Awake State Research Articles

Workflow for the unsupervised clustering of sleep stages identifies light and deep sleep in electrophysiological recordings in mice

BackgroundSleep physiology plays a critical role in brain development and aging. Accurate sleep staging, which categorizes different sleep states, is fundamental for sleep physiology studies. Traditional methods for sleep staging rely on manual, rule-based scoring techniques, which limit their accuracy and adaptability. New methodWe describe, test and challenge a workflow for unsupervised clustering of sleep states (WUCSS) in rodents, which uses accelerometer and electrophysiological data to classify different sleep states. WUCSS utilizes unsupervised clustering to identify sleep states using six features, extracted from 4-second epochs. ResultsWe gathered high-quality EEG recordings combined with accelerometer data in diverse transgenic mouse lines (male ApoE3 versus ApoE4 knockin; male CNTNAP2 KO versus wildtype littermates). WUCSS showed high recall, precision, and F1-score against manual scoring on awake, NREM, and REM sleep states. Within NREM, WUCSS consistently identified two additional clusters that qualify as deep and light sleep states. Comparison with existing methodsThe ability of WUCSS to discriminate between deep and light sleep enhanced the precision and comprehensiveness of the current mouse sleep physiology studies. This differentiation led to the discovery of an additional sleep phenotype, notably in CNTNAP2 KO mice, showcasing the method's superiority over traditional scoring methods. ConclusionsWUCSS, with its unsupervised approach and classification of deep and light sleep states, provides an unbiased opportunity for researchers to enhance their understanding of sleep physiology. Its high accuracy, adaptability, and ability to save time and resources make it a valuable tool for improving sleep staging in both clinical and preclinical research.

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation.

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.

Age-dependent coupling characteristics of bilateral frontal EEG during desflurane anesthesia.

Objectives.The purpose of this study is to investigate the age dependence of bilateral frontal electroencephalogram (EEG) coupling characteristics, and find potential age-independent depth of anesthesia monitoring indicators for the elderlies.Approach.We recorded bilateral forehead EEG data from 41 patients (ranged in 19-82 years old), and separated into three age groups: 18-40 years (n= 12); 40-65 years (n= 14), >65 years (n= 15). All these patients underwent desflurane maintained general anesthesia (GA). We analyzed the age-related EEG spectra, phase amplitude coupling (PAC), coherence and phase lag index (PLI) of EEG data in the states of awake, GA, and recovery.Main results.The frontal alpha power shows age dependence in the state of GA maintained by desflurane. Modulation index in slow oscillation-alpha and delta-alpha bands showed age dependence and state dependence in varying degrees, the PAC pattern also became less pronounced with increasing age. In the awake state, the coherence in delta, theta and alpha frequency bands were all significantly higher in the >65 years age group than in the 18-40 years age group (p< 0.05 for three frequency bands). The coherence in alpha-band was significantly enhanced in all age groups in GA (p< 0.01) and then decreased in recovery state. Notably, the PLI in the alpha band was able to significantly distinguish the three states of awake, GA and recovery (p< 0.01) and the results of PLI in delta and theta frequency bands had similar changes to those of coherence.Significance.We found the EEG coupling and synchronization between bilateral forehead are age-dependent. The PAC, coherence and PLI portray this age-dependence. The PLI and coherence based on bilateral frontal EEG functional connectivity measures and PAC based on frontal single-channel are closely associated with anesthesia-induced unconsciousness.

Association Between Clinical Measures of Depth of Sedation and Multimodal Cerebral Physiology in Acute Traumatic Neural Injury.

Neurointensive care primarily focuses on secondary injury reduction, utilizing a variety of guideline-based approaches (including administration of high-dose sedation) to reduce the injured state. However, titration of sedation is currently based on the Richmond Agitation Sedation Scale (RASS), a subjective clinical grading score of a patient's response to external physical stimuli, and not an objective measure. Therefore, it is likely that there exists substantial variation in objective sedation depth for a given clinical grade in these patients, leading to undesired sedation depths and cerebral physiological consequences. Improper sedation can impede cerebral autoregulation, emphasizing the critical need for optimal sedation in traumatic brain injury (TBI) patients. This study evaluates the relationship between RASS to an objective measure of depth of sedation (bispectral index, BIS) and cerebral physiological measures. Fifty-nine patients were assessed using Jonckheere-Terpstra testing to compare various key physiologies with RASS. RASS (-5 through 0 categories) showed no statistically significant relationship between BIS and cerebral physiological parameters, after adjusting for multiple comparisons. Furthermore, it is crucial to note that within each RASS value, the distribution of the physiological measures all had high variability. As an exemplar, for RASS values of -5 and -4, BIS ranged from near 0 (burst suppression levels) up to over 80 (near awake states). BIS and other cerebral physiologies displayed substantial variation across each RASS category. This suggests that RASS as a means to titrate sedative medication for the goal of neuroprotection is insufficient. More momentary, individualized determination of sedation depth is required for TBI patients.

Automating Polysomnography in an Under-Explored Animal Model: Preliminary Results from Hibernating Bears

Animal hibernation is a hypometabolic state that may inform translational research to improve clinical outcomes for hypoxic patients whose oxygen supply does not match their demand. Bears are an excellent animal model, as they decrease their body temperature to only 30-35°C during hibernation and suppress their metabolism down to 25% of normal resting levels while having a more comparable physiology to humans than deep hibernators such as small rodents. As little is known about their sleep patterns during hibernation, we continuously monitored for more than 3500 days via biotelemetry a variety of physiological parameters from 16 captive American black bears in and out of hibernation. We recorded EEG, EOG and EMG signals that are commonly used to determine wake, REM sleep and NREM sleep vigilance states in conventional animal models (polysomnography). Such a data set is too large to fully annotate manually, so we compared two automated approaches. We first manually annotated two one-day recordings at body temperature extremes from each of 6 bears during hibernation when body temperatures were oscillating widely in multiday cycles with intermittent bouts of shivering (Tøien et al. 2011). We also manually scored a one-day, non-hibernating recording at normal (summer) body temperature from these bears. Based on this reference data set, we evaluated two automated scoring applications based on different machine learning classifiers: open source Somnotate (author Paul Brodersen), which is trained on multiple files, and proprietary Somnivore (author Giancarlo Allocca), which is trained on a subset of epochs from each individual recording. Somnotate gave best results during hold-one-out testing when using separate models for hibernating and non-hibernating data, and then performed comparably for both conditions. Somnivore was by design trained on a small subset (100 epochs of each kind) of each file to be tested. Both applications provided typical F-measures against manual reference scores in the 0.90-0.97 range. Outliers in the lower 0.72-0.88 range were highly correlated between the two applications, indicating that specific files are more challenging to annotate — either manually, automatically, or both. We conclude that both applications have accuracies on par with manual scorers when trained on high quality data. Supported by NIH COBRE under grant number [P20GM130443]. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Sleep pressure modulates single-neuron synapse number in zebrafish

Sleep is a nearly universal behaviour with unclear functions1. The synaptic homeostasis hypothesis proposes that sleep is required to renormalize the increases in synaptic number and strength that occur during wakefulness2. Some studies examining either large neuronal populations3 or small patches of dendrites4 have found evidence consistent with the synaptic homeostasis hypothesis, but whether sleep merely functions as a permissive state or actively promotes synaptic downregulation at the scale of whole neurons is unclear. Here, by repeatedly imaging all excitatory synapses on single neurons across sleep–wake states of zebrafish larvae, we show that synapses are gained during periods of wake (either spontaneous or forced) and lost during sleep in a neuron-subtype-dependent manner. However, synapse loss is greatest during sleep associated with high sleep pressure after prolonged wakefulness, and lowest in the latter half of an undisrupted night. Conversely, sleep induced pharmacologically during periods of low sleep pressure is insufficient to trigger synapse loss unless adenosine levels are boosted while noradrenergic tone is inhibited. We conclude that sleep-dependent synapse loss is regulated by sleep pressure at the level of the single neuron and that not all sleep periods are equally capable of fulfilling the functions of synaptic homeostasis.

Flow Topology of the Bi-Stable Wake States for the DrivAer Fastback Model

For this work, conditional averaging and Proper Orthogonal Decomposition (POD) were used to analyze the salient three-dimensional structures in the wake of a DrivAer fastback model with smooth underbody. Conditional averaging revealed that the bi-stable structure of the wake consists of a ring-like structure with three vortex legs, which includes a vortex pair on the side associated with the bi-stability and one on the opposite side associated with the wheel vortex. POD revealed the entrainment of low-momentum fluid from the wheel wake into the vortex pair leads to an induced spanwise crossflow which drives a feedback loop for the bi-stability. The resultant bi-stable structure was dependent on the state of the wheels. With stationary wheels, the feedback mechanism is enhanced, leading to higher spanwise crossflow that breaks the ring-like vortex. A different structure was observed when the wheels rotate, wherein the ring-like structure is unbroken and pierced by the vortex pair. The feedback mechanism and resultant vortex structure are similar to those found in simplified square-back models. Given the similarity in bi-stability between realistic and simplified vehicles, the suppression of the bi-stability in realistic vehicles could initially be based on the same mechanism as that for simplified square-back models.

DRIVER DROWSINESS DETECTION SYSTEMS

Car accidents are frequently caused due to many reasons like drowsiness, drunkenness or tiredness, which has serious consequences for traffic safety. Numerous factors, such as fatigue, intoxication, or drowsiness, commonly contribute to car accidents, which have detrimental effects on traffic safety. Many fatal collisions might be avoided if sleepy drivers were warned beforehand. Many sleepiness detection technologies are available to identify and warn drivers of any indications of inattention while driving. Sensors in self-driving cars must be able to detect whether a driver is sleepy, agitated, or experiencing sharp emotional fluctuations. Thus far There have been numerous recommendations for enhanced warning systems to prevent sleepy driving. When these systems detect a significant lane departure, a change in the headway distance, or other indications of subpar driving, they sound an alarm. These systems rely heavily on machine learning algorithms, which allow them to learn and adjust to unique driving patterns and characteristics. In supervised learning, models are trained on labelled datasets to discriminate between awake and sleepy states. These approaches are widely used for classification tasks. Unsupervised learning techniques are also applied for anomaly detection, which finds departures from typical driving behaviour. The incorporation of cutting-edge sensors like facial recognition cameras and brainwave sensors, which offer more thorough insights into the driver's condition, has recently improved driver sleepiness detection systems. Moreover, these systems are more accurate and responsive when real-time data processing and cloud-based analytics are used. KEYWORDS Drowsiness-detection, Driver-Fatigue, Computer Vision, Real Time, survey, Eye Tracking Technology, Automotive Safety Systems, Driver Assistance Systems, Real-time Drowsiness Detection, Alertness Monitoring.

Stimulus-induced arousal with transient electroencephalographic improvement distinguishes nonictal from ictal generalized periodic discharges.

In the case of suspicion of nonconvulsive status epilepticus (NCSE), reactivity on electroencephalograms (EEGs) can provide valuable diagnostic information. Reactivity refers to responses to auditory or somatosensory stimulation, with changes in amplitude and frequency of background activity. Because of self-perpetuating processes and the failure of self-terminating mechanisms, status epilepticus is unlikely to cease when patients spontaneously move, and it cannot typically be stopped by external stimulation (i.e., auditory and tactile stimuli). The defining EEG characteristic of absence status epilepticus is the presence of bilateral, synchronous, symmetric, rhythmic paroxysmal activity that shows little or no reactivity to sensory stimulation. On the other hand, in metabolic/toxic or multifactorial encephalopathies, triphasic waves (TWs) are influenced by the level of vigilance. TWs may be transiently abolished when patients increase their level of alertness from a drowsy/lethargic state to a state of wakefulness. This reactivity is only observed when patients can be aroused by a somatosensory or auditory stimulus. This reactivity tends to disappear with increasing severity of the disease and in comatose patients. In patients without preexisting developmental and epileptic encephalopathy, this pattern of stimulus-induced wakefulness with transient improvement of the EEG is a major criterion in determining that the EEG patterns are not ictal. This criterion of reactivity on EEGs, beyond the classical clinical/EEG criteria of NCSE (Salzburg criteria), should now be systematically added.

Case-control study of heart rate variability and sleep apnea in childhood sickle cell disease.

Obstructive sleep apnea (OSA) is common in sickle cell disease (SCD) despite the absence of overweight, suggesting a specific pathophysiology. We previously showed that otherwise healthy children with increased pharyngeal compliance, a main endotype of OSA, exhibited decreased sympathetic modulation. Our objective was to assess whether modifications of heart rate variability (HRV) and compliance are associated in SCD. Cases (children with SCD, African or Caribbean ethnicity) and controls (otherwise healthy children, same ethnicity), aged 4-18 years, were selected from our database of children referred for OSA and matched for sex, age, and obstructive apnea-hypopnoea index (OAHI) score. The children underwent polysomnography and acoustic pharyngometry (to compute compliance). HRV analyses were performed from 5 min ECG recordings in wakeful, NREM, and REM sleep states and from the whole night. Twenty-one pairs were analysed (median age 10.5 years, 24 girls). Children with SCD had lower BMI z-scores and more tonsil hypertrophy than control children. Children with SCD and OSA (OAHI ≥2/hour) were characterised by lower compliance than children with SCD without OSA. An inverse relationship between compliance and SD2 (HRV from whole night, inversely related to sympathetic modulation) was evidenced (negative relationship in SCD: R = -0.63, p = 0.002 vs. positive relationship in controls R = 0.59, p = 0.006). In conclusion, while the decrease in sympathetic modulation in control children may contribute to increasing pharyngeal compliance, its decrease seems protective in children with sickle cell disease, which underlines the specificity of OSAS pathophysiology in SCD that could be due to sickle cell disease related smooth muscle dystonia.

Sleep and Ultramarathon: Exploring Patterns, Strategies, and Repercussions of 1,154 Mountain Ultramarathons Finishers

BackgroundSleep and physical performance are strongly related and mutually influence each other. Athletes, particularly in disciplines like offshore sailing and ultra-endurance sports, often suffer from sleep deprivation due to factors like irregular training times, travel, and the extended duration of events like 100-mile mountain races. Despite growing interest in sleep’s role in sports science, few studies have specifically investigated the sleep patterns of ultramarathon runners. This study aimed to investigate sleep patterns and sleep management strategies in ultramarathons, and the repercussions of sleep deprivation during and after races.MethodsThis cross-sectional study using e-survey was conducted on 1154 runners from two ultramarathons (a 165 km race with 9,576 m positive elevation; 2018 finish time [23:18:48–66:04:00], and a 111 km race with 6,433 m elevation; [15:34:56 − 41:54:16]).ResultsThe results revealed that 58% of the runners reported implementing sleep management strategies before or during the race. Most runners began the race with some level of sleep debt (-50 min a week before the race). During the races, 77% of runners slept, with the cumulative sleep duration varying based on race duration and the number of nights spent on the race (76 min at 165 km and 27 min at 111 km). Short naps lasting less than 30 min were the most popular strategy. The prevalence of symptoms attributed to sleep deprivation during the race was high (80%), with reported falls and hallucinations. After the race, runners reported recovering a normal state of wakefulness relatively quickly (within two days); 22% believed that sleep deprivation during the race increased the risk of accidents in everyday life.ConclusionThis study provides valuable insights into sleep patterns and strategies in ultramarathon running and emphasizes the importance of adequate sleep management for performance and post-race recovery.

Daydreaming as spontaneous immersive imagination: A phenomenological analysis

Research on the specific features of daydreaming compared with mind-wandering and night dreaming is a neglected topic in the philosophy of mind and the cognitive neuroscience of spontaneous thought. The extant research either conflates daydreaming with mind-wandering (whether understood as task-unrelated thought, unguided attention, or disunified thought), characterizes daydreaming as opposed to mind-wandering (Dorsch, 2015), or takes daydreaming to encompass any and all “imagined events” (Newby-Clark &amp; Thavendran, 2018). These dueling definitions obstruct future research on spontaneous thought, and are insufficiently precise to guide empirical studies. They also fail to illuminate the phenomenal core of daydreaming, namely, its dreamlike qualities. Although daydreaming is related to both mind-wandering and narrative imagination, it is not reducible to either. We argue that daydreams are experiences of spontaneous, immersive imagination in the waking state. The main task of our investigation is to distinguish daydreaming, conceptually and phenomenologically, from mind-wandering, on the one hand, and night dreaming, on the other. Although daydream experiences can vary widely, we distinguish prototypical experiences of daydreaming from adjacent imaginative activity, including fleeting imagery and “focused daydreaming,” or crafted visualization. We consider our phenomenological analysis as preparatory work for conceptually distinguishing different spontaneous and imaginative states so that they can be investigated accordingly with questionnaires and qualitative methods. We argue that precision about the phenomenal character of daydreaming can guide neurophenomenological investigations, help delimit studies on individual variance in daydreaming features, and identify differences among daydreaming, mind-wandering, and night dreaming conceptually and phenomenologically, and possibly eventually in terms of neural correlates.

Neural assemblies coordinated by cortical waves are associated with waking and hallucinatory brain states

The relationship between sensory stimuli and perceptions is brain-state dependent: in wakefulness, suprathreshold stimuli evoke perceptions; under anesthesia, perceptions are abolished; and during dreaming and in dissociated states, percepts are internally generated. Here, we exploit this state dependence to identify brain activity associated with internally generated or stimulus-evoked perceptions. In awake mice, visual stimuli phase reset spontaneous cortical waves to elicit 3-6Hz feedback traveling waves. These stimulus-evoked waves traverse the cortex and entrain visual and parietal neurons. Under anesthesia as well as during ketamine-induced dissociation, visual stimuli do not disrupt spontaneous waves. Uniquely, in the dissociated state, spontaneous waves traverse the cortex caudally and entrain visual and parietal neurons, akin to stimulus-evoked waves in wakefulness. Thus, coordinated neuronal assemblies orchestrated by traveling cortical waves emerge in states in which perception can manifest. The awake state is privileged in that this coordination is reliably elicited by external visual stimuli.

Gaps in the wall of a perivascular space act as valves to produce a directed flow of cerebrospinal fluid: a hoop-stress model.

The flow of cerebrospinal fluid (CSF) along perivascular spaces (PVSs) is an important part of the brain's system for clearing metabolic waste. Astrocyte endfeet bound the PVSs of penetrating arteries, separating them from brain extracellular space. Gaps between astrocyte endfeet might provide a low-resistance pathway for fluid transport across the wall. Recent studies suggest that the astrocyte endfeet function as valves that rectify the CSF flow, producing the net flow observed in pial PVSs by changing the size of the gaps in response to pressure changes. In this study, we quantify this rectification based on three features of the PVSs: the quasi-circular geometry, the deformable endfoot wall, and the pressure oscillation inside. We provide an analytical model, based on the thin-shell hoop-stress approximation, and predict a pumping efficiency of about 0.4, which would contribute significantly to the observed flow. When we add the flow resistance of the extracellular space (ECS) to the model, we find an increased net flow during sleep, due to the known increase in ECS porosity (decreased flow resistance) compared to that in the awake state. We corroborate our analytical model with three-dimensional fluid-solid interaction simulations.

Performance Evaluation of a New Sport Watch in Sleep Tracking: A Comparison against Overnight Polysomnography in Young Adults.

Introduction: This study aimed to validate the ability of a prototype sport watch (Polar Electro Oy, FI) to recognize wake and sleep states in two trials with and without an interval training session (IT) 6 h prior to bedtime. Methods: Thirty-six participants completed this study. Participants performed a maximal aerobic test and three polysomnography (PSG) assessments. The first night served as a device familiarization night and to screen for sleep apnea. The second and third in-home PSG assessments were counterbalanced with/without IT. Accuracy and agreement in detecting sleep stages were calculated between PSG and the prototype. Results: Accuracy for the different sleep stages (REM, N1 and N2, N3, and awake) as a true positive for the nights without exercise was 84 ± 5%, 64 ± 6%, 81 ± 6%, and 91 ± 6%, respectively, and for the nights with exercise was 83 ± 7%, 63 ± 8%, 80 ± 7%, and 92 ± 6%, respectively. The agreement for the sleep night without exercise was 60.1 ± 8.1%, k = 0.39 ± 0.1, and with exercise was 59.2 ± 9.8%, k = 0.36 ± 0.1. No significant differences were observed between nights or between the sexes. Conclusion: The prototype showed better or similar accuracy and agreement to wrist-worn consumer products on the market for the detection of sleep stages with healthy adults. However, further investigations will need to be conducted with other populations.

Accelerated lymph flow from infusion of crystalloid fluid during general anesthesia

BackgroundKinetic analysis of crystalloid fluid yields a central distribution volume (Vc) of the same size as the expected plasma volume (approximately 3 L) except during general anesthesia during which Vc might be only half as large. The present study examined whether this difference is due to influence of the intravascular albumin balance.MethodsA population volume kinetic analysis according to a three-compartment model was performed based on retrospective data from 160 infusion experiments during which 1–2.5 L of crystalloid fluid had been infused intravenously over 20–30 min. The plasma dilution based on blood hemoglobin (Hb) and plasma albumin (Alb) was measured on 2,408 occasions and the urine output on 454 occasions. One-third of the infusions were performed on anesthetized patients while two-thirds were given to awake healthy volunteers.ResultsThe Hb-Alb dilution difference was four times greater during general anesthesia than in the awake state (+ 0.024 ± 0.060 versus − 0.008 ± 0.050; mean ± SD; P < 0.001) which shows that more albumin entered the plasma than was lost by capillary leakage. The Hb-Alb dilution difference correlated strongly and positively with the kinetic parameters governing the rate of fluid transfer through the fast-exchange interstitial fluid compartment (k12 and k21) and inversely with the size of Vc. Simulations suggest that approximately 200 mL of fluid might be translocated from the interstitial space to the plasma despite ongoing fluid administration.ConclusionsPronounced plasma volume expansion early during general anesthesia is associated with a positive intravascular albumin balance that is due to accelerated lymphatic flow. This phenomenon probably represents adjustment of the body fluid volumes to anesthesia-induced vasodilatation.

Characterising the motion and cardiorespiratory interaction of preterm infants can improve the classification of their sleep state.

This study aimed to classify quiet sleep, active sleep and wake states in preterm infants by analysing cardiorespiratory signals obtained from routine patient monitors. We studied eight preterm infants, with an average postmenstrual age of 32.3 ± 2.4 weeks, in a neonatal intensive care unit in the Netherlands. Electrocardiography and chest impedance respiratory signals were recorded. After filtering and R-peak detection, cardiorespiratory features and motion and cardiorespiratory interaction features were extracted, based on previous research. An extremely randomised trees algorithm was used for classification and performance was evaluated using leave-one-patient-out cross-validation and Cohen's kappa coefficient. A sleep expert annotated 4731 30-second epochs (39.4 h) and active sleep, quiet sleep and wake accounted for 73.3%, 12.6% and 14.1% respectively. Using all features, and the extremely randomised trees algorithm, the binary discrimination between active and quiet sleep was better than between other states. Incorporating motion and cardiorespiratory interaction features improved the classification of all sleep states (kappa 0.38 ± 0.09) than analyses without these features (kappa 0.31 ± 0.11). Cardiorespiratory interactions contributed to detecting quiet sleep and motion features contributed to detecting wake states. This combination improved the automated classifications of sleep states.

Over- and underreporting of seizures: How big is the problem?

Clinical decisions on managing epilepsy patients rely on patient accuracy regarding seizure reporting. Studies have noted disparities between patient-reported seizures and electroencephalographic (EEG) findings during video-EEG monitoring periods, chiefly highlighting underreporting of seizures, a well-recognized phenomenon. However, seizure overreporting is a significant problem discussed within the literature, although not in such a large cohort. Our aim is to quantify the over- and underreporting of seizures in a large cohort of ambulatory EEG patients. We performed a retrospective data analysis on 3407 patients referred to a diagnostic service for ambulatory video-EEG between 2020 and 2022. Both patient-reported events and events discovered on review of the video-EEG were analyzed and classified as epileptic, psychogenic (typically clinical motor events, without accompanying EEG change), or noncorrelated events (NCEs; without perceivable clinical or EEG change). Events were analyzed by state of arousal and indication for referral. Subgroup analysis was performed in patients with focal and generalized epilepsies. A total of 21 024 events were recorded by 3407 patients. Fifty-eight percent of reported events were NCEs, whereas 27% of all events were epileptic. Sixty-four percent of epileptic seizures were not reported by the patient but discovered by the clinical service on review of the recording. NCEs were in the highest proportion in the awake and drowsy arousal states and were the most common event type for the majority of referral indications. Subgroup analysis found a significantly higher proportion of NCEs in the patients with focal epilepsy (23%) compared to generalized epilepsy (10%; p < .001, chi-squared proportion test). Our results reaffirm the phenomenon of underreporting and highlight the prevalence of overreporting. Overreporting likely represents irrelevant symptoms or electrographic discharges not represented on scalp electrodes, identification of which has important clinical relevance. Future studies should analyze events by risk factors to elucidate relationships clinicians can use and investigate the etiology of NCEs.

Noribogaine acute administration in rats promotes wakefulness and suppresses REM sleep.

Ibogaine is a potent atypical psychedelic that has gained considerable attention due to its antiaddictive and antidepressant properties in preclinical and clinical studies. Previous research from our group showed that ibogaine suppresses sleep and produces an altered wakefulness state, which resembles natural REM sleep. However, after systemic administration, ibogaine is rapidly metabolized to noribogaine, which also shows antiaddictive effects but with a distinct pharmacological profile, making this drug a promising therapeutic candidate. Therefore, we still ignore whether the sleep/wake alterations depend on ibogaine or its principal metabolite noribogaine. To answer this question, we conducted polysomnographic recordings in rats following the administration of pure noribogaine. Our results show that noribogaine promotes wakefulness while reducing slow-wave sleep and blocking REM sleep, similar to our previous results reported for ibogaine administration. Thus, we shed new evidence on the mechanisms by which iboga alkaloids work in the brain.

Commentary] When ‘Ignorance is Bliss’ in Medicine

Treatment of diseases can be simple as well as effective with only limited medical knowledge, provided the physician is connected with the ‘pure consciousness’ within oneself, which is also the basis of everything in the universe. The ‘inner self’ or ‘pure consciousness’ has refreshing and healing qualities. This healing ‘inner self’ is within the conscious reach of every individual in the waking state, through the practice of meditation. The physician connected to his ‘inner self’ can help the patient to reach a more blissful state of consciousness, thus facilitating healing of all types of diseases. While mind-body therapies are patient-dependent self-help strategies, the physician who is connected with the ‘inner self’, can directly help to initiate the healing process. Positivity is manifested by the physician regardless of whether the medical knowledge he utilizes is ‘simple’ or the more complex ‘scientific’. There may be ‘ignorance’ of complex ‘scientific knowledge’, but there is ‘wisdom’ of being connected with the source of all healing.