Awake State Research Articles

Turbulent flows past two elliptical cylinders in tandem arrangement: wake dynamics and aerodynamic characteristics

Abstract. This study investigates the aerodynamic phenomena of drafting, a common technique observed in various racing sports, by analyzing the wake dynamics behind two 2D elliptic cylinders placed in tandem. The research explores how the separation distance and the azimuthal angle between the cylinders affect turbulent wake patterns and aerodynamic coefficients. A numerical study was conducted using a RANS-based simulation, with findings validated through physical experiments in a wind tunnel. The study identifies six distinct wake dynamics: Wake states without vortex shedding, Single bluff body wake, Suppressed vortex shedding, Coupled vortex shedding, Anti-phase vortex shedding, and In-phase vortex shedding. These dynamics vary significantly with changes in separation ratio and angle of attack, highlighting the critical influence of these parameters on the wake behavior and aerodynamic performance. The results are presented in a phase diagram, illustrating the evolution of wake patterns across different conditions. This research fills existing knowledge gaps by providing a detailed analysis of the wake dynamics behind elliptic cylinders at high Reynolds numbers, with potential applications in improving aerodynamic strategies in various engineering and sporting contexts.

EEG-Derived Markers to Improve Prognostic Evaluation of Disorders of Consciousness.

Disorders of consciousness (DoC) are characterized by alteration in arousal and/or awareness commonly caused by severe brain injury. There exists a consensus on adopting advanced neuroimaging and electrophysiological procedures to improve diagnosis/prognosis of DoC patients. Currently, these procedures are prevalently applied in a research-oriented context and their translation into clinical practice is yet to come. The aim of the study consisted in the identification of measures derived from routinary electroencephalography (EEG) able to support clinicians in the prediction of DoC patients' outcome. In the present study, a routine EEG was recorded during rest from a sample of 58 DoC patients clinically diagnosed as Unresponsive Wakefulness State (UWS) and Minimally Conscious State (MCS) and followed-up for 3 months. EEG-based features characterizing brain activity in terms of spectral content and resting state networks organization were used in a predictive machine learning model to i) identify which were the most promising features in predicting patients' exit from the DoC, regardless of the clinical diagnosis and ii) verify whether such features would have been the same best discriminating UWS from MCS or specific of the outcome prediction. A predictive machine learning model was built on EEG features related to spectral content and resting state networks which returned up to 85% of performance accuracy in outcome prediction and 76% in DoC state recognition (UWS vs MCS). We provided preliminary evidence for the exploitation of a routine EEG to improve the clinical management of non-communicative patients to be confirmed in a larger DoC population.

Evaluating the effects of three anesthetic regimens on retinal structure and function in the living mouse eye using a customized bimodal OCT/ORG system

Abstract Optical coherence tomography (OCT) is a non-invasive imaging technique that generates cross-sectional images of biological tissues at millimeter-level penetration depth with micron-level resolution. In this study, we developed a custom spectral-domain OCT system equipped with a flash stimulus module for dual-modality imaging of mouse retinal structure and function. The axial resolution of the system reached ∼2.7/2 μm in air/tissue following optimization and calibration. We deployed this system to conduct in vivo OCT structural imaging and optoretinography (ORG) functional assessment of mouse retina to investigate the effects of three anesthesia regimens. Statistical analysis of the results indicates that anesthesia results in a smaller relative intensity of inner/outer segment junction and external limiting membrane and a thickening of the outer segment compared to an awake state. Meanwhile, significant differences were observed in the effects on retinal structure and function between isoflurane and tribromoethanol anesthesia, while differences between isoflurane and esketamine+xylazine groups were small. These findings suggest that the type of anesthetic should be taken into account when comparing imaging results across studies reported in the literature.

Population Pharmacokinetic Modelling of Norepinephrine in Healthy Volunteers Prior to and During General Anesthesia.

Intraoperation hypotension (IOH) is commonly observed in patients undergoing surgery under general anesthesia, and even a brief episode of IOH can lead to unfavorable outcomes. To reduce the risk, blood pressure is closely measured during general anesthesia, and norepinephrine (NE) is frequently administered if hypotension is detected. Despite its routine application, information on the dose-exposure-response relationship of NE remains limited. Additionally, quantification of the influence of general anesthesia on the pharmacokinetics (PK) of NE is lacking. In this study, we aimed to describe NE PK in healthy volunteers and the influence of general anesthesia on its PK. A single-center, cross-over study was conducted in healthy volunteers. The volunteers received a step-up NE dosing scheme (0.04, 0.08, 0.12, 0.16 and 0.20 mcg-1/kg-1/min-1) first in the awake state and then under general anesthesia. General anesthesia was administered using a propofol/remifentanil Eleveld target-controlled infusion. During general anesthesia, a 30-second electrical stimulus was given as surrogate for surgical incision to the volunteers at each dosage step. Blood samples were drawn before the initial dosing and after each dosing step, and plasma NE, propofol and remifentanil concentrations were subsequently determined. A population PK model was developed using non-linear mixed effects modelling. Simulations were conducted to predict the plasma NE concentration in patients at different measured propofol concentrations. A total of 1219 samples were analyzed from 36 volunteers. A two-compartment model with a first-order elimination best described the data. Weight, age, and session effect (awake vs general anesthesia) were identified as relevant covariates on the clearance (CL) of NE. A 10% decrease in NE CL was observed after general anesthesia induction. This difference between sessions is better explained by the measured concentration of propofol, rather than the anticipated impact of cardiac output. The estimated post-stimulation NE concentration is 0.66 nmol/L-1 (95% CI 0.06-1.20 nmol/L-1) lower than the pre-stimulation NE concentration. Model simulation indicates that patients at a higher measured propofol concentration (e.g., 6 mcg/mL-1) exhibited higher NE concentrations (95% PI 18.10-43.89 nmol/L-1) than patients at a lower measured propofol concentration (e.g., 3 mcg/mL-1) (95% PI 16.81-38.91 nmol L-1). The NE PK is well described with a two-compartment model with a first-order elimination. NE CL exhibiting a 10% decrease under general anesthesia, with this difference being attributed to the measured concentration of propofol. The impact of stimulation on NE PK under general anesthesia is very limited. NL9312.

Measuring the dynamic balance of integration and segregation underlying consciousness, anesthesia, and sleep in humans

Consciousness requires a dynamic balance of integration and segregation in brain networks. We report an fMRI-based metric, the integration-segregation difference (ISD), which captures two key network properties: network efficiency (integration) and clustering (segregation). With this metric, we quantify brain state transitions from conscious wakefulness to unresponsiveness induced by the anesthetic propofol. The observed changes in ISD suggest a profound shift towards the segregation of brain networks during anesthesia. A common unimodal-transmodal sequence of disintegration and reintegration occurs in brain networks during, respectively, loss and return of responsiveness. Machine learning models using integration and segregation data accurately identify awake vs. unresponsive states and their transitions. Metastability (dynamic recurrence of non-equilibrium transient states) is more effectively explained by integration, while complexity (diversity of neural activity) is more closely linked with segregation. A parallel analysis of sleep states produces similar findings. Our results demonstrate that the ISD reliably indexes states of consciousness.

Sleep in the dromedary camel: features of the 'first night effect'.

The 'first night effect' (FNE) is a well-known phenomenon in polysomnographic (PSG) sleep studies, resulting in significant variations in the macrostructure of wakefulness and sleep states, particularly between the initial and subsequent sleep recording sessions. The FNE phenomenon during sleep has been studied in various species, revealing complex variations between several sessions of sleep recording. The present study used a non-invasive PSG method to examine differences between various vigilance states in four adult female dromedary camels during 4 consecutive nights and days of sleep recording. The results indicate the presence of a FNE in the architecture of the dromedary camel's vigilance states. On the first night, the proportions of wakefulness and light non-rapid eye movment (NREM) sleep (drowsiness) were higher, at a mean (standard error of the mean [SEM]) of 40.92% (0.88%) and 14.93% (0.37%), respectively; while the proportion of rumination (mean [SEM] 29.55% [0.92%]) was lower compared to consecutive nights. No FNE was found on deep NREM sleep, while night-time REM sleep had a shorter proportion during the first night compared to subsequent consecutive nights. A significantly lower REM/total sleep time (TST) ratio was observed on the first night. Daytime comparisons did not show any significant differences for the different vigilance states. The increase in wakefulness and light NREM sleep and the reduction in REM sleep and REM/TST sleep on the first night indicate a decline in sleep quality in the dromedary camel due to the FNE. Thus, we recommend excluding from a PSG sleep study at least the first session/night of the recordings to ensure accurate results.

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.

Exploring the Trinity Of 9NFTMANIA, Premium Domain, and COREDAOVIP through the Lens of The AUM Concept in The Mandukya Upanishad

This paper presents a novel conceptual framework correlating the symbolic elements of AUM (ॐ) from the Mandukya Upanishad with the evolving digital ecosystem represented by 9NFTMANIA, Premium Domain, and Coredaovip. AUM, regarded as the most sacred syllable in Hindu philosophy, embodies three states of consciousness: A (awake state), U (dream state), and M (deep sleep state). In this analogy, 9NFTMANIA reflects the awake state (A), where users actively engage with the metaverse; Premium Domain represents the dream state (U), where desires and digital ambitions are shaped; and Coredaovip embodies the deep sleep state (M), the unseen yet foundational element influencing and governing the digital landscape. This research draws parallels between the spiritual and digital worlds, offering insights into the dynamic relationships between metaverse platforms and their foundational principles.

NIR-II Anti-Stokes Luminescence Nanocrystals with 1710 nm Excitation for in vivo Bioimaging.

Anti-Stokes luminescence (ASL) based on lanthanide nanocrystals holds immense promise for in vivo optical imaging and bio-detection, which benefits from filtered autofluorescence. However, the current longest emission and excitation wavelengths of lanthanide ASL system were shorter than 1200 nm and 1532 nm, respectively, which limited tissue penetration depth and caused low signal-to-noise ratio (SNR) of in vivo imaging due to tissue scattering and water absorption. In this work, we extended the excitation wavelength to 1710 nm with the second near-infrared (NIR-II, 1000-1700 nm) emission up to 1650 nm through a novel ASL nanocrystal LiYF4:10%Tm@LiYF4:70%Er@LiYF4. Compared with 1532 nm excited ASL nanoprobes, the 1710 nm excited nanocrystals could improve in vivo imaging SNR by 12.72 folds. Based on this excellent imaging performance of the proposed ASL nanoprobes, three-channel in vivo dynamic multiplexed imaging was achieved, which quantitatively revealed metabolic rates of intestinal dynamics and liver enrichment under anesthetized and awake states. This innovative ASL nanoprobes and dynamic multiplexed imaging technology would be conducive to optimizing dosing regimen and treatment plans across various physiological conditions.

Convergent effects of different anesthetics on changes in phase alignment of cortical oscillations.

Many anesthetics cause loss of responsiveness despite having diverse underlying molecular and circuit actions. To explore the convergent effects of these drugs, we examined how anesthetic doses of ketamine and dexmedetomidine affected oscillations in the prefrontal cortex of nonhuman primates. Both anesthetics caused increases in phase locking in the ventrolateral and dorsolateral prefrontal cortex, within and across hemispheres. However, the nature of the phase locking varied. Activity in different subregions within a hemisphere became more anti-phase with both drugs. Local analyses within a region suggested that this finding could be explained by broad cortical distance-based effects, such as large traveling waves. By contrast, homologous areas across hemispheres became more in-phase. Our results suggest that both anesthetics induce strong patterns of cortical phase alignment that are markedly different from those in the awake state, and that these patterns may be a common feature driving loss of responsiveness from different anesthetic drugs.

NIR‐II Anti‐Stokes Luminescence Nanocrystals with 1710 nm Excitation for in vivo Bioimaging

Anti‐Stokes luminescence (ASL) based on lanthanide nanocrystals holds immense promise for in vivo optical imaging and bio‐detection, which benefits from filtered autofluorescence. However, the current longest emission and excitation wavelengths of lanthanide ASL system were shorter than 1200 nm and 1532 nm, respectively, which limited tissue penetration depth and caused low signal‐to‐noise ratio (SNR) of in vivo imaging due to tissue scattering and water absorption. In this work, we extended the excitation wavelength to 1710 nm with the second near‐infrared (NIR‐II, 1000‐1700 nm) emission up to 1650 nm through a novel ASL nanocrystal LiYF4:10%Tm@LiYF4:70%Er@LiYF4. Compared with 1532 nm excited ASL nanoprobes, the 1710 nm excited nanocrystals could improve in vivo imaging SNR by 12.72 folds. Based on this excellent imaging performance of the proposed ASL nanoprobes, three‐channel in vivo dynamic multiplexed imaging was achieved, which quantitatively revealed metabolic rates of intestinal dynamics and liver enrichment under anesthetized and awake states. This innovative ASL nanoprobes and dynamic multiplexed imaging technology would be conducive to optimizing dosing regimen and treatment plans across various physiological conditions.

Propofol-mediated loss of consciousness disrupts predictive routing and local field phase modulation of neural activity

Predictive coding is a fundamental function of the cortex. The predictive routing model proposes a neurophysiological implementation for predictive coding. Predictions are fed back from the deep-layer cortex via alpha/beta (8 to 30 Hz) oscillations. They inhibit the gamma (40 to 100 Hz) and spiking that feed sensory inputs forward. Unpredicted inputs arrive in circuits unprepared by alpha/beta, resulting in enhanced gamma and spiking. To test the predictive routing model and its role in consciousness, we collected data from intracranial recordings of macaque monkeys during passive presentation of auditory oddballs before and after propofol-mediated loss of consciousness (LOC). In line with the predictive routing model, alpha/beta oscillations in the awake state served to inhibit the processing of predictable stimuli. Propofol-mediated LOC eliminated alpha/beta modulation by a predictable stimulus in the sensory cortex and alpha/beta coherence between sensory and frontal areas. As a result, oddball stimuli evoked enhanced gamma power, late period (>200 ms from stimulus onset) spiking, and superficial layer sinks in the sensory cortex. LOC also resulted in diminished decodability of pattern-level prediction error signals in the higher-order cortex. Therefore, the auditory cortex was in a disinhibited state during propofol-mediated LOC. However, despite these enhanced feedforward responses in the auditory cortex, there was a loss of differential spiking to oddballs in the higher-order cortex. This may be a consequence of a loss of within-area and interareal spike-field coupling in the alpha/beta and gamma frequency bands. These results provide strong constraints for current theories of consciousness.

Positive end-expiratory pressure and emergence preoxygenation after bariatric surgery: A randomised controlled trial on postoperative oxygenation.

Positive end-expiratory pressure (PEEP) is important to increase lung volume and counteract airway closure during anaesthesia, especially in obese patients. However, maintaining PEEP during emergence preoxygenation might increase postoperative atelectasis by allowing susceptible lung areas to be filled with highly absorbable oxygen that gets entrapped when small airways collapse due to the sudden loss of PEEP at extubation. This study aimed to test the hypothesis that withdrawing PEEP just before emergence preoxygenation would better maintain postoperative oxygenation. Prospective, randomised controlled trial. Single centre secondary hospital in Sweden between December 2019 and January 2023. A total of 60 patients, with body mass index between 35 and 50 kg m -2 , undergoing laparoscopic bariatric surgery. Intraoperative ventilation was the same for all patients with a fixed PEEP of 12 or 14 cmH 2 O depending on body mass index. No recruitment manoeuvres were used. After surgery, patients were allocated to maintained PEEP or zero PEEP during emergence preoxygenation. The primary outcome was change in oxygenation from before awakening to 45 min postoperatively as measured by estimated venous admixture calculated from arterial blood gases. Both groups had impaired oxygenation postoperatively; in the group with PEEP maintained during awakening, estimated venous admixture increased by mean 9.1%, and for the group with zero PEEP during awakening, estimated venous admixture increased by mean 10.6%, difference -1.5% (95% confidence interval -4.6 to 1.7%), P = 0.354. Throughout anaesthesia, both groups exhibited low driving pressures and superior oxygenation compared with the awake state. Withdrawing PEEP before emergence preoxygenation, did not alter early postoperative oxygenation in obese patients undergoing laparoscopic bariatric surgery. Intraoperative oxygenation was excellent despite using fixed PEEP and no recruitment manoeuvres, but deteriorated after extubation, indicating a need for future studies aimed at improving the emergence procedure. www.clinicaltrials.gov , NCT04150276. Registration date: 4 November 2019. Principal investigator: Erland Östberg.

Profiling the sleep architecture of ageing adults using a seven-state continuous-time Markov model.

Sleep is a complex biological process regulated by networks of neurons and environmental factors. As one falls asleep, neurotransmitters from sleep-wake regulating neurones work in synergy to control the switching of different sleep states throughout the night. As sleep disorders or underlying neuropathology can manifest as irregular switching, analysing these patterns is crucial in sleep medicine and neuroscience. While hypnograms represent the switching of sleep states well, current analyses of hypnograms often rely on oversimplified temporal descriptive statistics (TDS, e.g., total time spent in a sleep state), which miss the opportunity to study the sleep state switching by overlooking the complex structures of hypnograms. In this paper, we propose analysing sleep hypnograms using a seven-state continuous-time Markov model (CTMM). This proposed model leverages the CTMM to depict the time-varying sleep-state transitions, and probes three types of insomnia by distinguishing three types of wake states. Fitting the proposed model to data from 2056 ageing adults in the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study, we profiled sleep architectures in this population and identified the various associations between the sleep state transitions and demographic factors and subjective sleep questions. Ageing, sex, and race all show distinctive patterns of sleep state transitions. Furthermore, we also found that the perception of insomnia and restless sleep are significantly associated with critical transitions in the sleep architecture. By incorporating three wake states in a continuous-time Markov model, our proposed method reveals interesting insights into the relationships between objective hypnogram data and subjective sleep quality assessments.

Differential effects of haloperidol on neural oscillations during wakefulness and sleep

The electrical activity of the brain, characterized by its frequency components, reflects a complex interplay between periodic (oscillatory) and aperiodic components. These components are associated with various neurophysiological processes, such as the excitation-inhibition balance (aperiodic activity) or interregional communication (oscillatory activity). However, we do not fully understand whether these components are truly independent or if different neuromodulators affect them in different ways. The dopaminergic system has a critical role for cognition and motivation, being a potential modulator of these power spectrum components. To improve our understanding of these questions, we investigated the differential effects of this system on these components using electrocorticogram recordings in cats, which show clear oscillations and aperiodic 1/f activity. Specifically, we focused on the effects of haloperidol (a D2 receptor antagonist) on oscillatory and aperiodic dynamics during wakefulness and sleep. By parameterizing the power spectrum into these two components, our findings reveal a robust modulation of oscillatory activity by the D2 receptor across the brain. Surprisingly, aperiodic activity was not significantly affected and exhibited inconsistent changes across the brain. This suggests a nuanced interplay between neuromodulation and the distinct components of brain oscillations, providing insights into the selective regulation of oscillatory dynamics in awake states.

How to quantify sleepiness during an attempt to sleep?

Background. Sleepiness assessment tools were mostly developed for detection of an elevated sleepiness level in the condition of sleep deprivation and several medical conditions. However, sleepiness occurs in various other conditions including the transition from wakefulness to sleep during an everyday attempt to get sleep.Objective. We examined whether objective sleepiness indexes can be implicated in detection of fluctuations in sleepiness level during the polysomnographically-monitored attempt to sleep, i.e. in the absence of self-reports on perceived sleepiness level throughout such an attempt.Approach. The polysomnographic signals were recorded in the afternoon throughout 106 90 min napping attempts of 53 university students (28 females). To calculate two objective sleepiness indexes, the electroencephalographic (EEG) spectra were averaged on 30 s epochs of each record, assigned to one of 5 sleep-wake stages, and scored using either the frequency weighting curve for sleepiness substate of wake state or loadings of each frequency on the 2nd principal component of variation in the EEG spectrum (either sleepiness score or PC2 score, respectively).Main results. We showed that statistically significant fluctuations in these two objective sleepiness indexes during epochs assigned to wake stage can be described in terms of the changes in verbally anchored levels of subjective sleepiness assessed by scoring on the 9-step Karolinska Sleepiness Scale.Significance. The results afford new opportunities to elaborate importance of intermediate substates between wake and sleep states for sleep-wake dynamics in healthy individuals and patients with disturbed sleep.

Electroencephalogram and phenotype patterns in neuronopathic Gaucher disease patients – ten years of experience in a single center

BackgroundThis study aimed to investigate the unique electroencephalography (EEG) patterns in neuronopathic Gaucher disease (GD) patients and explore the correlations between EEG findings and neurological phenotypes so as to optimize clinical outcomes.MethodsA retrospective analysis was conducted on 74 EEG recordings from 50 GD patients between January 2012 and July 2022.ResultsTwenty-three patients exhibited abnormal EEG recordings, including 11 of the GD1 type (the transitional type) and 12 with neuronopathic GD. Of the 12 neuronopathic GD patients, 9 patients with epilepsy were analysed specifically in terms of the clinical course. The primary waveform observed in the neuronopathic EEG recordings was the spike-and-wave complex (SWC) during both awake and sleep states. This was significantly different from sharp waves observed only during sleep in the patients of the transitional type (P = 0.0230). The abnormal discharges in the neuronopathic patients were most commonly located in the bilateral Rolandic areas, while the transitional type commonly involved the bilateral frontal regions. Three patients with an epileptic EEG pattern reported their initial seizures years later. Seizures in the neuronopathic patients were effectively controlled with anti-seizure medications (ASMs), despite the ongoing presence of abnormal EEG patterns. The EEG patterns during ocular symptoms were characterized by sporadic or continuous unilateral SWC during sleep.ConclusionsPatients with neuronopathic GD exhibit distinct EEG patterns that can help differentiate them from GD1 patients. Early treatment with ASMs can effectively control seizures. EEG plays a crucial role in monitoring seizures and can facilitate prompt intervention for GD patients.

Combined value of interictal markers and stimulated seizures to estimate the seizure onset zone in stereoelectroencephalography.

This study was undertaken to investigate the potential of interictal electroencephalographic (EEG) findings and electrically stimulated seizures during stereo-EEG (SEEG) as surrogate markers for the spontaneous seizure onset zone (spSOZ). We hypothesized that combining the localizing information of these markers would allow clinically meaningful estimation of the spSOZ. We included all patients (n = 63) who underwent SEEG between January 2013 and March 2020 at Helsinki University Hospital and had spontaneous seizures during the recording. We scored spikes, gamma activity, and background abnormality on each channel visually during a 12-h epoch containing waking state and sleep. Based on semiology, we classified stimulated seizures as typical or atypical/unclassifiable and estimated the stimulated SOZ (stimSOZ) for typical seizures. To assess which markers increased the odds of channel inclusion in the spSOZ, we fitted mixed effects logistic regression models. A combined regression model including the stimSOZ and interictal markers scored during sleep performed better in estimating which channels were part of the spSOZ than models based on stimSOZ (p < .001) or interictal markers (p < .001) alone. Of the individual markers, the effect sizes were greatest for inclusion of a channel in the stimSOZ (odds ratio [OR] = 60, 95% confidence interval [CI] = 37-97, p < .001) and for continuous (OR = 25, 95% CI = 12-55, p < .001) and subcontinuous (OR = 36, 95% CI = 21-64, p < .001) interictal spiking. At the individual level, the model's accuracy to predict spSOZ inclusion varied markedly (median accuracy = 85.7, range = 54.4-100), which was not explained by etiology (p > .05). Compared to either marker alone, combining visually rated interictal SEEG markers and stimulated seizures improved prediction of which SEEG channels belonged to the spSOZ. Inclusion in the stimSOZ and continuous or subcontinuous spikes increased the odds of spSOZ inclusion the most. Future studies should investigate whether suboptimal sampling of the true epileptogenic zone can explain the model's poor performance in certain patients.

Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data

BackgroundWide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjunct EEG and EMG recordings. However, this process is time-consuming, invasive and often suffers from low inter- and intra-rater reliability. Therefore, an automated sleep state classification method that operates on spatiotemporal WFCI data is desired. New methodA hybrid network architecture consisting of a convolutional neural network (CNN) to extract spatial features of image frames and a bidirectional long short-term memory network (BiLSTM) with attention mechanism to identify temporal dependencies among different time points was proposed to classify WFCI data into states of wakefulness, NREM and REM sleep. ResultsSleep states were classified with an accuracy of 84 % and Cohen’s κ of 0.64. Gradient-weighted class activation maps revealed that the frontal region of the cortex carries more importance when classifying WFCI data into NREM sleep while posterior area contributes most to the identification of wakefulness. The attention scores indicated that the proposed network focuses on short- and long-range temporal dependency in a state-specific manner. Comparison with existing methodOn a held out, repeated 3-hour WFCI recording, the CNN-BiLSTM achieved a κ of 0.67, comparable to a κ of 0.65 corresponding to the human EEG/EMG-based scoring. ConclusionsThe CNN-BiLSTM effectively classifies sleep states from spatiotemporal WFCI data and will enable broader application of WFCI in sleep research.

Parabrachial nucleus Vglut2 expressing neurons projection to the extended amygdala involved in the regulation of wakefulness during sevoflurane anesthesia in mice.

The parabrachial nucleus (PBN) promotes wakefulness states under general anesthesia. Recent studies have shown that glutamatergic neurons within the PBN play a crucial role in facilitating emergence from anesthesia. Our previous study indicates that vesicular glutamate transporter 2 (vglut2) expression neurons of the PBN extend into the extended amygdala (EA). However, the modulation of PBNvglut2-EA in general anesthesia remains poorly understood. This study aims to investigate the role of PBNvglut2-EA in alterations of consciousness during sevoflurane anesthesia. We first validated vglut2-expressing neuron projections from the PBN to the EA using anterograde tracing. Then, we conducted immunofluorescence staining of c-Fos to investigate the role of the EA involved in the regulation of consciousness during sevoflurane anesthesia. After, we performed calcium fiber photometry recordings to determine the changes in PBNvglut2-EA activity. Lastly, we modulated PBNvglut2-EA activity under sevoflurane anesthesia using optogenetics, and electroencephalogram (EEG) was recorded during specific optogenetic modulation. The expression of vglut2 in PBN neurons projected to the EA, and c-Fos expression in the EA was significantly reduced during sevoflurane anesthesia. Fiber photometry revealed that activity in the PBNvglut2-EA pathway was suppressed during anesthesia induction but restored upon awakening. Optogenetic activation of the PBNvglut2-EA delayed the induction of anesthesia. Meanwhile, EEG recordings showed significantly decreased δ oscillations and increased β and γ oscillations compared to the EYFP group. Furthermore, optogenetic activation of the PBNvglut2-EA resulted in an acceleration of awakening from anesthesia, accompanied by decreased δ oscillations on EEG recordings. Optogenetic inhibition of PBNvglut2-EA accelerated anesthesia induction. Surprisingly, we found a sex-specific regulation of PBNvglut2-EA in this study. The activity of PBNvglut2-EA was lower in males during the induction of anesthesia and decreased more rapidly during sevoflurane anesthesia compared to females. Photoactivation of the PBNvglut2-EA reduced the sensitivity of males to sevoflurane, showing more pronounced wakefulness behavior and EEG changes than females. PBNvglut2-EA is involved in the promotion of wakefulness under sevoflurane anesthesia. Furthermore, PBNvglut2-EA shows sex differences in the changes of consciousness induced by sevoflurane anesthesia.