Nodding behavior couples to vigilance fluctuation in a high-calorie diet model of drowsiness.
ABSTRACT: Drowsiness is an awake state with increased sleep drive, yet the neural correlates and underlying mechanisms remains unclear. Here, we established a mouse model of drowsiness, where mice are fasted for 1 day and then allowed to overeat high-fat food (to promote sleep) while positioned in an open-field box (to promote vigilance). They fall into a long-lasting drowsy state, as reflected by repeated and open-eyed nodding of the head while in a standing position. Simultaneous recording of electroencephalogram (EEG) and neck electromyogram (EMG) readouts revealed that this drowsy state including nodding state had multiple stages in terms of the relationship between the level of vigilance and head movement: delta oscillations decreased in power prior to the head-nodding period and increased during the non-nodding period. Cav3.1-knockout mice, which have reduced delta oscillations, showed frequent head nodding with reduced duration of nodding episodes compared to wild-type mice. This suggests that the balance of drive is tilted in favor of wakefulness, likely due to their previously proposed decrease in sleep-promoting functions. Our findings indicate that delta oscillations play a dominant role in controlling vigilance dynamics during sleep/wake competition and that our novel mouse model may be useful for studying drowsiness and related neurological disorders.
Project description:Numerous ocular parameters have been proposed as reliable physiological markers of drowsiness. A device that measures many of these parameters and then combines them into a single metric (the Johns Drowsiness Scale [JDS]) is being used commercially to assess drowsiness in professional drivers. Here, we examine how these parameters reflect changes in drowsiness, and how they relate to objective and subjective indices of the drowsy state in a controlled laboratory setting.A within subject prospective study.29 healthy adults (18 males; mean age 23.3 ± 4.6 years; range 18-34 years).N/A.Over the course of a 30-h extended wake vigil under constant routine (CR) conditions, participants were monitored using infrared reflectance oculography (Optalert) and completed bi-hourly neurobehavioral tests, including the Karolinska Sleepiness Scale (KSS) and Psychomotor Vigilance Task (PVT). Ocular-defined increases in drowsiness were evident with extended time awake and during the biological night for all ocular parameters; JDS being the most sensitive marker of drowsiness induced by sleep regulatory processes (p < 0.0001). In addition, the associations between JDS in the preceding 10-min period and subsequent PVT lapses and KSS were stronger (AUC 0.74/0.80, respectively) than any other ocular metric, such that PVT lapses, mean response time (RT), and KSS increased in a dose-response manner as a function of prior JDS score (p < 0.0001).Ocular parameters captured by infrared reflectance oculography detected fluctuations in drowsiness due to time awake and during the biological night. The JDS outcome was the strongest predictor of drowsiness among those tested, and showed a clear association to objective and subjective measures of drowsiness. Our findings indicate this real-time objective drowsiness monitoring system is an effective tool for monitoring changes in alertness and performance along the alert-drowsy continuum in a controlled laboratory setting.
Project description:Drowsy driving imposes a high safety risk. Current systems often use driving behavior parameters for driver drowsiness detection. The continuous driving automation reduces the availability of these parameters, therefore reducing the scope of such methods. Especially, techniques that include physiological measurements seem to be a promising alternative. However, in a dynamic environment such as driving, only non- or minimal intrusive methods are accepted, and vibrations from the roadbed could lead to degraded sensor technology. This work contributes to driver drowsiness detection with a machine learning approach applied solely to physiological data collected from a non-intrusive retrofittable system in the form of a wrist-worn wearable sensor. To check accuracy and feasibility, results are compared with reference data from a medical-grade ECG device. A user study with 30 participants in a high-fidelity driving simulator was conducted. Several machine learning algorithms for binary classification were applied in user-dependent and independent tests. Results provide evidence that the non-intrusive setting achieves a similar accuracy as compared to the medical-grade device, and high accuracies (>92%) could be achieved, especially in a user-dependent scenario. The proposed approach offers new possibilities for human-machine interaction in a car and especially for driver state monitoring in the field of automated driving.
Project description:As we fall sleep, our brain traverses a series of gradual changes at physiological, behavioural and cognitive levels, which are not yet fully understood. The loss of responsiveness is a critical event in the transition from wakefulness to sleep. Here we seek to understand the electrophysiological signatures that reflect the loss of capacity to respond to external stimuli during drowsiness using two complementary methods: spectral connectivity and EEG microstates. Furthermore, we integrate these two methods for the first time by investigating the connectivity patterns captured during individual microstate lifetimes. While participants performed an auditory semantic classification task, we allowed them to become drowsy and unresponsive. As they stopped responding to the stimuli, we report the breakdown of alpha networks and the emergence of theta connectivity. Further, we show that the temporal dynamics of all canonical EEG microstates slow down during unresponsiveness. We identify a specific microstate (D) whose occurrence and duration are prominently increased during this period. Employing machine learning, we show that the temporal properties of microstate D, particularly its prolonged duration, predicts the response likelihood to individual stimuli. Finally, we find a novel relationship between microstates and brain networks as we show that microstate D uniquely indexes significantly stronger theta connectivity during unresponsiveness. Our findings demonstrate that the transition to unconsciousness is not linear, but rather consists of an interplay between transient brain networks reflecting different degrees of sleep depth.
Project description:Accumulating evidence reveals that neuronal oscillations with various frequency bands in the brain have different physiological functions. However, the frequency band divisions in rats were typically based on empirical spectral distribution from limited channels information. In the present study, functionally relevant frequency bands across vigilance states and brain regions were identified using factor analysis based on 9 channels EEG signals recorded from multiple brain areas in rats. We found that frequency band divisions varied both across vigilance states and brain regions. In particular, theta oscillations during REM sleep were subdivided into two bands, 5-7 and 8-11 Hz corresponding to the tonic and phasic stages, respectively. The spindle activities of SWS were different along the anterior-posterior axis, lower oscillations (~16 Hz) in frontal regions and higher in parietal (~21 Hz). The delta and theta activities co-varied in the visual and auditory cortex during wakeful rest. In addition, power spectra of beta oscillations were significantly decreased in association cortex during REM sleep compared with wakeful rest. These results provide us some new insights into understand the brain oscillations across vigilance states, and also indicate that the spatial factor should not be ignored when considering the frequency band divisions in rats.
Project description:Sleep is one of our most important physiological functions that maintains physical and mental health. Two studies examined whether discrete areas of attention are equally affected by sleep loss. This was achieved using a repeated-measures within-subjects design, with two contrasting conditions: normal sleep and partial sleep restriction of 5-h. Study 1 compared performance on a sustained attention task (Psychomotor Vigilance task; PVT) with performance on a transient attention task (Attentional Blink; AB). PVT performance, but not performance on the AB task, was impaired after sleep restriction. Study 2 sought to determine the neural underpinnings of the phenomenon, using electroencephalogram (EEG) frequency analysis, which measured activity during the brief eyes-closed resting state before the tasks. AB performance was unaffected by sleep restriction, despite clearly observable changes in brain activity. EEG results showed a significant reduction in resting state alpha oscillations that was most prominent centrally in the right hemisphere. Changes in individual alpha and delta power were also found to be related to changes in subjective sleepiness and PVT performance. Results likely reflect different levels of impairment in specific forms of attention following sleep loss.
Project description:INTRODUCTION:Prior research shows that physicians in training are at risk for drowsy driving following their clinical duties, which may put them in danger of experiencing adverse driving events. This study explores the relationship between sleepiness, overall sleep hygiene, level of training, and adverse driving events following an overnight shift in emergency medicine (EM) residents. METHODS:Throughout the 2018-2019 academic year, 50 EM residents from postgraduate years 1-4 completed self-administered surveys regarding their sleepiness before and after their drive home following an overnight shift, any adverse driving events that occurred during their drive home, and their overall sleep hygiene. RESULTS:Fifty out of a possible 57 residents completed the survey for a response rate of 87.7%. Sleepiness was significantly associated with adverse driving events (beta = 0.31; P < .001). Residents with high sleepiness levels reported significantly more adverse driving events. Residents reported significantly higher sleepiness levels after completing their drive home (mean = 7.04, standard deviation [SD] = 1.41) compared to sleepiness levels before driving home (mean = 5.58, SD = 1.81). Residency training level was significantly associated with adverse driving events (beta = -0.59, P < .01). Senior residents reported significantly fewer adverse driving events compared to junior residents. CONCLUSION:Emergency physicians in training are at risk for drowsy driving-related motor vehicle crashes following overnight work shifts. Trainees of all levels underestimated their true degree of sleepiness prior to initiating their drive home, while junior residents were at higher risk for adverse driving events.
Project description:STUDY OBJECTIVES:The present studies examine the effects of NMDAR activation by NYX-2925 diurnal rhythmicity of both sleep and wake as well as emotion. METHODS:Twenty-four-hour sleep EEG recordings were obtained in sleep-deprived and non-sleep-deprived rats. In addition, the day-night cycle of both activity and mood was measured using home cage ultrasonic-vocalization recordings. RESULTS:NYX-2925 significantly facilitated non-REM (NREM) sleep during the lights-on (sleep) period, and this effect persisted for 3 days following a single dose in sleep-deprived rats. Sleep-bout duration and REM latencies were increased without affecting total REM sleep, suggesting better sleep quality. In addition, delta power during wake was decreased, suggesting less drowsiness. NYX-2925 also rescued learning and memory deficits induced by sleep deprivation, measured using an NMDAR-dependent learning task. Additionally, NYX-2925 increased positive affect and decreased negative affect, primarily by facilitating the transitions from sleep to rough-and-tumble play and back to sleep. In contrast to NYX-2925, the NMDAR antagonist ketamine acutely (1-4 hours post-dosing) suppressed REM and non-REM sleep, increased delta power during wake, and blunted the amplitude of the sleep-wake activity rhythm. DISCUSSION:These data suggest that NYX-2925 could enhance behavioral plasticity via improved sleep quality as well as vigilance during wake. As such, the facilitation of sleep by NYX-2925 has the potential to both reduce symptom burden on neurological and psychiatric disorders as well as serve as a biomarker for drug effects through restoration of sleep architecture.
Project description:This paper presents the 60-s time-resolution segment from our 50-h total sleep deprivation (TSD) dataset (Aidman et al., 2018)  that captures minute-by-minute dynamics of driving performance (lane keeping and speed variability) along with objective, oculography-derived drowsiness estimates synchronised to the same 1-min driving epochs. Eleven participants (5 females, aged 18-28) were randomised into caffeine (administered in four 200?mg doses via chewing gum in the early morning hours) or placebo groups. Every three hours they performed a 40?min simulated drive in a medium fidelity driving simulator, while their drowsiness was continuously measured with a spectacle frame-mounted infra-red alertness monitoring system. The dataset covers 15 driving periods of 40?min each, and thus contains over 600 data points of paired data per participant. The 1-min time resolution enables detailed time-series analyses of both time-since-wake and time-on-task performance dynamics and associated drowsiness levels. It also enables direct examination of the relationships between drowsiness and task performance measures. The question of how these relationships might change under various intervention conditions (caffeine in our case) seems worth further investigation.
Project description:OBJECTIVES:Sleep, which comprises of rapid eye movement (REM) and non-REM stages 1-3 (N1-N3), is a natural occurring state of decreased arousal that is crucial for normal cardiovascular, immune and cognitive function. The principal sedative drugs produce electroencephalogram beta oscillations, which have been associated with neurocognitive dysfunction. Pharmacological induction of altered arousal states that neurophysiologically approximate natural sleep, termed biomimetic sleep, may eliminate drug-induced neurocognitive dysfunction. METHODS:We performed a prospective, single-site, three-arm, randomized-controlled, crossover polysomnography pilot study (n?=?10) comparing natural, intravenous dexmedetomidine- (1-?g/kg over 10 min [n?=?7] or 0.5-?g/kg over 10?min [n?=?3]), and zolpidem-induced sleep in healthy volunteers. Sleep quality and psychomotor performance were assessed with polysomnography and the psychomotor vigilance test, respectively. Sleep quality questionnaires were also administered. RESULTS:We found that dexmedetomidine promoted N3 sleep in a dose dependent manner, and did not impair performance on the psychomotor vigilance test. In contrast, zolpidem extended release was associated with decreased theta (?5-8?Hz; N2 and N3) and increased beta oscillations (?13-25?Hz; N2 and REM). Zolpidem extended release was also associated with increased lapses on the psychomotor vigilance test. No serious adverse events occurred. CONCLUSIONS:Pharmacological induction of biomimetic N3 sleep with psychomotor sparing benefits is feasible. SIGNIFICANCE:These results suggest that ?2a adrenergic agonists may be developed as a new class of sleep enhancing medications with neurocognitive sparing benefits.
Project description:In unconscious status (e.g., deep sleep and anesthetic unconsciousness) where cognitive functions are not generated there is still a significant level of brain activity present. Indeed, the electrophysiology of the unconscious brain is characterized by well-defined thalamocortical rhythmicity. Here we address the ionic basis for such thalamocortical rhythms during unconsciousness. In particular, we address the role of CaV3.1 T-type Ca(2+) channels, which are richly expressed in thalamic neurons. Toward this aim, we examined the electrophysiological and behavioral phenotypes of mice lacking CaV3.1 channels (CaV3.1 knockout) during unconsciousness induced by ketamine or ethanol administration. Our findings indicate that CaV3.1 KO mice displayed attenuated low-frequency oscillations in thalamocortical loops, especially in the 1- to 4-Hz delta band, compared with control mice (CaV3.1 WT). Intriguingly, we also found that CaV3.1 KO mice exhibited augmented high-frequency oscillations during unconsciousness. In a behavioral measure of unconsciousness dynamics, CaV3.1 KO mice took longer to fall into the unconscious state than controls. In addition, such unconscious events had a shorter duration than those of control mice. The thalamocortical interaction level between mediodorsal thalamus and frontal cortex in CaV3.1 KO mice was significantly lower, especially for delta band oscillations, compared with that of CaV3.1 WT mice, during unconsciousness. These results suggest that the CaV3.1 channel is required for the generation of a given set of thalamocortical rhythms during unconsciousness. Further, that thalamocortical resonant neuronal activity supported by this channel is important for the control of vigilance states.