Harnessing olfactory bulb oscillations to perform fully brain-based sleep-scoring and real-time monitoring of anaesthesia depth

Odor representation and coding by the mitral/tufted cells in the olfactory bulb

The olfactory bulb (OB) is the first relay station in the olfactory system and functions as a crucial hub. It can represent odor information precisely and accurately in an ever-changing environment. As the only output neurons in the OB, mitral/tufted cells encode information such as odor identity and concentration. Recently, the neural strategies and mechanisms underlying odor representation and encoding in the OB have been investigated extensively. Here we review the main progress on this topic. We first review the neurons and circuits involved in odor representation, including the different cell types in the OB and the neural circuits within and beyond the OB. We will then discuss how two different coding strategies-spatial coding and temporal coding-work in the rodent OB. Finally, we discuss potential future directions for this research topic. Overall, this review provides a comprehensive description of our current understanding of how odor information is represented and encoded by mitral/tufted cells in the OB.

Selective Modulation of Fear Memory in Non-Rapid Eye Movement Sleep

Sleep stabilizes memories for their consolidation, but how to modify specific fear memory during sleep remains unclear. Here, it is reported that using targeted memory reactivation (TMR) to reactivate prior fear learning experience in non-slow wave sleep (NS) inhibits fear memory consolidation, while TMR during slow wave sleep (SWS) enhances fear memory in mice. Replaying conditioned stimulus (CS) during sleep affects sleep spindle occurrence, leading to the reduction or enhancement of slow oscillation-spindle (SO-spindle) coupling in NS and SWS, respectively. Optogenetic inhibition of pyramidal neurons in the frontal association cortex (FrA) during TMR abolishes the behavioral effects of NS-TMR and SWS-TMR by modulating SO-spindle coupling. Notably, calcium imaging of the L2/3 pyramidal neurons in the FrA shows that CS during SWS selectively enhances the activity of neurons previously activated during fear conditioning (FC+ neurons), which significantly correlates with CS-elicited spindle power spectrum density. Intriguingly, these TMR-induced calcium activity changes of FC+ neurons further correlate with mice freezing behavior, suggesting their contributions to the consolidation of fear memories. The findings indicate that TMR can selectively weaken or strengthen fear memory, in correlation with modulating SO-spindle coupling and the reactivation of FC+ neurons during substages of non-rapid eye movement (NREM) sleep.

Understanding How Acute Alcohol Impacts Neural Encoding in the Rodent Brain

Alcohol impacts neural circuitry throughout the brain and has wide-ranging effects on the biophysical properties of neurons in these circuits. Articulating how these wide-ranging effects might eventually result in altered computational properties has the potential to provide a tractable working model of how alcohol alters neural encoding. This chapter reviews what is currently known about how acute alcohol influences neural activity in cortical, hippocampal, and dopaminergic circuits as these have been the primary focus of understanding how alcohol alters neural computation. While other neural systems have been the focus of exhaustive work on this topic, these brain regions are the ones where in vivo neural recordings are available, thus optimally suited to make the link between changes in neural activity and behavior. Rodent models have been key in developing an understanding of how alcohol impacts the function of these circuits, and this chapter therefore focuses on work from mice and rats. While progress has been made, it is critical to understand the challenges and caveats associated with experimental procedures, especially when performed in vivo, which are designed to answer this question and if/how to translate these data to humans. The hypothesis is discussed that alcohol impairs the ability of neural circuits to acquire states of neural activity that are transiently elevated and characterized by increased complexity. It is hypothesized that these changes are distinct from the traditional view of alcohol being a depressant of neural activity in the forebrain.

State-dependent alteration of respiration in a rat model of Parkinson's disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder. Besides major deficits in motor coordination, patients may also display sensory and cognitive impairments, which are often overlooked despite being inherently part of the PD symptomatology. Amongst those symptoms, respiration, a key mechanism involved in the regulation of multiple physiological and neuronal processes, appears to be altered. Importantly, breathing patterns are highly correlated with the animal's behavioral states. This raises the question of the potential impact of behavioral state on respiration deficits in PD. To answer this question, we first characterized the respiratory parameters in a neurotoxin-induced rat model of PD (6-OHDA) across three different vigilance states: sleep, quiet waking and exploration. We noted a significantly higher respiratory frequency in 6-OHDA rats during quiet waking compared to Sham rats. A higher respiratory amplitude was also observed in 6-OHDA rats during both quiet waking and exploration. No effect of the treatment was noted during sleep. Given the relation between respiration and olfaction and the presence of olfactory deficits in PD patients, we then investigated the odor-evoked sniffing response in PD rats, using an odor habituation/cross-habituation paradigm. No substantial differences were observed in olfactory abilities between the two groups, as assessed through sniffing frequency. These results corroborate the hypothesis that respiratory impairments in 6-OHDA rats are vigilance-dependent. Our results also shed light on the importance of considering the behavioral state as an impacting factor when analyzing respiration.

Pharmacological inhibition of S6K1 rescues synaptic deficits and attenuates seizures and depression in chronic epileptic rats

BACKGROUND

Recent studies have shown that mTOR signaling plays an important role in synaptic plasticity. However, the function of S6K1, the mechanistic target of rapamycin kinase complex 1 (mTORC1) substrate, in epilepsy remains unknown.

AIMS

Our present study aimed to explore the mechanism by which S6K1 is involved in chronic epilepsy.

METHODS

First, immunostaining was used to measure neurite length and complexity in kainic acid (KA)-treated primary cultured neurons treated with PF-4708671, a highly selective S6K1 inhibitor. We obtained evidence for the role of S6K1 in protecting and promoting neuronal growth and development in vitro. Next, to explore the function and mechanism of the S6K1 inhibitor in epilepsy, a pilocarpine-induced chronic epileptic rat model was established. In vivo electrophysiology (including local field potentiation in CA1 and long-term potentiation), depression/anxiety-like behavior tests, and Golgi staining were performed to assess seizure behavior, power spectral density, depression/anxiety-like behavior, and synaptic plasticity. Furthermore, western blotting was applied to explore the potential molecular mechanisms.

RESULTS

We found that inhibition of S6K1 expression significantly decreased seizures and depression-like behavior and restored power at low frequencies (1-80 Hz), especially in the delta, theta, and alpha bands, in chronic epileptic rats. In addition, PF-4708671 reversed the LTP defect in hippocampal CA3-CA1 and corrected spine loss and dendritic pathology.

CONCLUSION

In conclusion, our data suggest that inhibition of S6K1 attenuates seizures and depression in chronic epileptic rats via the rescue of synaptic structural and functional deficits. Given the wide range of physiological functions of mTOR, inhibition of its effective but relatively simple functional downstream molecules is a promising target for the development of drugs for epilepsy.

The pros and cons of using automated sleep scoring in sleep research

Sleep scoring plays a pivotal role both in sleep research and in clinical practice. Traditionally, this process has relied on manual scoring by human experts, but it is marred by time constraints, and inconsistencies between different scorers. Consequently, the quest for more efficient and reliable approaches has sparked a great interest in the realm of automatic sleep-scoring methods. In this article, we provide an exploration of the merits and drawbacks of automatic sleep scoring, alongside the pressing challenges and critical considerations that demand attention in this evolving field.

Isoflurane impairs olfaction by increasing neuronal activity in the olfactory bulb

AIM

General anesthesia can induce cognitive deficits in both humans and rodents, correlating with pathological alterations in the hippocampus. However, whether general anesthesia affects olfactory behaviors remains controversial as clinical studies have produced inconsistent results. Therefore, we aimed to investigate how olfactory behaviors and neuronal activity are affected by isoflurane exposure in adult mice.

METHODS

The olfactory detection test, olfactory sensitivity test, and olfactory preference/avoidance test were used to examine olfactory function. In vivo electrophysiology was performed in awake, head-fixed mice to record single-unit spiking and local field potentials in the olfactory bulb (OB). We also performed patch-clamp recordings of mitral cell activity. For morphological studies, immunofluorescence and Golgi-Cox staining were applied.

RESULTS

Repeated exposure to isoflurane impaired olfactory detection in adult mice. The main olfactory epithelium, the first region exposed to anesthetics, displayed increased proliferation of basal stem cells. In the OB, a crucial hub for olfactory processing, repeated isoflurane exposure increased the odor responses of mitral/tufted cells. Furthermore, the odor-evoked high gamma response was decreased after isoflurane exposure. Whole-cell recordings further indicated that repeated isoflurane exposure increased the excitability of mitral cells, which may be due to weakened inhibitory input in isoflurane-exposed mice. In addition, elevated astrocyte activation and glutamate transporter-1 expression in the OB were observed in isoflurane-exposed mice.

CONCLUSIONS

Our findings indicate that repeated isoflurane exposure impairs olfactory detection by increasing neuronal activity in the OB in adult mice.

State-dependent coupling of hippocampal oscillations

Oscillations occurring simultaneously in a given area represent a physiological unit of brain states. They allow for temporal segmentation of spikes and support distinct behaviors. To establish how multiple oscillatory components co-vary simultaneously and influence neuronal firing during sleep and wakefulness in mice, we describe a multivariate analytical framework for constructing the state space of hippocampal oscillations. Examining the co-occurrence patterns of oscillations on the state space, across species, uncovered the presence of network constraints and distinct set of cross-frequency interactions during wakefulness compared to sleep. We demonstrated how the state space can be used as a canvas to map the neural firing and found that distinct neurons during navigation were tuned to different sets of simultaneously occurring oscillations during sleep. This multivariate analytical framework provides a window to move beyond classical bivariate pipelines for investigating oscillations and neuronal firing, thereby allowing to factor-in the complexity of oscillation-population interactions.

Spotlight on Sleep Stage Classification Based on EEG

The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG], and electromyography [EMG]), derived from the Rechtschaffen and Kales manual, were published in 2007 at the initiative of the American Academy of Sleep Medicine, and regularly updated over years. They offer an important tool to assess objective markers in different types of sleep/wake subjective complaints. With the aims and advantages of simplicity, reproducibility and standardization of practices in research and, most of all, in sleep medicine, they have overall changed little in the way they describe sleep. However, our knowledge on sleep/wake physiology and sleep disorders has evolved since then. High-density electroencephalography and intracranial electroencephalography studies have highlighted local regulation of sleep mechanisms, with spatio-temporal heterogeneity in vigilance states. Progress in the understanding of sleep disorders has allowed the identification of electrophysiological biomarkers better correlated with clinical symptoms and outcomes than standard sleep parameters. Finally, the huge development of sleep medicine, with a demand for explorations far exceeding the supply, has led to the development of alternative studies, which can be carried out at home, based on a smaller number of electrophysiological signals and on their automatic analysis. In this perspective article, we aim to examine how our description of sleep has been constructed, has evolved, and may still be reshaped in the light of advances in knowledge of sleep physiology and the development of technical recording and analysis tools. After presenting the strengths and limitations of the classification of sleep stages, we propose to challenge the "EEG-EOG-EMG" paradigm by discussing the physiological signals required for sleep stages identification, provide an overview of new tools and automatic analysis methods and propose avenues for the development of new approaches to describe and understand sleep/wake states.

Decoding behavior from global cerebrovascular activity using neural networks

Functional Ultrasound (fUS) provides spatial and temporal frames of the vascular activity in the brain with high resolution and sensitivity in behaving animals. The large amount of resulting data is underused at present due to the lack of appropriate tools to visualize and interpret such signals. Here we show that neural networks can be trained to leverage the richness of information available in fUS datasets to reliably determine behavior, even from a single fUS 2D image after appropriate training. We illustrate the potential of this method with two examples: determining if a rat is moving or static and decoding the animal's sleep/wake state in a neutral environment. We further demonstrate that our method can be transferred to new recordings, possibly in other animals, without additional training, thereby paving the way for real-time decoding of brain activity based on fUS data. Finally, the learned weights of the network in the latent space were analyzed to extract the relative importance of input data to classify behavior, making this a powerful tool for neuroscientific research.

Reciprocal relationships between sleep and smell

Despite major anatomical differences with other mammalian sensory systems, olfaction shares with those systems a modulation by sleep/wake states. Sleep modulates odor sensitivity and serves as an important regulator of both perceptual and associative odor memory. In addition, however, olfaction also has an important modulatory impact on sleep. Odors can affect the latency to sleep onset, as well as the quality and duration of sleep. Olfactory modulation of sleep may be mediated by direct synaptic interaction between the olfactory system and sleep control nuclei, and/or indirectly through odor modulation of arousal and respiration. This reciprocal interaction between sleep and olfaction presents novel opportunities for sleep related modulation of memory and perception, as well as development of non-pharmacological olfactory treatments of simple sleep disorders.

Discriminating Sleep From Freezing With Cortical Spindle Oscillations

In-vivo longitudinal recordings require reliable means to automatically discriminate between distinct behavioral states, in particular between awake and sleep epochs. The typical approach is to use some measure of motor activity together with extracellular electrophysiological signals, namely the relative contribution of theta and delta frequency bands to the Local Field Potential (LFP). However, these bands can partially overlap with oscillations characterizing other behaviors such as the 4 Hz accompanying rodent freezing. Here, we first demonstrate how standard methods fail to discriminate between sleep and freezing in protocols where both behaviors are observed. Then, as an alternative, we propose to use the smoothed cortical spindle power to detect sleep epochs. Finally, we show the effectiveness of this method in discriminating between sleep and freezing in our recordings.

Network and synaptic mechanisms underlying high frequency oscillations in the rat and cat olfactory bulb under ketamine-xylazine anesthesia

Wake-related ketamine-dependent high frequency oscillations (HFO) can be recorded in local field potentials (LFP) from cortical and subcortical regions in rodents. The mechanisms underlying their generation and occurrence in higher mammals are unclear. Unfortunately, anesthetic doses of pure ketamine attenuate HFO, which has precluded their investigation under anesthesia. Here, we show ketamine-xylazine (KX) anesthesia is associated with a prominent 80–130 Hz rhythm in the olfactory bulb (OB) of rats, whereas 30–65 Hz gamma power is diminished. Simultaneous LFP and thermocouple recordings revealed the 80–130 Hz rhythm was dependent on nasal respiration. This rhythm persisted despite surgical excision of the piriform cortex. Silicon probes spanning the dorsoventral aspect of the OB revealed this rhythm was strongest in ventral areas and associated with microcurrent sources about the mitral layer. Pharmacological microinfusion studies revealed dependency on excitatory-inhibitory synaptic activity, but not gap junctions. Finally, a similar rhythm occurred in the OB of KX-anesthetized cats, which shared key features with our rodent studies. We conclude that the activity we report here is driven by nasal airflow, local excitatory-inhibitory interactions, and conserved in higher mammals. Additionally, KX anesthesia is a convenient model to investigate further the mechanisms underlying wake-related ketamine-dependent HFO.

EEG, MEG and neuromodulatory approaches to explore cognition: Current status and future directions

Neural oscillations and their association with brain states and cognitive functions have been object of extensive investigation over the last decades. Several electroencephalography (EEG) and magnetoencephalography (MEG) analysis approaches have been explored and oscillatory properties have been identified, in parallel with the technical and computational advancement. This review provides an up-to-date account of how EEG/MEG oscillations have contributed to the understanding of cognition. Methodological challenges, recent developments and translational potential, along with future research avenues, are discussed.

Ramelteon modulates gamma oscillations in the rat primary motor cortex during non-REM sleep

Sleep disorders adversely affect daily activities and cause physiological and psychiatric problems. The shortcomings of benzodiazepine hypnotics have led to the development of ramelteon, a melatonin MT1 and MT2 agonist. Although the sleep-promoting effects of ramelteon have been documented, few studies have precisely investigated the structure of sleep and neural oscillatory activities. In this study, we recorded electrocorticograms in the primary motor cortex, the primary somatosensory cortex and the olfactory bulb as well as electromyograms in unrestrained rats treated with either ramelteon or vehicle. A neural-oscillation-based algorithm was used to classify the behavior of the rats into three vigilance states (e.g., awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep). Moreover, we investigated the region-, frequency- and state-specific modulation of extracellular oscillations in the ramelteon-treated rats. We demonstrated that in contrast to benzodiazepine treatment, ramelteon treatment promoted NREM sleep and enhanced fast gamma power in the primary motor cortex during NREM sleep, while REM sleep was unaffected. Gamma oscillations locally coordinate neuronal firing, and thus, ramelteon modulates neural oscillations in sleep states in a unique manner and may contribute to off-line information processing during sleep.

Acute Ramelteon Treatment Maintains the Cardiac Rhythms of Rats during Non-REM Sleep

Sleep curtailment negatively affects cardiac activities and thus should be ameliorated by pharmacological methods. One of the therapeutic targets is melatonin receptors, which tune circadian rhythms. Ramelteon, a melatonin MT1/MT2 receptor agonist, has recently been developed to modulate sleep-wake rhythms. To date, the sleep-promoting effect of ramelteon has been widely delineated, but whether ramelteon treatment physiologically influences cardiac function is not well understood. To address this question, we recorded electrocardiograms, electromyograms, and electrocorticograms in the frontal cortex and the olfactory bulb of unrestrained rats treated with either ramelteon or vehicle. We detected vigilance states based on physiological measurements and analyzed cardiac and muscular activities. We found that during non-rapid eye movement (non-REM) sleep, heartrate variability was maintained by ramelteon treatment. Analysis of the electromyograms confirmed that neither microarousal during non-REM sleep nor the occupancy of phasic periods during REM sleep was altered by ramelteon. Our results indicate that ramelteon has a remedial effect on cardiac activity by keeping the heartrate variability and may reduce cardiac dysfunction during sleep.

Identification of the sleep-wake states in rats using the high-frequency activity of the electroencephalogram

The electroencephalographic signal constitutes the main sign classically used for the identification of states of alertness. However, activities in the high frequency (>100 Hz) range have not been properly studied despite their high potential for sleep scoring in rodents. In the present study, we designed a method for the identification of the sleep-wake states in rats by exclusively using high-frequency activities of the electroencephalogram. By calculating the ratio between the amplitude of the electroencephalographic signal from 110 to 200 Hz and from 110 to 300 Hz, we obtained an index that had values that were low during wakefulness, intermediate during non-REM sleep and high during REM sleep. This high-frequency index (HiFI) allowed the identification of each state without the need to study other signs such as muscle activity or eye movements. To evaluate the performance of the index, we compared it with the conventional scoring of the sleep-wake cycle based upon the study of the electromyogram and delta (0.5-4 Hz), theta (6-9 Hz) and sigma (10-14 Hz) bands of the electroencephalogram. The index had an accuracy of 90.43 ± 1.91% (Cohen's kappa value of 0.82), confirming that the study of the high-frequency activities of the electroencephalogram was sufficient to reliably identify alertness states in the rat. Compared to other sleep-scoring methods, the HiFI has several advantages. It only requires one electroencephalography electrode, thus reducing the severity of the surgical preparation of the experimental animal, and its calculation is very simple, so it can be easily implemented online to classify sleep-wake states in real time.

Effect of Xylazine-Tiletamine-Zolazepam on the Local Field Potential of the Rat Olfactory Bulb

Neural oscillations of the mammalian olfactory system have been studied for decades. This research suggests they are linked to various processes involved in odor information analysis, depending on the vigilance state and presentation of stimuli. In addition, the effects of various anesthetics, including commonly used ones like chloral hydrate, pentobarbital, ketamine, and urethane, on the local field potential (LFP) in the olfactory bulb (OB) have been studied. In particular, the combination of xylazine and tiletamine-zolazepam has been shown to produce steady anesthesia for an extended period and relatively few adverse effects; however, their effects on the LFP in the OB remain unknown. To study those effects, we recorded the LFP in the OB of rats under xylazine-tiletamine-zolazepam anesthesia. During the period of anesthesia, the spectral powers of the 1-4, 9-16, 31-64, 65-90 frequency bands increased significantly, and that of 91-170 Hz frequency band decreased significantly, whereas no significant changes were observed in the 5-8 and 17-30 Hz ranges. These results reveal dynamic changes in the time and frequency characteristics of the LFP in the OB of rats under xylazine-tiletamine- zolazepam anesthesia and suggest that this combination of anesthetics could be used for studying oscillatory processes in the OB of rats.

Understanding the interplay of sleep and aging: Methodological challenges

In quest of new avenues to explain, predict, and treat pathophysiological conditions during aging, research on sleep and aging has flourished. Despite the great scientific potential to pinpoint mechanistic pathways between sleep, aging, and pathology, only little attention has been paid to the suitability of analytic procedures applied to study these interrelations. On the basis of electrophysiological sleep and structural brain data of healthy younger and older adults, we identify, illustrate, and resolve methodological core challenges in the study of sleep and aging. We demonstrate potential biases in common analytic approaches when applied to older populations. We argue that uncovering age-dependent alterations in the physiology of sleep requires the development of adjusted and individualized analytic procedures that filter out age-independent interindividual differences. Age-adapted methodological approaches are thus required to foster the development of valid and reliable biomarkers of age-associated cognitive pathologies.

Robust, automated sleep scoring by a compact neural network with distributional shift correction

Studying the biology of sleep requires the accurate assessment of the state of experimental subjects, and manual analysis of relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram and electromyogram data has shown great promise as a sleep scoring method, approaching the limits of inter-rater reliability. As with any machine learning algorithm, the inputs to a sleep scoring classifier are typically standardized in order to remove distributional shift caused by variability in the signal collection process. However, in scientific data, experimental manipulations introduce variability that should not be removed. For example, in sleep scoring, the fraction of time spent in each arousal state can vary between control and experimental subjects. We introduce a standardization method, mixture z-scoring, that preserves this crucial form of distributional shift. Using both a simulated experiment and mouse in vivo data, we demonstrate that a common standardization method used by state-of-the-art sleep scoring algorithms introduces systematic bias, but that mixture z-scoring does not. We present a free, open-source user interface that uses a compact neural network and mixture z-scoring to allow for rapid sleep scoring with accuracy that compares well to contemporary methods. This work provides a set of computational tools for the robust automation of sleep scoring.