citrate Transporter Disorder.

SLC13A5 Citrate Transporter Disorder is a rare pediatric neurodevelopmental disorder. Patients have epilepsy, developmental disability, and impaired mobility. While sleep disorders are common in children with neurodevelopmental disorders, sleep abnormalities have not been reported in SLC13A5 patients. Here, we assessed sleep disturbances in patients through caregiver reported surveys and in a transgenic mouse model of SLC13A5 deficiency. A total of 26 patients were evaluated with the Sleep Disturbance Scale for Children three times over a one-year span. Sleep and wake activities were assessed in the SLC13A5 knock-out (KO) mice using wireless telemetry devices. A high burden of clinically significant sleep disturbances were reported in the patients, with heterogeneous symptoms that remained stable across time. While sleep disturbances were common, less than 30% of patients were prescribed medications for sleep. Comparatively, in SLC13A5 KO mice using EEG recordings, significant alterations were found during light cycles, when rodents typically sleep. During the sleep period, SLC13A5 mice had increased activity, decreased paradoxical sleep, and changes in absolute power spectral density, indicating altered sleep architecture in the mouse model. Our results demonstrate a significant component of sleep disturbances in SLC13A5 patients and mice, highlighting a potential gap in patient care. Further investigation of sleep dysfunction and the underlying etiologies of sleep disturbances in SLC13A5 citrate transporter disorder is warranted.

Investigating light sensitivity in bipolar disorder (HELIOS-BD)

Many people with bipolar disorder have disrupted circadian rhythms. This means that the timing of sleep and wake activities becomes out-of-sync with the standard 24-hour cycle. Circadian rhythms are strongly influenced by light levels and previous research suggests that people with bipolar disorder might have a heightened sensitivity to light, causing more circadian rhythm disruption, increasing the potential for triggering a mood switch into mania or depression. Lithium has been in clinical use for over 70 years and is acknowledged to be the most effective long-term treatment for bipolar disorder. Lithium has many reported actions in the body but the precise mechanism of action in bipolar disorder remains an active area of research. Central to this project is recent evidence that lithium may work by stabilising circadian rhythms of mood, cognition and rest/activity. Our primary hypothesis is that people with bipolar disorder have some pathophysiological change at the level of the retina which makes them hypersensitive to the visual and non-visual effects of light, and therefore more susceptible to circadian rhythm dysfunction. We additionally hypothesise that the mood-stabilising medication lithium is effective in bipolar disorder because it reduces this hypersensitivity, making individuals less vulnerable to light-induced circadian disruption. We will recruit 180 participants into the HELIOS-BD study. Over an 18-month period, we will assess visual and non-visual responses to light, as well as retinal microstructure, in people with bipolar disorder compared to healthy controls. Further, we will assess whether individuals with bipolar disorder who are being treated with lithium have less pronounced light responses and attenuated retinal changes compared to individuals with bipolar disorder not being treated with lithium. This study represents a comprehensive investigation of visual and non-visual light responses in a large bipolar disorder population, with great translational potential for patient stratification and treatment innovation.

Personalized interpretable prediction of perceived sleep quality: Models with meaningful cardiovascular and behavioral features.

Understanding a person's perceived quality of sleep is an important problem, but hard due to its poor definition and high intra- as well as inter-individual variation. In the short term, sleep quality has an established impact on cognitive function during the following day as well as on fatigue. In the long term, good quality sleep is essential for mental and physical health and contributes to quality of life. Despite the need to better understand sleep quality as an early indicator for sleep disorders, perceived sleep quality has been rarely modeled for multiple consecutive days using biosignals. In this paper, we present novel insights on the association of cardiac activity and perceived sleep quality using an interpretable modeling approach utilizing the publicly available intensive-longitudinal study M2Sleep. Our method takes as input signals from commodity wearable devices, including motion and blood volume pulses. Despite processing only simple and clearly interpretable features, we achieve an accuracy of up to 70% with an AUC of 0.76 and reduce the error by up to 36% compared to related work. We further argue that collected biosignals and sleep quality labels should be normalized per-participant to enable a medically insightful analysis. Coupled with explainable models, this allows for the interpretations of effects on perceived sleep quality. Analysis revealed that besides higher skin temperature and sufficient sleep duration, especially higher average heart rate while awake and lower minimal activity of the parasympathetic and sympathetic nervous system while asleep increased the chances of higher sleep quality.

An electrophysiological correlate of sleep in a shark.

Sleep is a prominent physiological state observed across the animal kingdom. Yet, for some animals, our ability to identify sleep can be masked by behaviors otherwise associated with being awake, such as for some sharks that must swim continuously to push oxygenated seawater over their gills to breathe. We know that sleep in buccal pumping sharks with clear rest/activity cycles, such as draughtsboard sharks (Cephaloscyllium isabellum, Bonnaterre, 1788), manifests as a behavioral shutdown, postural relaxation, reduced responsiveness, and a lowered metabolic rate. However, these features of sleep do not lend themselves well to animals that swim nonstop. In addition to video and accelerometry recordings, we tried to explore the electrophysiological correlates of sleep in draughtsboard sharks using electroencephalography (EEG), electromyography, and electrooculography, while monitoring brain temperature. The seven channels of EEG activity had a surprising level of (apparent) instability when animals were swimming, but also when sleeping. The amount of stable EEG signals was too low for replication within- and across individuals. Eye movements were not measurable, owing to instability of the reference electrode. Based on an established behavioral characterization of sleep in draughtsboard sharks, we offer the original finding that muscle tone was strongest during active wakefulness, lower in quietly awake sharks, and lowest in sleeping sharks. We also offer several critical suggestions on how to improve techniques for characterizing sleep electrophysiology in future studies on elasmobranchs, particularly for those that swim continuously. Ultimately, these approaches will provide important insights into the evolutionary confluence of behaviors typically associated with wakefulness and sleep.

Analysis of the alpha activity envelope in electroencephalography in relation to the ratio of excitatory to inhibitory neural activity.

Alpha waves, one of the major components of resting and awake cortical activity in human electroencephalography (EEG), are known to show waxing and waning, but this phenomenon has rarely been analyzed. In the present study, we analyzed this phenomenon from the viewpoint of excitation and inhibition. The alpha wave envelope was subjected to secondary differentiation. This gave the positive (acceleration positive, Ap) and negative (acceleration negative, An) values of acceleration and their ratio (Ap-An ratio) at each sampling point of the envelope signals for 60 seconds. This analysis was performed on 36 participants with Alzheimer's disease (AD), 23 with frontotemporal dementia (FTD) and 29 age-matched healthy participants (NC) whose data were provided as open datasets. The mean values of the Ap-An ratio for 60 seconds at each EEG electrode were compared between the NC and AD/FTD groups. The AD (1.41 ±0.01 (SD)) and FTD (1.40 ±0.02) groups showed a larger Ap-An ratio than the NC group (1.38 ±0.02, p<0.05). A significant correlation between the envelope amplitude of alpha activity and the Ap-An ratio was observed at most electrodes in the NC group (Pearson's correlation coefficient, r = -0.92 ±0.15, mean for all electrodes), whereas the correlation was disrupted in AD (-0.09 ±0.21, p<0.05) and disrupted in the frontal region in the FTD group. The present method analyzed the envelope of alpha waves from a new perspective, that of excitation and inhibition, and it could detect properties of the EEG, Ap-An ratio, that have not been revealed by existing methods. The present study proposed a new method to analyze the alpha activity envelope in electroencephalography, which could be related to excitatory and inhibitory neural activity.

Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index (ABI) metric, a transformation of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}, and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}. Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical use in a large dataset.

Active Cluster Wake Mixing

In recent years, the relevance of the interaction between neighboring wind farms has grown steadily. As one farm extracts energy from the wind, a downstream one can systematically experience lower wind speeds which threatens the economic viability of the farm. Significant progress has been made in understanding these farm-farm wake interactions, but we still lack methodologies to mitigate their undesired effects. In this study, we introduce Active Cluster Wake Mixing (ACWM). This novel method aims to accelerate the recovery of the cluster wake using dynamic control actions: By exciting the thrust of the individual turbines depending on their relative location, we generate non-uniform patterns of energy extraction. Phase offsets between the individual excitation signals propagate these regions through the wind farm. This results in large-scale velocity gradients inside the farm, which also affect the flow in the cluster wake region. An in-depth exploration and optimization of ACWM requires significant computational effort. Therefore, we compare three different wind farm modeling approaches in Large Eddy Simulations (LES) that differ in their computational costs regarding their suitability for further exploration of ACWM. For this purpose, we use an unoptimized ACWM scheme with two different excitation frequencies. For the first time ever we successfully show that ACWM manipulates the flow inside the wind farm with favorable effects on the wake velocity. We also demonstrate that the modeling of cluster wakes is challenging and has a significant effect on the potential gain.

Design of a robotic platform for hybrid wind tunnel experiments of floating wind farms

Wind tunnel experiments incorporating factors like realistic ambient wind conditions, merging of multiple wakes, and active wake controls are needed to understand and improve modeling of floating wind farms. A key technology for this kind of experiments is the robotic system emulating the wind turbine motion. This article addresses the design of a robotic platform with three degrees-of-freedom (surge, pitch, and yaw) specifically tailored for wind tunnel experiments on floating wind farms. This robotic system aims to accurately reproduce the motion spectrum of floating wind turbines of 10-22MW and to simulate rotor-atmospheric wind interactions. The robotic platform has a compact design to be positioned in multiple units inside the wind tunnel and avoid disturbing the wake of the wind turbine on top of it. To achieve these goals, the wind turbine is partially integrated in the robotic platform that employs a parallel kinematic scheme and has all actuators close to the wind tunnel floor.

Consolidation of emotional memory during waking rest depends on trait anxiety

A short period of eyes-closed waking rest improves long-term memory for recently learned information, including declarative, spatial, and procedural memory. However, the effect of rest on emotional memory consolidation remains unknown. This preregistered study aimed to establish whether post-encoding rest affects emotional memory and how anxiety levels might modulate this effect. Participants completed a modified version of the dot-probe attention task that involved reacting to and encoding word stimuli appearing underneath emotionally negative or neutral photos. We tested the effect of waking rest on memory for these words and pictures by manipulating the state that participants entered just after this task (rest vs. active wake). Trait anxiety levels were measured using the State-Trait Anxiety Inventory and examined as a covariate. Waking rest improved emotional memory consolidation for individuals high in trait anxiety. These results suggest that the beneficial effect of waking rest on memory extends into the emotional memory domain but depends on individual characteristics such as anxiety.

Modulation of neural spiking in motor cortex-cerebellar networks during sleep spindles.

Sleep spindles appear to play an important role in learning new motor skills. Motor skill learning engages several regions in the brain with two important areas being the motor cortex (M1) and the cerebellum. However, the neurophysiological processes in these areas during sleep, especially how spindle oscillations affect local and cross-region spiking, are not fully understood. We recorded activity from the M1 and cerebellar cortex in 8 rats during spontaneous activity to investigate how sleep spindles in these regions are related to local spiking as well as cross-region spiking. We found that M1 firing was significantly changed during both M1 and cerebellum spindles and this spiking occurred at a preferred phase of the spindle. On average, M1 and cerebellum neurons showed most spiking at the M1 or cerebellum spindle peaks. These neurons also developed a preferential phase-locking to local or cross-area spindles with the greatest phase-locking value at spindle peaks; however, this preferential phase-locking wasn't significant for cerebellar neurons when compared to cerebellum spindles. Additionally, we found the percentage of task-modulated cells in the M1 and cerebellum that fired with non-uniform spike-phase distribution during M1/ cerebellum spindle peaks were greater in the rats that learned a reach-to-grasp motor task robustly. Finally, we found that spindle-band LFP coherence (for M1 and cerebellum LFPs) showed a positive correlation with success rate in the motor task. These findings support the idea that sleep spindles in both the M1 and cerebellum recruit neurons that participate in the awake task to support motor memory consolidation.Significance Statement Neural processing during sleep spindles is linked to memory consolidation. However, little is known about sleep activity in the cerebellum and whether cerebellum spindles can affect spiking activity in local or distant areas. We report the effect of sleep spindles on neuron activity in the M1 and cerebellum-specifically their firing rate and phase-locking to spindle oscillations. Our results indicate that awake practice neuronal activity is tempered during local M1 and cerebellum spindles, and during cross-region spindles, which may support motor skill learning. We describe spiking dynamics in motor networks spindle oscillations that may aid in the learning of skills. Our results support the sleep reactivation hypothesis and suggest that awake M1 activity may be reactivated during cerebellum spindles.

Comparison of Chronotypes and their Relationship with Academic Performance and Quality of Life in University Students

Abstract Objective An individual's chronotype affects circadian characteristics associated with bedtime, waking, and other daily activities. It is known that academic achievement is strongly dependent on personality traits. The present study aimed to investigate the relationship regarding chronotype, quality of life, and academic performance of university students by comparing three educational fields: medicine, technology, and art. Materials and Methods The present cross-sectional study was conducted with 400 medicine, technology, and art students enrolled at universities in Tehran between2018 and 2019, with convenience sampling from January 2020 to January 2021. The students filled out online questionnaires, including a demographics questionnaire, a quality of life assessment questionnaire (the World Health Organization Quality of Life: Brief Version, WHOQOL-BREF), the Morningness-Eveningness Questionnaire (MEQ), the Pittsburgh Sleep Quality Index (PSQI), and the Depression, Anxiety, and Stress Scale-21 items (DASS-21). The statistical analysis was performed using the IBM SPSS Statistics for Windows software, version 22.0 (p &lt; 0.05). Results A total of 400 students were enrolled in the present study, including 115 medicine, 153 technology, and 132 art students (67.3% of female and 33.7% of male subjects, with a mean age of 21.06 ± 2.063 years). In spite of the absence of significant differences among the chronotypes of the three groups, there was a significant correlation regarding the chronotypes in all groups and quality of life (p = 0.005). Morning-type individuals presented better quality of life and better quality of sleep (p &lt; 0.001; r = 0.175). No significant associations were found involving the students' academic performance and their chronotypes (p &gt; 0.05; r = 0.026). Conclusion Considering the chronotype's effect of improving the quality of life of students and, therefore, their academic performance, more studies are essential to effectively improve the academic performance of individuals with different chronotypes.

Distinct lateral hypothalamic CaMKIIα neuronal populations regulate wakefulness and locomotor activity

For nearly a century, evidence has accumulated indicating that the lateral hypothalamus (LH) contains neurons essential to sustain wakefulness. While lesion or inactivation of LH neurons produces a profound increase in sleep, stimulation of inhibitory LH neurons promotes wakefulness. To date, the primary wake-promoting cells that have been identified in the LH are the hypocretin/orexin (Hcrt) neurons, yet these neurons have little impact on total sleep or wake duration across the 24-h period. Recently, we and others have identified other LH populations that increase wakefulness. In the present study, we conducted microendoscopic calcium imaging in the LH concomitant with EEG and locomotor activity (LMA) recordings and found that a subset of LH neurons that express Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα) are preferentially active during wakefulness. Chemogenetic activation of these neurons induced sustained wakefulness and greatly increased LMA even in the absence of Hcrt signaling. Few LH CaMKIIα-expressing neurons are hypocretinergic or histaminergic while a small but significant proportion are GABAergic. Ablation of LH inhibitory neurons followed by activation of the remaining LH CaMKIIα neurons induced similar levels of wakefulness but blunted the LMA increase. Ablated animals showed no significant changes in sleep architecture but both spontaneous LMA and high theta (8 to 10 Hz) power during wakefulness were reduced. Together, these findings indicate the existence of two subpopulations of LH CaMKIIα neurons: an inhibitory population that promotes locomotion without affecting sleep architecture and an excitatory population that promotes prolonged wakefulness even in the absence of Hcrt signaling.

Interaction of acetylcholine and oxytocin neuromodulation in the hippocampus

A postulated role of subcortical neuromodulators is to control brain states. Mechanisms by which different neuromodulators compete or cooperate at various temporal scales remain an open question. We investigated the interaction of acetylcholine (ACh) and oxytocin (OXT) at slow and fast timescales during various brain states. Although these neuromodulators fluctuated in parallel during NREM packets, transitions from NREM to REM were characterized by a surge of ACh but a continued decrease of OXT. OXT signaling lagged behind ACh. High ACh was correlated with population synchrony and gamma oscillations during active waking, whereas minimum ACh predicts sharp-wave ripples (SPW-Rs). Optogenetic control of ACh and OXT neurons confirmed the active role of these neuromodulators in the observed correlations. Synchronous hippocampal activity consistently reduced OXT activity, whereas inactivation of the lateral septum-hypothalamus path attenuated this effect. Our findings demonstrate how cooperative actions of these neuromodulators allow target circuits to perform specific functions.

Sleep deprivation drives brain-wide changes in cholinergic presynapse abundance in Drosophila melanogaster

Sleep is an evolutionarily conserved state that supports brain functions, including synaptic plasticity, in species across the animal kingdom. Here, we examine the neuroanatomical and cell-type distribution of presynaptic scaling in the fly brain after sleep loss. We previously found that sleep loss drives accumulation of the active zone scaffolding protein Bruchpilot (BRP) within cholinergic Kenyon cells of the Drosophila melanogaster mushroom body (MB), but not in other classes of MB neurons. To test whether similar cell type-specific trends in plasticity occur broadly across the brain, we used a flp-based genetic reporter to label presynaptic BRP in cholinergic, dopaminergic, GABAergic, or glutamatergic neurons. We then collected whole-brain confocal image stacks of BRP intensity to systematically quantify BRP, a marker of presynapse abundance, across 37 neuropil regions of the central fly brain. Our results indicate that sleep loss, either by overnight (12-h) mechanical stimulation or chronic sleep disruption in insomniac mutants, broadly elevates cholinergic synapse abundance across the brain, while synapse abundance in neurons that produce other neurotransmitters undergoes weaker, if any, changes. Extending sleep deprivation to 24 h drives brain-wide upscaling in glutamatergic, but not other, synapses. Finally, overnight male-male social pairings induce increased BRP in excitatory synapses despite male-female pairings eliciting more waking activity, suggesting experience-specific plasticity. Within neurotransmitter class and waking context, BRP changes are similar across the 37 neuropil domains, indicating that similar synaptic scaling rules may apply across the brain during acute sleep loss and that sleep need may broadly alter excitatory-inhibitory balance in the central brain.