Hippocampal and cortical communication around micro-arousals in slow-wave sleep

Serotonin modulates infraslow oscillation in the dentate gyrus during Non-REM sleep

Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with electrophysiological and optical imaging tools during sleep-wake cycles. We found that the activity of major glutamatergic cell populations in the DG is organized into in-fraslow oscillations (0.01 - 0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep. Further experiments revealed that the infraslow oscillation in the DG is modulated by rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by 5-HT1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.

Correlation between serum leptin level and sleep monitoring indexes in patients with obstructive sleep apnea hypopnea syndrome and its predictive value: a cross-sectional analysis

Objective

To investigate the association between serum leptin (LP) level and polysomnography (PSG) parameters in patients with obstructive sleep apnea hypopnea syndrome (OSAHS).

Methods

A cross-sectional study was conducted. The data of subjects who underwent PSG at hospital between January 2021 and December 2022 were collected retrospectively, 220 participants were included. The subjects were categorized into simple snoring group (n = 45), mild OSAHS group (n = 63), moderate OSAHS group (n = 52), and severe OSAHS group (n = 60). The general characteristics, PSG indices, and serological indices were collected retrospectively. Pearson correlation analysis was used to observe the correlation between serum LP level and PSG parameters. The value of serum LP level in predicting OSAHS was analyzed by receiver operating characteristic curve.

Results

The serum LP level was positively correlated with micro-arousal count, micro-arousal index (MAI), high apnea hypopnea index, times of blood oxygen decreased by≥3% and time in saturation lower 90%, and negatively correlated with lowest nocturnal oxygen saturation and mean oxygen saturation (p < 0.05). The area under the curve (AUC) of serum LP level in predicting the occurrence of OSAHS was 0.8276 (95% CI: 0.7713-0.8839), and when the Youden index was 0.587, the sensitivity was 72.00%, and the specificity was 86.67% (p < 0.0001). In the population with high MAI, the AUC of serum LP level in predicting the occurrence of OSAHS was 0.8825 (95% CI: 0.7833-0.9817), and when the Youden index was 0.690, the sensitivity was 79.00% and the specificity was 90.00% (p < 0.0001).

Conclusion

Serum LP level is associated with the severity of OSAHS. Serum LP level demonstrates a strong predictive value for the occurrence of OSAHS, particularly in population with high MAI.

Changes of Serum Adiponectin Level in Patients with Obstructive Sleep Apnea Hypopnea Syndrome and Its Relationship with Sleep Monitoring Indexes

Objective

To observe the changes of serum adiponectin (AP) levels in patients with obstructive sleep apnea hypopnea syndrome (OSAHS) and explore the correlation between serum AP and polysomnography (PSG) parameters in patients with OSAHS.

Methods

The data of subjects who underwent PSG at the hospital between January 2021 and December 2022 were collected retrospectively and divided into simple snoring group (AHI < 5 times/h, n = 45), mild OSAHS group (5 ≤ AHI < 15 times/h, n = 63), moderate OSAHS group (15 ≤ AHI ≤ 30 times/h, n = 52), and severe OSAHS group (AHI > 30 times/h, n = 60). The general data, PSG indices, and serological indices of the subjects were collected and compared between groups. Pearson correlation analysis and partial correlation analysis were employed to examine the correlation between serum AP level and PSG parameters. Ordered logistic regression was employed to analyze the risk factors influencing the severity of OSAHS. The predictive capability of the serum AP level in determining the occurrence of OSAHS was assessed using ROC. The serum AP levels of subjects with different subtypes of PSG indicators were compared.

Results

In the simple snoring group, mild OSAHS group, moderate OSAHS group, and severe OSAHS group, there were statistically significant differences in microarousal count, MAI, AHI, times of blood oxygen decreased by ≥ 3%, L-SaO2, and TS90% among the 4 groups (P < 0.05). The level of serum AP was positively correlated with L-SaO2 and negatively correlated with the proportion of REM, microarousal count, MAI, AHI, times of blood oxygen decreased by ≥ 3%, TS90%, and LP (P < 0.05). High AHI was a risk factor affecting the severity of OSAHS (95% CI: 1.446-4.170). The AUC of serum AP level in diagnosing OSAHS was 0.906 (95% CI: 0.8601-0.9521), and when the Youden Index was 0.678, the sensitivity was 88.9%, and the specificity was 78.9% (P < 0.0001). In the population with a high microarousal count, high AHI, and high times of blood oxygen decreased by ≥ 3% and high TS90%, the serum AP level was lower than that in the low-level population (P < 0.05). In the population with high L-SaO2, the serum AP level was higher than that in low-level population (P < 0.05).

Conclusion

The level of serum AP decreased with the increase of the disease severity of patients with OSAHS and demonstrates a significant predictive capability for the occurrence of OSAHS. Monitoring the level of serum AP can effectively forecast the risk of OSAHS. Furthermore, alterations in serum AP levels are associated with both hypoxemia and a heightened frequency of arousal in patients with OSAHS.

Sleep scoring in rodents: Criteria, automatic approaches and outstanding issues

There is nothing we spend as much time on in our lives as we do sleeping, which makes it even more surprising that we currently do not know why we need to sleep. Most of the research addressing this question is performed in rodents to allow for invasive, mechanistic approaches. However, in contrast to human sleep, we currently do not have shared and agreed upon standards on sleep states in rodents. In this article, we present an overview on sleep stages in humans and rodents and a historical perspective on the development of automatic sleep scoring systems in rodents. Further, we highlight specific issues in rodent sleep that also call into question some of the standards used in human sleep research.

Sleep restores an optimal computational regime in cortical networks

Sleep is assumed to subserve homeostatic processes in the brain; however, the set point around which sleep tunes circuit computations is unknown. Slow-wave activity (SWA) is commonly used to reflect the homeostatic aspect of sleep; although it can indicate sleep pressure, it does not explain why animals need sleep. This study aimed to assess whether criticality may be the computational set point of sleep. By recording cortical neuron activity continuously for 10-14 d in freely behaving rats, we show that normal waking experience progressively disrupts criticality and that sleep functions to restore critical dynamics. Criticality is perturbed in a context-dependent manner, and waking experience is causal in driving these effects. The degree of deviation from criticality predicts future sleep/wake behavior more accurately than SWA, behavioral history or other neural measures. Our results demonstrate that perturbation and recovery of criticality is a network homeostatic mechanism consistent with the core, restorative function of sleep.

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.

Regulation of stress-induced sleep fragmentation by preoptic glutamatergic neurons

Sleep disturbances are detrimental to our behavioral and emotional well-being. Stressful events disrupt sleep, in particular by inducing brief awakenings (microarousals, MAs), resulting in sleep fragmentation. The preoptic area of the hypothalamus (POA) is crucial for sleep control. However, how POA neurons contribute to the regulation of MAs and thereby impact sleep quality is unknown. Using fiber photometry in mice, we examine the activity of genetically defined POA subpopulations during sleep. We find that POA glutamatergic neurons are rhythmically activated in synchrony with an infraslow rhythm in the spindle band of the electroencephalogram during non-rapid eye movement sleep (NREMs) and are transiently activated during MAs. Optogenetic stimulation of these neurons promotes MAs and wakefulness. Exposure to acute social defeat stress fragments NREMs and significantly increases the number of transients in the calcium activity of POA glutamatergic neurons during NREMs. By reducing MAs, optogenetic inhibition during spontaneous sleep and after stress consolidates NREMs. Monosynaptically restricted rabies tracing reveals that POA glutamatergic neurons are innervated by brain regions regulating stress and sleep. In particular, presynaptic glutamatergic neurons in the lateral hypothalamus become activated after stress, and stimulating their projections to the POA promotes MAs and wakefulness. Our findings uncover a novel circuit mechanism by which POA excitatory neurons regulate sleep quality after stress.

Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitions

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and current computational annotation methods ignore intermediate states because the classification features become ambiguous, even though intermediate states contain important information regarding vigilance state dynamics. To address this problem, we have developed "Somnotate"-a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). First we demonstrate that Somnotate sets new standards in polysomnography, exhibiting annotation accuracies that exceed human experts on mouse electrophysiological data, remarkable robustness to errors in the training data, compatibility with different recording configurations, and an ability to maintain high accuracy during experimental interventions. However, the key feature of Somnotate is that it quantifies and reports the certainty of its annotations. We leverage this feature to reveal that many intermediate vigilance states cluster around state transitions, whereas others correspond to failed attempts to transition. This enables us to show for the first time that the success rates of different types of transition are differentially affected by experimental manipulations and can explain previously observed sleep patterns. Somnotate is open-source and has the potential to both facilitate the study of sleep stage transitions and offer new insights into the mechanisms underlying sleep-wake dynamics.

Electrophysiological damage to neuronal membrane alters ephaptic entrainment

The brain is commonly understood as a complex network system with a particular organization and topology that can result in specific electrophysiological patterns. Among all the dynamic elements resulting from the circuits of the brain's network, ephapticity is a cellular communication mechanism that has received little attention. To understand the network's properties of ephaptic entrainment, we start investigating the ephaptic effect on a single neuron. In this study, we used numerical simulations to examine the relationship between alterations in ephaptic neuronal entrainment and impaired electrophysiological properties of the neuronal membrane, which can occur via spike field coherence (SFC). This change in frequency band amplitude is observed in some neurodegenerative diseases, such as Parkinson's or Alzheimer's. To further investigate these phenomena, we proposed a damaged model based on the impairment of both the resistance of the ion channels and the capacitance of the lipid membrane. Therefore, we simulated ephaptic entrainment with the hybrid neural model quadratic integrate-and-fire ephaptic (QIF-E), which mimics an ephaptic entrainment generated by an LFP (simulate a neuronal group). Our results indicate a link between peak entrainment (ephapticity) preference and a shift in frequency band when damage occurs mainly in ion channels. Finally, we discuss possible relationships between ephaptic entrainment and neurodegenerative diseases associated with aging factors.

A noradrenergic-hypothalamic neural substrate for stress-induced sleep disturbances

In our daily life, we are exposed to uncontrollable and stressful events that disrupt our sleep. However, the underlying neural mechanisms deteriorating the quality of non-rapid eye movement sleep (NREMs) and REM sleep are largely unknown. Here, we show in mice that acute psychosocial stress disrupts sleep by increasing brief arousals (microarousals [MAs]), reducing sleep spindles, and impairing infraslow oscillations in the spindle band of the electroencephalogram during NREMs, while reducing REMs. This poor sleep quality was reflected in an increased number of calcium transients in the activity of noradrenergic (NE) neurons in the locus coeruleus (LC) during NREMs. Opto- and chemogenetic LC-NE activation in naïve mice is sufficient to change the sleep microarchitecture similar to stress. Conversely, chemogenetically inhibiting LC-NE neurons reduced MAs during NREMs and normalized their number after stress. Specifically inhibiting LC-NE neurons projecting to the preoptic area of the hypothalamus (POA) decreased MAs and enhanced spindles and REMs after stress. Optrode recordings revealed that stimulating LC-NE fibers in the POA indeed suppressed the spiking activity of POA neurons that are activated during sleep spindles and REMs and inactivated during MAs. Our findings reveal that changes in the dynamics of the stress-regulatory LC-NE neurons during sleep negatively affect sleep quality, partially through their interaction with the POA.

An open-source, ready-to-use and validated ripple detector plugin for the Open Ephys GUI

OBJECTIVE

Sharp wave-ripples (SWRs, 100-250 Hz) are oscillatory events extracellularly recorded in the CA1 subfield of the hippocampus during sleep and quiet wakefulness. Many studies employed closed-loop strategies to either detect and abolish SWRs within the hippocampus or manipulate other relevant areas upon ripple detection. However, the code and schematics necessary to replicate the detection system are not always available, which hinders the reproducibility of experiments among different research groups. Furthermore, information about performance is not usually reported. Here, we sought to provide an open-source, validated ripple detector for the scientific community.

APPROACH

We developed and validated a ripple detection plugin integrated into the Open Ephys GUI. It contains a built-in movement detector based on accelerometer or electromyogram data that prevents false ripple events (due to chewing, grooming, or moving, for instance) from triggering the stimulation/manipulation device.

MAIN RESULTS

To determine the accuracy of the detection algorithm, we first carried out simulations in Matlab with real ripple recordings. Using a specific combination of detection parameters (amplitude threshold of 5 standard deviations above the mean, time threshold of 10 ms, and RMS block size of 7 samples), we obtained a 97% true positive rate and 2.48 false positives per minute. Next, an Open Ephys plugin based on the same detection algorithm was developed, and a closed-loop system was set up to evaluate the round trip (ripple onset-to-stimulation) latency over synthetic data. The lowest latency obtained was 34.5 ± 0.5 ms. The embedded movement monitoring was effective in reducing false positives and the plugin's flexibility to detect pathological events was also verified.

SIGNIFICANCE

Besides contributing to increased reproducibility, we anticipate that the developed ripple detector plugin will be helpful for many closed-loop applications in the field of systems neuroscience.

Ephaptic entrainment in hybrid neuronal model

In recent decades, there has been a growing interest in the impact of electric fields generated in the brain. Transmembrane ionic currents originate electric fields in the extracellular space and are capable of affecting nearby neurons, a phenomenon called ephaptic neuronal communication. In the present work, the Quadratic Integrated-and-Fire model (QIF-E) underwent an adjustment/improvement to include the ephaptic entrainment behavior between neurons and electric fields. Indeed, the aim of our study is to validate the QIF-E model, which is a model to estimate the influence of electric fields on neurons. For this purpose, we evaluated whether the main properties observed in an experiment by Anastassiou et al. (Nat Neurosci 14:217-223, 2011), which analyzed the effect of an electric field on cortical pyramidal neurons, are reproduced with the QIF-E model. In this way, the analysis tools are employed according to the neuronal activity regime: (i) for the subthreshold regime, the circular statistic is used to describe the phase differences between the input stimulus signal (electrode) and the modeled membrane response; (ii) in the suprathreshold regime, the Population Vector and the Spike Field Coherence are used to estimate phase preferences and the entrainment intensity between the input stimulus and Action Potentials. The results observed are (i) in the subthreshold regime the values of the phase differences change with distinct frequencies of the input stimulus; (ii) in the supra-threshold regime the preferential phase of Action Potentials changes for different frequencies. In addition, we explore other parameters of the model, such as noise and membrane characteristic-time, in order to understand different types of neurons and extracellular environment related to ephaptic communication. Such results are consistent with results observed in empirical experiments based on ephaptic phenomenon. In addition, the QIF-E model allows further studies on the physiological importance of ephaptic communication in the brain, and its simplicity may open a door to simulate the ephaptic response in neuronal networks and assess the impact of ephaptic communication in such scenarios.

Cyclic alternating patterns and arousals: what is relevant in obstructive sleep apnea? In Memoriam Mario Giovanni Terzano

PURPOSE OF REVIEW

To review main knowledges and gaps in the field of sleep microstructure, represented by the cyclic alternating pattern (CAP), in obstructive sleep apnea (OSA).

RECENT FINDINGS

The (electroencephalographic and autonomic) 'intensity' of arousals in OSA patients, measured through the metrics of CAP, correlate with OSA severity and with disease burden. Continuous positive airway pressure determines variations in sleep architecture (conventional parameters) and at the microstructural level, at different time points.

SUMMARY

CAP is not only an 'attractor' of arousals, but also organizes distribution of K-complexes and delta bursts in non-rapid eye movement sleep. Although attention is always concentrated on the A-phase of CAP, a crucial role is play by the phase B, which reflects a period of transient inhibition. Respiratory events in OSA are a typical example of phase B-associated condition, as they occur during the interval between successive A-phases. Accordingly sleep microstructure provides useful insights in the pathophysiology and estimation of OSA severity and may be exploited to follow-up treatment efficacy. In the complex relationship among sleep fragmentation, excessive daytime sleepiness, cognition and cardiovascular risk the CAP framework can offer an integrative perspective in a multidisciplinary scenario.

Sleep Instability Correlates with Attentional Impairment in Boys with Attention Deficit Hyperactivity Disorder

Theoretical models of sleep and attention deficit hyperactivity disorder (ADHD) suggest that symptoms of ADHD are associated with daytime sleepiness, but it has received little support. The present study aimed at testing an alternative model involving the association of attentional instability with sleep instability, i.e., sleep stage transitions and arousals. Twelve ADHD and 15 healthy control (HC) boys aged between 8 and 12 years old underwent polysomnography recording and attentional testing. The microarousal index, the number of awakenings, and the number of stage shifts between stages 1, 2, 3, 4 and REM sleep throughout the night were computed as sleep stability parameters. Attentional functioning was assessed using the Continuous Performance Test-II. We found significantly higher sleep instability in ADHD compared to HC. Sleep arousals and stage transitions (micro arousal index, stage 4/3 and 2/4 transitions) in ADHD significantly correlated with lower attentional scores. No association whatsoever was found between sleep instability and attentional functioning in HC. The results show that sleep instability is associated with lower attentional performance in boys with ADHD, but not in HC. This could be compatible with a model according to which attention and sleep stability share a common neural substrate in ADHD.

Multi-scale neural decoding and analysis

Objective.

Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment.

Approach.

We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes.

Main results.

We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches.

Significance.

This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.

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.

Low-cost and versatile electrodes for extracellular chronic recordings in rodents

Electrophysiological data are used to investigate fundamental properties of brain function, its relation to cognition, and its dysfunction in diseases. The development of reliable and open-source systems for electrophysiological data acquisition is decreasing the total cost of constructing and operating an electrophysiology laboratory, and facilitates low-cost methods to extract and analyze the data (Siegle et al., 2017). Here we detail our method of building custom-designed low-cost electrodes. These electrodes can be customized and manufactured by any researcher to address a broad set of research questions, further decreasing the final cost of an implanted animal. Finally, we present data showing such an electrode has a good signal quality to record LFP.

Disruption of neocortical synchronisation during slow-wave sleep in the rotenone model of Parkinson's disease

Parkinson's disease motor dysfunctions are associated with improperly organised neural oscillatory activity. The presence of such disruption at the early stages of the disease in which altered sleep is one of the main features could be a relevant predictive feature. Based on this, we aimed to investigate the neocortical synchronisation dynamics during slow-wave sleep (SWS) in the rotenone model of Parkinson's disease. After rotenone administration within the substantia nigra pars compacta, one group of male Wistar rats underwent sleep-wake recording. Considering the association between SWS oscillatory activity and memory consolidation, another group of rats underwent a memory test. The fine temporal structure of synchronisation dynamics was evaluated by a recently developed technique called first return map. We observed that rotenone administration decreased the time spent in SWS and altered the power spectrum within different frequency bands, whilst it increased the transition rate from a synchronised to desynchronised state. This neurotoxin also increased the probability of longer and decreased the probability of shorter desynchronisation events. At the same time, we observed impairment in object recognition memory. These findings depict an electrophysiological fingerprint represented by a disruption in the typical oscillatory activity within the neocortex at the early stages of Parkinson's disease, concomitant with a decrease in the time spent in SWS and impairment in recognition memory.