The transition from slow-wave sleep to paradoxical sleep: evolving facts and concepts of the neurophysiological processes underlying the intermediate stage of sleep

The "Twin Peaks" method of automated Spike-Wave detection: A two-step, two-criteria Matlab application

BACKGROUND

There are many automated spike-wave discharge detectors, but the known weaknesses of otherwise good methods and the varying working conditions of different research groups (mainly the access to hardware and software) invite further exploration into alternative approaches.

NEW METHOD

The algorithm combines two criteria, one in the time-domain and one in the frequency-domain, exploiting morphological asymmetry and the presence of harmonics, respectively. The time-domain criterion is additionally adjusted by normal modelling between the first and second iterations.

RESULTS

We report specificity, sensitivity and accuracy values for 20 recordings from 17 mature, male WAG/Rij rats. In addition, performance was preliminary tested with different hormones, pharmacological injections and species (mice) in a smaller sample. Accuracy and specificity were consistently above 91 %. The number of automatically detected spike-wave discharges was strongly correlated with the numbers derived from visual inspection. Sensitivity varied more strongly than specificity, but high values were observed in both rats and mice.

COMPARISON WITH EXISTING METHODS

The algorithm avoids low-voltage movement artifacts, displays a lower false positive rate than many predecessors and appears to work across species, i.e. while designed initially with data from the WAG/Rij rat, the algorithm can pick up seizure activity in the mouse of considerably lower inter-spike frequency. Weaknesses of the proposed method include a lower sensitivity than several predecessors.

CONCLUSION

The algorithm excels in being a selective and flexible (based on e.g. its performance across rats and mice) spike-wave discharge detector. Future work could attempt to increase the sensitivity of this approach.

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

BACKGROUND

Sleep 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 METHOD

We 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.

RESULTS

We 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 METHODS

The 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.

CONCLUSIONS

WUCSS, 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.

Effects of non-rapid eye movement sleep on the cortical synaptic expression of GluA1-containing AMPA receptors

Converging electrophysiological, molecular and ultrastructural evidence supports the hypothesis that sleep promotes a net decrease in excitatory synaptic strength, counteracting the net synaptic potentiation caused by ongoing learning during waking. However, several outstanding questions about sleep-dependent synaptic weakening remain. Here, we address some of these questions by using two established molecular markers of synaptic strength, the levels of the AMPA (alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors containing the GluA1 subunit and the phosphorylation of GluA1 at serine 845 (p-GluA1(845)). We previously found that, in the rat cortex and hippocampus, these markers are lower after 6-8 h of sleep than after the same time spent awake. Here, we measure GluA1 and p-GluA1(845) levels in synaptosomes of mouse cortex after 5 h of either sleep, sleep deprivation, recovery sleep after sleep deprivation or selective REM sleep deprivation (32 C57BL/B6 adult mice, 16 females). We find that relative to after sleep deprivation, these synaptic markers are lower after sleep independent of whether the mice were allowed to enter REM sleep. Moreover, 5 h of recovery sleep following acute sleep deprivation is enough to renormalize their expression. Thus, the renormalization of GluA1 and p-GluA1(845) expression crucially relies on NREM sleep and can occur in a few hours of sleep after acute sleep deprivation.

Homeostatic regulation of rapid eye movement sleep by the preoptic area of the hypothalamus

Rapid eye movement sleep (REMs) is characterized by activated electroencephalogram (EEG) and muscle atonia, accompanied by vivid dreams. REMs is homeostatically regulated, ensuring that any loss of REMs is compensated by a subsequent increase in its amount. However, the neural mechanisms underlying the homeostatic control of REMs are largely unknown. Here, we show that GABAergic neurons in the preoptic area of the hypothalamus projecting to the tuberomammillary nucleus (POAGAD2→TMN neurons) are crucial for the homeostatic regulation of REMs in mice. POAGAD2→TMN neurons are most active during REMs, and inhibiting them specifically decreases REMs. REMs restriction leads to an increased number and amplitude of calcium transients in POAGAD2→TMN neurons, reflecting the accumulation of REMs pressure. Inhibiting POAGAD2→TMN neurons during REMs restriction blocked the subsequent rebound of REMs. Our findings reveal a hypothalamic circuit whose activity mirrors the buildup of homeostatic REMs pressure during restriction and that is required for the ensuing rebound in REMs.

Homeostatic regulation of REM sleep by the preoptic area of the hypothalamus

Rapid-eye-movement sleep (REMs) is characterized by activated electroencephalogram (EEG) and muscle atonia, accompanied by vivid dreams. REMs is homeostatically regulated, ensuring that any loss of REMs is compensated by a subsequent increase in its amount. However, the neural mechanisms underlying the homeostatic control of REMs are largely unknown. Here, we show that GABAergic neurons in the preoptic area of the hypothalamus projecting to the tuberomammillary nucleus (POAGAD2→TMN neurons) are crucial for the homeostatic regulation of REMs. POAGAD2→TMN neurons are most active during REMs, and inhibiting them specifically decreases REMs. REMs restriction leads to an increased number and amplitude of calcium transients in POAGAD2→TMN neurons, reflecting the accumulation of REMs pressure. Inhibiting POAGAD2→TMN neurons during REMs restriction blocked the subsequent rebound of REMs. Our findings reveal a hypothalamic circuit whose activity mirrors the buildup of homeostatic REMs pressure during restriction and that is required for the ensuing rebound in REMs.

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.

A medullary hub for controlling REM sleep and pontine waves

Rapid-eye-movement (REM) sleep is a distinct behavioral state associated with vivid dreaming and memory processing. Phasic bursts of electrical activity, measurable as spike-like pontine (P)-waves, are a hallmark of REM sleep implicated in memory consolidation. However, the brainstem circuits regulating P-waves, and their interactions with circuits generating REM sleep, remain largely unknown. Here, we show that an excitatory population of dorsomedial medulla (dmM) neurons expressing corticotropin-releasing-hormone (CRH) regulates both REM sleep and P-waves in mice. Calcium imaging showed that dmM CRH neurons are selectively activated during REM sleep and recruited during P-waves, and opto- and chemogenetic experiments revealed that this population promotes REM sleep. Chemogenetic manipulation also induced prolonged changes in P-wave frequency, while brief optogenetic activation reliably triggered P-waves along with transiently accelerated theta oscillations in the electroencephalogram (EEG). Together, these findings anatomically and functionally delineate a common medullary hub for the regulation of both REM sleep and P-waves.

Electroencephalographic features of the developing brain in 72 dogs under xylazine sedation: a visual and statistical analysis

Electroencephalogram (EEG) is a neurophysiological test, which is widely used in human medicine for epilepsy diagnosis and other neurological disorders. For an adequate interpretation, it is necessary to know the electroencephalogram features for different stages of development. Despite the growing interest in its implementation in veterinary medicine, standardized descriptions of the EEG features of the different stages of brain development in dogs are restricted to studies with limited number of dogs and limited age groups. In this research, the electroencephalographic recording of 72 dogs of different breeds and ages was carried out under xylazine sedation to determine tracing characteristics by visual analysis and through statistical analysis of power spectrum. To establish the EEG features of recordings, 3 essential aspects were selected: (a) the presence or absence of slow waves of 4 to 6-7 Hz; (b) the comparison of the electrical activity recorded in the temporal and dorsal cortex channels; and (c) the visual increase of the alpha activity. Visual analysis on both reference and bipolar montage was performed by the authors and additionally blindly corroborated by two human neurophysiologists. The results allowed us to differentiate 5 age groups: 0-5, 6-11, 12-17, 18-23, and >24 months. Statistical analysis of the power spectrum was performed by analysis of variance (ANOVA) with a completely randomized design (CRD) under factorial arrangement by observing the effect of ages, channels and electroencephalographic rhythms on relative power. The results obtained matched those observed in the visual analysis. According to our results, the characteristics of the EEG corresponding to the adult animal begin to appear at 12 months of age but stabilize after 24 months of age. In this case, the evident differences in the processes of development and maturation of the neopallium and the rhinencephalon play a determining role. Our results differ from those obtained by other authors, probably due to the addition of a deep electrode that facilitates the recording of temporal cortical activity and its deeper rhinencephalic connections.

Memory-enhancing properties of sleep depend on the oscillatory amplitude of norepinephrine

Sleep has a complex micro-architecture, encompassing micro-arousals, sleep spindles and transitions between sleep stages. Fragmented sleep impairs memory consolidation, whereas spindle-rich and delta-rich non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep promote it. However, the relationship between micro-arousals and memory-promoting aspects of sleep remains unclear. In this study, we used fiber photometry in mice to examine how release of the arousal mediator norepinephrine (NE) shapes sleep micro-architecture. Here we show that micro-arousals are generated in a periodic pattern during NREM sleep, riding on the peak of locus-coeruleus-generated infraslow oscillations of extracellular NE, whereas descending phases of NE oscillations drive spindles. The amplitude of NE oscillations is crucial for shaping sleep micro-architecture related to memory performance: prolonged descent of NE promotes spindle-enriched intermediate state and REM sleep but also associates with awakenings, whereas shorter NE descents uphold NREM sleep and micro-arousals. Thus, the NE oscillatory amplitude may be a target for improving sleep in sleep disorders.

Comparative Assessment of TSPO Modulators on Electroencephalogram Activity and Exploratory Behavior

Network communication in the CNS relies upon multiple neuronal and glial signaling pathways. In addition to synaptic transmission, other organelles such as mitochondria play roles in cellular signaling. One highly conserved mitochondrial signaling mechanism involves the 18 kDa translocator protein (TSPO) of the outer mitochondrial membrane. Originally, TSPO was identified as a binding site for benzodiazepines in the periphery. It was later discovered that TSPO is found in mitochondria, including in CNS cells. TSPO is implicated in multiple cellular processes, including the translocation of cholesterol and steroidogenesis, porphyrin transport, cellular responses to stress, inflammation, and tumor progression. Yet the impacts of modulating TSPO signaling on network activity and behavioral performance have not been characterized. In the present study, we assessed the effects of TSPO modulators PK11195, Ro5-4864, and XBD-173 via electroencephalography (EEG) and the open field test (OFT) at low to moderate doses. Cortical EEG recordings revealed increased power in the δ and θ frequency bands after administration of each of the three modulators, as well as compound- and dose-specific changes in α and γ. Behaviorally, these compounds reduced locomotor activity in the OFT in a dose-dependent manner, with XBD-173 having the subtlest behavioral effects while still strongly modulating the EEG. These findings indicate that TSPO modulators, despite their diversity, exert similar effects on the EEG while displaying a range of sedative/hypnotic effects at moderate to high doses. These findings bring us one step closer to understanding the functions of TSPO in the brain and as a target in CNS disease.

Hydroalcoholic Extract of Ashwagandha Improves Sleep by Modulating GABA/Histamine Receptors and EEG Slow-Wave Pattern in In Vitro - In Vivo Experimental Models

Withania somnifera (ashwagandha) has been used traditionally as a remedy for insomnia and to enhance cognitive function. The effects of ashwagandha extract (AE, 35% withanolide glycosides, Shoden^Ⓡ) on the expression levels of γ-aminobutyric acid (GABA)_Aρ1 and histamine H3 receptors in Rattus norvegicus glioblastoma (C6) cell lines were studied using semiquantitative reverse transcriptase-polymerase chain reactions. The effects of AE on sleep onset and duration were studied in Swiss albino mice using the pentobarbital-induced sleep model. Furthermore, the effects on nonrapid eye movement (NREM) and rapid eye movement sleep patterns were studied in Wistar rats with electroencephalogram (EEG) to support the improvement in sleep quality. There was an increase in gene expression levels of GABA_Aρ1 receptor (1.38 and 1.94 folds) and histamine H3 (1.14 and 1.29 folds) receptors induced by AE at doses of 15 and 30 μg/mL compared to control. AE at doses of 10, 25, and 50 mg/kg body weight showed a significant decrease in time to sleep onset and increased total sleep duration in the pentobarbital-induced sleep model. At 50 mg/kg body weight dosage level, a 34% decrease (P<0.0001) in sleep onset time and 47% increase (P<0.0001) in sleep duration was observed. The EEG study showed significant improvement in alpha, beta, theta, delta, and gamma bands at doses of 10, 25, and 50 mg/kg body weight with delta waves showing increases of 30%, 46% (P<0.05), and 34%, respectively. The induction of sleep, GABA-mimetic action, NREM sleep, and the effects on slow-wave cycles support the calming property of AE in improving the quality of sleep.

Regulation of REM sleep by inhibitory neurons in the dorsomedial medulla

The two major stages of mammalian sleep-rapid eye movement sleep (REMs) and non-REM sleep (NREMs)-are characterized by distinct brain rhythms ranging from millisecond to minute-long (infraslow) oscillations. The mechanisms controlling transitions between sleep stages and how they are synchronized with infraslow rhythms remain poorly understood. Using opto- and chemogenetic manipulation in mice, we show that GABAergic neurons in the dorsomedial medulla (dmM) promote the initiation and maintenance of REMs, in part through their projections to the dorsal and median raphe nuclei. Fiber photometry revealed that their activity is strongly increased during REMs and fluctuates during NREMs in close synchrony with infraslow oscillations in the sleep spindle band of the electroencephalogram. The phase of this rhythm influenced the latency and probability with which dmM activation induced REMs. Thus, dmM inhibitory neurons strongly promote REMs, and their slow activity fluctuations may coordinate the timing of REMs episodes with infraslow brain rhythms.

Sleep Disturbances in Rats With Genetic Pre-disposition to Spike-Wave Epilepsy (WAG/Rij)

Wistar Albino Glaxo Rijswijk (WAG/Rij) rats are widely used in basic and pre-clinical studies as a valid genetic model of absence epilepsy. Adult WAG/Rij rats exhibit generalized 8–10-Hz spike-wave discharges (SWDs) in the electroencephalogram. SWDs are known to result from thalamocortical circuit dysfunction, and this implies an intimate relationship between slow-wave EEG activity, sleep spindles, and SWDs. The present mini review summarizes relevant research on sleep-related disturbances associated with spike-wave epilepsy in WAG/Rij rats in the domain of slow-wave sleep EEG and microarousals. It also discusses enhancement of the intermediate stage of sleep. In general, sleep EEG studies provide important information about epileptogenic processes related to spike-wave epilepsy.

Zopiclone to treat insomnia in older adults: A systematic review

Considering the global increase in use of Z-drugs to treat insomnia, the study objective was to conduct a systematic review on the efficacy and safety of zopiclone to treat sleep disorders in older adults compared to other sedative-hypnotics, to placebo or to non-pharmacological interventions. The literature search for original reports - clinical trials, cohort studies and cross-sectional, observational investigations - was done in eleven databases and web search engines followed PRISMA guidelines, and methodological quality was assessed using the Risk of Bias tool in the Cochrane Reviewers' Handbook. The search resulted in 12 randomized, placebo-controlled clinical trials along with 2 open studies and 2 observational reports. Overall, the studies suggest that zopiclone is effective to treat insomnia by reducing sleep latency, nocturnal awakenings and wake time after sleep onset while increasing total sleep time, with probable effects on sleep architecture. Zopiclone was found to be fairly tolerated, to induce a low rate of adverse events with non-severe impact on psychomotor or cognitive performance and to produce no major harm to the overall well-being and daily living abilities. However, the quality of most studies was classified as low or unclear. Though the studies available support benefits from zopiclone use, there is still a need for further evidence on long-term effects, tolerability and safety in the treatment of older adults by means of high-quality trials.

A probabilistic model for the ultradian timing of REM sleep in mice

A salient feature of mammalian sleep is the alternation between rapid eye movement (REM) and non-REM (NREM) sleep. However, how these two sleep stages influence each other and thereby regulate the timing of REM sleep episodes is still largely unresolved. Here, we developed a statistical model that specifies the relationship between REM and subsequent NREM sleep to quantify how REM sleep affects the following NREM sleep duration and its electrophysiological features in mice. We show that a lognormal mixture model well describes how the preceding REM sleep duration influences the amount of NREM sleep till the next REM sleep episode. The model supports the existence of two different types of sleep cycles: Short cycles form closely interspaced sequences of REM sleep episodes, whereas during long cycles, REM sleep is first followed by an interval of NREM sleep during which transitions to REM sleep are extremely unlikely. This refractory period is characterized by low power in the theta and sigma range of the electroencephalogram (EEG), low spindle rate and frequent microarousals, and its duration proportionally increases with the preceding REM sleep duration. Using our model, we estimated the propensity for REM sleep at the transition from NREM to REM sleep and found that entering REM sleep with higher propensity resulted in longer REM sleep episodes with reduced EEG power. Compared with the light phase, the buildup of REM sleep propensity was slower during the dark phase. Our data-driven modeling approach uncovered basic principles underlying the timing and duration of REM sleep episodes in mice and provides a flexible framework to describe the ultradian regulation of REM sleep in health and disease.

Automated scoring of pre-REM sleep in mice with deep learning

Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accuracies for the classical sleep stages of Wake, REM, and Non-REM. Meanwhile, it has been recognized that the statistics of transitional stages such as pre-REM, found between Non-REM and REM, may hold additional insight into the physiology of sleep and are now under vivid investigation. We propose a classification system based on a simple neural network architecture that scores the classical stages as well as pre-REM sleep in mice. When restricted to the classical stages, the optimized network showed state-of-the-art classification performance with an out-of-sample F1 score of 0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1 scores on pre-REM (0.5) compared to the classical stages. The result is comparable to previous attempts to score transitional stages in other species such as transition sleep in rats or N1 sleep in humans. Nevertheless, we observed that the sequence of predictions including pre-REM typically transitioned from Non-REM to REM reflecting sleep dynamics observed by human scorers. Our findings provide further evidence for the difficulty of scoring transitional sleep stages, likely because such stages of sleep are under-represented in typical data sets or show large inter-scorer variability. We further provide our source code and an online platform to run predictions with our trained network.

Shared and unique features of mammalian sleep spindles - insights from new and old animal models

Sleep spindles are phasic events observed in mammalian non-rapid eye movement sleep. They are relevant today in the study of memory consolidation, sleep quality, mental health and ageing. We argue that our advanced understanding of their mechanisms has not exhausted the utility and need for animal model work. This is both because some topics, like cognitive ageing, have not yet been addressed sufficiently in comparative efforts and because the evolutionary history of this oscillation is still poorly understood. Comparisons across species often are either limited to referencing the classical cat and rodent models, or are over-inclusive, uncritically including reports of sleep spindles in rarely studied animals. In this review, we discuss the emergence of new (dog and sheep) models for sleep spindles and compare the strengths and shortcomings of new and old models based on the three validation criteria for animal models - face, predictive, and construct validity. We conclude that an emphasis on cognitive ageing might dictate the future of comparative sleep spindle studies, a development that is already becoming visible in studies on dogs. Moreover, reconstructing the evolutionary history of sleep spindles will require more stringent criteria for their identification, across more species. In particular, a stronger emphasis on construct and predictive validity can help verify if spindle-like events in other species are actual sleep spindles. Work in accordance with such stricter validation suggests that sleep spindles display more universally shared features, like defining frequency, than previously thought.

A mechanism for learning with sleep spindles

Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

The Transition Between Slow-Wave Sleep and REM Sleep Constitutes an Independent Sleep Stage Organized by Cholinergic Mechanisms in the Rostrodorsal Pontine Tegmentum

There is little information on either the transition state occurring between slow-wave sleep (SWS) and rapid eye movement (REM) sleep, as well as about its neurobiological bases. This transition state, which is known as the intermediate state (IS), is well-defined in rats but poorly characterized in cats. Previous studies in our laboratory demonstrated that cholinergic stimulation of the perilocus coeruleus α nucleus (PLCα) in the pontine tegmentum of cats induced two states: wakefulness with muscle atonia and a state of dissociated sleep we have called the SPGO state. The SPGO state has characteristics in common with the IS, such including the presence of ponto-geniculo-occipital waves (PGO) and EEG synchronization with δ wave reduction. Therefore, the aims of the present study were (1) to characterize the IS in the cat and, (2), to study the analogy between the SPGO and the different sleep stages showing PGO activity, including the IS. Polygraphic recordings of 10 cats were used. In seven cats carbachol microinjections (20-30 nL, 0.01-0.1 M) were delivered in the PLCα. In the different states, PGO waves were analyzed and power spectra obtained for the δ, θ, α, and β bands of the EEG from the frontal and occipital cortices, and for the θ hippocampal band. Statistical comparisons were made between the values obtained from the different states. The results indicate that the IS constitutes a state with characteristics that are distinct from both the preceding SWS and the following REM sleep, and that SPGO presents a high analogy with the IS. Therefore, the SPGO state induced by administering carbachol in the PLCα nucleus seems to be an expression of the physiological IS of the cat. Consequently, we propose that the PLCα region, besides being involved in the mechanisms of muscle atonia, may also be responsible for organizing the transition from SWS to REM sleep.

Theta Oscillations Alternate With High Amplitude Neocortical Population Within Synchronized States

Synchronized states are marked by large-amplitude low-frequency oscillations in the cortex. These states can be seen during quiet waking or slow-wave sleep. Within synchronized states, previous studies have noted a plethora of different types of activity, including delta oscillations (0.5-4 Hz) and slow oscillations (<1 Hz) in the neocortex and large- and small- irregular activity in the hippocampus. However, it is not still fully characterized how neural populations contribute to the synchronized state. Here we apply independent component analysis to parse which populations are involved in different kinds of neocortical activity, and find two populations that alternate throughout synchronized states. One population broadly affects neocortical deep layers, and is associated with larger amplitude slower neocortical oscillations. The other population exhibits theta-frequency oscillations that are not easily observed in raw field potential recordings. These theta oscillations apparently come from below the neocortex, suggesting hippocampal origin, and are associated with smaller amplitude faster neocortical oscillations. Relative involvement of these two alternating populations may indicate different modes of operation within synchronized states.

Cortical region-specific sleep homeostasis in mice: effects of time of day and waking experience

Sleep–wake history, wake behaviors, lighting conditions, and circadian time influence sleep, but neither their relative contribution nor the underlying mechanisms are fully understood. The dynamics of electroencephalogram (EEG) slow-wave activity (SWA) during sleep can be described using the two-process model, whereby the parameters of homeostatic Process S are estimated using empirical EEG SWA (0.5–4 Hz) in nonrapid eye movement sleep (NREMS), and the 24 hr distribution of vigilance states. We hypothesized that the influence of extrinsic factors on sleep homeostasis, such as the time of day or wake behavior, would manifest in systematic deviations between empirical SWA and model predictions. To test this hypothesis, we performed parameter estimation and tested model predictions using NREMS SWA derived from continuous EEG recordings from the frontal and occipital cortex in mice. The animals showed prolonged wake periods, followed by consolidated sleep, both during the dark and light phases, and wakefulness primarily consisted of voluntary wheel running, learning a new motor skill or novel object exploration. Simulated SWA matched empirical levels well across conditions, and neither waking experience nor time of day had a significant influence on the fit between data and simulation. However, we consistently observed that Process S declined during sleep significantly faster in the frontal than in the occipital area of the neocortex. The striking resilience of the model to specific wake behaviors, lighting conditions, and time of day suggests that intrinsic factors underpinning the dynamics of Process S are robust to extrinsic influences, despite their major role in shaping the overall amount and distribution of vigilance states across 24 hr.

Absent sleep EEG spindle activity in GluA1 (Gria1) knockout mice: relevance to neuropsychiatric disorders

Sleep EEG spindles have been implicated in attention, sensory processing, synaptic plasticity and memory consolidation. In humans, deficits in sleep spindles have been reported in a wide range of neurological and psychiatric disorders, including schizophrenia. Genome-wide association studies have suggested a link between schizophrenia and genes associated with synaptic plasticity, including the Gria1 gene which codes for the GluA1 subunit of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor. Gria1^-/- mice exhibit a phenotype relevant for neuropsychiatric disorders, including reduced synaptic plasticity and, at the behavioural level, attentional deficits leading to aberrant salience. In this study we report a striking reduction of EEG power density including the spindle-frequency range (10-15 Hz) during sleep in Gria1^-/- mice. The reduction of spindle-activity in Gria1^-/- mice was accompanied by longer REM sleep episodes, increased EEG slow-wave activity in the occipital derivation during baseline sleep, and a reduced rate of decline of EEG slow wave activity (0.5-4 Hz) during NREM sleep after sleep deprivation. These data provide a novel link between glutamatergic dysfunction and sleep abnormalities in a schizophrenia-relevant mouse model.

Association of sleep impairments and gastrointestinal disorders in the context of the visceral theory of sleep

It was noticed long ago that sleep disorders or interruptions to the normal sleep pattern were associated with various gastrointestinal disorders. We review the studies which established the causal link between these disorders and sleep impairment. However, the mechanism of interactions between the quality of sleep and gastrointestinal pathophysiology remained unclear. Recently, the visceral theory of sleep was formulated. This theory proposes that the same brain structures, and particularly the same cortical sensory areas, which in wakefulness are involved in processing of the exteroceptive information, switch during sleep to the processing of information coming from various visceral systems. We review the studies which demonstrated that neurons of the various cortical areas (occipital, parietal, frontal) during sleep began to fire in response to activation coming from the stomach and small intestine. These data demonstrate that, during sleep, the computational power of the central nervous system, including all cortical areas, is engaged in restoration of visceral systems. Thus, the general mechanism of the interaction between quality of sleep and health became clear.

Sinomenine, an Alkaloid Derived from Sinomenium acutum Potentiates Pentobarbital-Induced Sleep Behaviors and Non-Rapid Eye Movement (NREM) Sleep in Rodents

Sinomenium acutum has been long used in the preparations of traditional medicine in Japan, China and Korea for the treatment of various disorders including rheumatism, fever, pulmonary diseases and mood disorders. Recently, it was reported that Sinomenium acutum, has sedative and anxiolytic effects mediated by GABA-ergic systems. These experiments were performed to investigate whether sinomenine (SIN), an alkaloid derived from Sinomenium acutum enhances pentobarbital-induced sleep via γ-aminobutyric acid (GABA)-ergic systems, and modulates sleep architecture in mice. Oral administration of SIN (40 mg/kg) markedly reduced spontaneous locomotor activity, similar to diazepam (a benzodiazepine agonist) in mice. SIN shortened sleep latency, and increased total sleep time in a dose-dependent manner when co-administrated with pentobarbital (42 mg/kg, i.p.). SIN also increased the number of sleeping mice and total sleep time by concomitant administration with the sub-hypnotic dosage of pentobarbital (28 mg/kg, i.p.). SIN reduced the number of sleep-wake cycles, and increased total sleep time and non-rapid eye movement (NREM) sleep. In addition, SIN also increased chloride influx in the primary cultured hypothalamic neuronal cells. Furthermore, protein overexpression of glutamic acid decarboxylase (GAD_65/67) and GABA_A receptor subunits by western blot were found, being activated by SIN. In conclusion, SIN augments pentobarbital-induced sleeping behaviors through GABA_A-ergic systems, and increased NREM sleep. It could be a candidate for the treatment of insomnia.

Cortical dendritic activity correlates with spindle-rich oscillations during sleep in rodents

How sleep influences brain plasticity is not known. In particular, why certain electroencephalographic (EEG) rhythms are linked to memory consolidation is poorly understood. Calcium activity in dendrites is known to be necessary for structural plasticity changes, but this has never been carefully examined during sleep. Here, we report that calcium activity in populations of neocortical dendrites is increased and synchronised during oscillations in the spindle range in naturally sleeping rodents. Remarkably, the same relationship is not found in cell bodies of the same neurons and throughout the cortical column. Spindles during sleep have been suggested to be important for brain development and plasticity. Our results provide evidence for a physiological link of spindles in the cortex specific to dendrites, the main site of synaptic plasticity.

Different stages of sleep, marked by particular electroencephalographic (EEG) signatures, have been linked to memory consolidation, but underlying mechanisms are poorly understood. Here, the authors show that dendritic calcium synchronisation correlates with spindle-rich sleep phases.

Different Simultaneous Sleep States in the Hippocampus and Neocortex

STUDY OBJECTIVES

Investigators assign sleep-waking states using brain activity collected from a single site, with the assumption that states occur at the same time throughout the brain. We sought to determine if sleep-waking states differ between two separate structures: the hippocampus and neocortex.

METHODS

We measured electrical signals (electroencephalograms and electromyograms) during sleep from the hippocampus and neocortex of five freely behaving adult male rats. We assigned sleep-waking states in 10-sec epochs based on standard scoring criteria across a 4-h recording, then analyzed and compared states and signals from simultaneous epochs between sites.

RESULTS

We found that the total amount of each state, assigned independently using the hippocampal and neocortical signals, was similar between the hippocampus and neocortex. However, states at simultaneous epochs were different as often as they were the same (P = 0.82). Furthermore, we found that the progression of states often flowed through asynchronous state-pairs led by the hippocampus. For example, the hippocampus progressed from transition-to-rapid eye movement sleep to rapid eye movement sleep before the neocortex more often than in synchrony with the neocortex (38.7 ± 16.2% versus 15.8 ± 5.6% mean ± standard error of the mean).

CONCLUSIONS

We demonstrate that hippocampal and neocortical sleep-waking states often differ in the same epoch. Consequently, electrode location affects estimates of sleep architecture, state transition timing, and perhaps even percentage of time in sleep states. Therefore, under normal conditions, models assuming brain state homogeneity should not be applied to the sleeping or waking brain.

Methods of automated absence seizure detection, interference by stimulation, and possibilities for prediction in genetic absence models

BACKGROUND

Genetic rat models for childhood absence epilepsy have become instrumental in developing theories on the origin of absence epilepsy, the evaluation of new and experimental treatments, as well as in developing new methods for automatic seizure detection, prediction, and/or interference of seizures.

METHOD

Various methods for automated off and on-line analyses of ECoG in rodent models are reviewed, as well as data on how to interfere with the spike-wave discharges by different types of invasive and non-invasive electrical, magnetic, and optical brain stimulation. Also a new method for seizure prediction is proposed.

RESULTS

Many selective and specific methods for off- and on-line spike-wave discharge detection seem excellent, with possibilities to overcome the issue of individual differences. Moreover, electrical deep brain stimulation is rather effective in interrupting ongoing spike-wave discharges with low stimulation intensity. A network based method is proposed for absence seizures prediction with a high sensitivity but a low selectivity. Solutions that prevent false alarms, integrated in a closed loop brain stimulation system open the ways for experimental seizure control.

CONCLUSIONS

The presence of preictal cursor activity detected with state of the art time frequency and network analyses shows that spike-wave discharges are not caused by sudden and abrupt transitions but that there are detectable dynamic events. Their changes in time-space-frequency characteristics might yield new options for seizure prediction and seizure control.

Synaptic Homeostasis and Restructuring across the Sleep-Wake Cycle

Sleep is critical for hippocampus-dependent memory consolidation. However, the underlying mechanisms of synaptic plasticity are poorly understood. The central controversy is on whether long-term potentiation (LTP) takes a role during sleep and which would be its specific effect on memory. To address this question, we used immunohistochemistry to measure phosphorylation of Ca2+/calmodulin-dependent protein kinase II (pCaMKIIα) in the rat hippocampus immediately after specific sleep-wake states were interrupted. Control animals not exposed to novel objects during waking (WK) showed stable pCaMKIIα levels across the sleep-wake cycle, but animals exposed to novel objects showed a decrease during subsequent slow-wave sleep (SWS) followed by a rebound during rapid-eye-movement sleep (REM). The levels of pCaMKIIα during REM were proportional to cortical spindles near SWS/REM transitions. Based on these results, we modeled sleep-dependent LTP on a network of fully connected excitatory neurons fed with spikes recorded from the rat hippocampus across WK, SWS and REM. Sleep without LTP orderly rescaled synaptic weights to a narrow range of intermediate values. In contrast, LTP triggered near the SWS/REM transition led to marked swaps in synaptic weight ranking. To better understand the interaction between rescaling and restructuring during sleep, we implemented synaptic homeostasis and embossing in a detailed hippocampal-cortical model with both excitatory and inhibitory neurons. Synaptic homeostasis was implemented by weakening potentiation and strengthening depression, while synaptic embossing was simulated by evoking LTP on selected synapses. We observed that synaptic homeostasis facilitates controlled synaptic restructuring. The results imply a mechanism for a cognitive synergy between SWS and REM, and suggest that LTP at the SWS/REM transition critically influences the effect of sleep: Its lack determines synaptic homeostasis, its presence causes synaptic restructuring.

Initiation of sleep-dependent cortical-hippocampal correlations at wakefulness-sleep transition

Sleep is involved in memory consolidation. Current theories propose that sleep-dependent memory consolidation requires active communication between the hippocampus and neocortex. Indeed, it is known that neuronal activities in the hippocampus and various neocortical areas are correlated during slow-wave sleep. However, transitioning from wakefulness to slow-wave sleep is a gradual process. How the hippocampal-cortical correlation is established during the wakefulness-sleep transition is unknown. By examining local field potentials and multiunit activities in the rat hippocampus and visual cortex, we show that the wakefulness-sleep transition is characterized by sharp-wave ripple events in the hippocampus and high-voltage spike-wave events in the cortex, both of which are accompanied by highly synchronized multiunit activities in the corresponding area. Hippocampal ripple events occur earlier than the cortical high-voltage spike-wave events, and hippocampal ripple incidence is attenuated by the onset of cortical high-voltage spike waves. This attenuation leads to a temporary weak correlation in the hippocampal-cortical multiunit activities, which eventually evolves to a strong correlation as the brain enters slow-wave sleep. The results suggest that the hippocampal-cortical correlation is established through a concerted, two-step state change that first synchronizes the neuronal firing within each brain area and then couples the synchronized activities between the two regions.

A microstructural study of sleep instability in drug-naive patients with schizophrenia and healthy controls: sleep spindles, rapid eye movements, and muscle atonia

This study aimed at characterizing the functional stability of sleep in schizophrenia by quantifying dissociated stages of sleep (DSS), and to explore their correlation with psychopathology. The sleep of 10 first-break, drug-naive young adults with schizophrenia and 10 controls was recorded. Four basic DSS patterns were scored: 1) the transitional EEG-mixed intermediate stage (EMIS); 2) Rapid-eye-movement (REM) sleep without rapid eye movement (RSWR); 3) REM sleep without atonia (RSWA); and 4) non-REM sleep with rapid eye movements. An intermediate sleep (IS) score was calculated by summing EMIS and RSWR scores, and the durations of intra-REM sleep periods IS (IRSPIS) and IS scored "at the expense" of REM sleep (ISERS) were determined. Patients were administered the Brief Psychiatric Rating Scale (BPRS) at the time of recording. Proportions of each DSS variables over total sleep time and proportions of IRSPIS and ISERS over REM sleep duration were compared between patients and controls. Correlation coefficients between DSS variables and BPRS total scores were calculated. The proportion of total DSS did not differ between patients and controls. Among DSS subtypes, RSWA was significantly increased in patients while other comparisons showed no significant differences. Significant positive correlations were found between BPRS scores and proportions of DSS, IS, RSWR, IRSPIS and ISERS over total sleep and REM sleep durations. These results demonstrate the functional instability of REM sleep in first-break, drug naive young adults with schizophrenia and unveil a pattern reminiscent of REM sleep behavior disorder. The significant correlation suggests that schizophrenia and REM sleep share common neuronal control mechanisms.

Sleep pattern and learning in knockdown mice with reduced cholinergic neurotransmission

Impaired cholinergic neurotransmission can affect memory formation and influence sleep-wake cycles (SWC). In the present study, we describe the SWC in mice with a deficient vesicular acetylcholine transporter (VAChT) system, previously characterized as presenting reduced acetylcholine release and cognitive and behavioral dysfunctions. Continuous, chronic ECoG and EMG recordings were used to evaluate the SWC pattern during light and dark phases in VAChT knockdown heterozygous (VAChT-KDHET, n=7) and wild-type (WT, n=7) mice. SWC were evaluated for sleep efficiency, total amount and mean duration of slow-wave, intermediate and paradoxical sleep, as well as the number of awakenings from sleep. After recording SWC, contextual fear-conditioning tests were used as an acetylcholine-dependent learning paradigm. The results showed that sleep efficiency in VAChT-KDHET animals was similar to that of WT mice, but that the SWC was more fragmented. Fragmentation was characterized by an increase in the number of awakenings, mainly during intermediate sleep. VAChT-KDHET animals performed poorly in the contextual fear-conditioning paradigm (mean freezing time: 34.4±3.1 and 44.5±3.3 s for WT and VAChT-KDHET animals, respectively), which was followed by a 45% reduction in the number of paradoxical sleep episodes after the training session. Taken together, the results show that reduced cholinergic transmission led to sleep fragmentation and learning impairment. We discuss the results on the basis of cholinergic plasticity and its relevance to sleep homeostasis. We suggest that VAChT-KDHET mice could be a useful model to test cholinergic drugs used to treat sleep dysfunction in neurodegenerative disorders.

Behavioral and electrophysiological correlates of sleep and sleep homeostasis

The definition of what sleep is depends on the method that is applied to record sleep. Behavioral and (electro)-physiological measures of sleep clearly overlap in mammals and birds , but it is often unclear how these two relate in other vertebrates and invertebrates. Homeostatic regulation of sleep, where the amount of sleep depends on the amount of previous waking, can be observed in physiology and behavior in all animals this was tested in. In mammals and birds, sleep is generally subdivided into two states, non-rapid eye movement (NREM) sleep and REM sleep. In mammals the combination of behavioral sleep and the changes in the slow-wave range of the NREM sleep electroencephalogram (EEG) can explain and predict the occurrence and depth of sleep in great detail. For REM sleep this is far less clear. Finally, the discovery that slow-waves in the NREM sleep EEG are influenced locally on the cortex depending on prior waking behavior is an interesting new development that asks for an adaptation of the concept of homeostatic regulation of sleep. Incorporating local sleep into models of sleep regulation is needed to obtain a comprehensive picture.

The Efficacy Study on Si Ni San Freeze-Dried Powder on Sleep Phase in Insomniac and Normal Rats

Objectives. To investigate the effect of Si Ni San freeze-dried powder (SNSP) on sleep phase in insomniac and normal rats, to identify its mode of action in improving sleep, and to provide a reliable method for determining pharmacodynamic material basis of Si-Ni-San on improving sleep. Methods. Rats were deprived of sleep by using the footplate electrical stimulator to record the rats' electroencephalogram (EEG) and electromyogram (EMG) by using polysomnography (PSG) and copy insomnia model by the method of electric stimulation. Analysis on EEG and EMG was carried out to observe the effects of SNSP on the sleep phase of insomniac and normal rats. Results. Rats were treated by intragastric administration (i.g.) consecutively for seven days. The results showed that the total sleep time was extended; meanwhile, SWS2 (P < 0.01) and REMS (P < 0.05) were mainly prolonged for both insomniac and normal rats. The dates implied SNSP could significantly improve sleep. Conclusions. SNSP could prolong SWS2 and REMS, the experimental reproducibility is good, and the dates indicate that SNSP has the sedative function. Study on the effects of SNSP on sleep phases provided a basis for the further studies on effective constituents and the pharmacodynamic mechanism of SNSP.

Dynamics of action potential initiation in the GABAergic thalamic reticular nucleus in vivo

Understanding the neural mechanisms of action potential generation is critical to establish the way neural circuits generate and coordinate activity. Accordingly, we investigated the dynamics of action potential initiation in the GABAergic thalamic reticular nucleus (TRN) using in vivo intracellular recordings in cats in order to preserve anatomically-intact axo-dendritic distributions and naturally-occurring spatiotemporal patterns of synaptic activity in this structure that regulates the thalamic relay to neocortex. We found a wide operational range of voltage thresholds for action potentials, mostly due to intrinsic voltage-gated conductances and not synaptic activity driven by network oscillations. Varying levels of synchronous synaptic inputs produced fast rates of membrane potential depolarization preceding the action potential onset that were associated with lower thresholds and increased excitability, consistent with TRN neurons performing as coincidence detectors. On the other hand the presence of action potentials preceding any given spike was associated with more depolarized thresholds. The phase-plane trajectory of the action potential showed somato-dendritic propagation, but no obvious axon initial segment component, prominent in other neuronal classes and allegedly responsible for the high onset speed. Overall, our results suggest that TRN neurons could flexibly integrate synaptic inputs to discharge action potentials over wide voltage ranges, and perform as coincidence detectors and temporal integrators, supported by a dynamic action potential threshold.

Functional Anatomy of Non-REM Sleep

The state of non-REM sleep (NREM), or slow wave sleep, is associated with a synchronized EEG pattern in which sleep spindles and/or K complexes and high-voltage slow wave activity (SWA) can be recorded over the entire cortical surface. In humans, NREM is subdivided into stages 2 and 3-4 (presently named N3) depending on the proportions of each of these polygraphic events. NREM is necessary for normal physical and intellectual performance and behavior. An overview of the brain structures involved in NREM generation shows that the thalamus and the cerebral cortex are absolutely necessary for the most significant bioelectric and behavioral events of NREM to be expressed; other structures like the basal forebrain, anterior hypothalamus, cerebellum, caudal brain stem, spinal cord and peripheral nerves contribute to NREM regulation and modulation. In NREM stage 2, sustained hyperpolarized membrane potential levels resulting from interaction between thalamic reticular and projection neurons gives rise to spindle oscillations in the membrane potential; the initiation and termination of individual spindle sequences depends on corticothalamic activities. Cortical and thalamic mechanisms are also involved in the generation of EEG delta SWA that appears in deep stage 3-4 (N3) NREM; the cortex has classically been considered to be the structure that generates this activity, but delta oscillations can also be generated in thalamocortical neurons. NREM is probably necessary to normalize synapses to a sustainable basal condition that can ensure cellular homeostasis. Sleep homeostasis depends not only on the duration of prior wakefulness but also on its intensity, and sleep need increases when wakefulness is associated with learning. NREM seems to ensure cell homeostasis by reducing the number of synaptic connections to a basic level; based on simple energy demands, cerebral energy economizing during NREM sleep is one of the prevalent hypotheses to explain NREM homeostasis.

To what extent do neurobiological sleep-waking processes support psychoanalysis?

Sigmund Freud's thesis was that there is a censorship during waking that prevents memory of events, drives, wishes, and feelings from entering the consciousness because they would induce anxiety due to their emotional or ethical unacceptability. During dreaming, because the efficiency of censorship is decreased, latent thought contents can, after dream-work involving condensation and displacement, enter the dreamer's consciousness under the figurative form of manifest content. The quasi-closed dogma of psychoanalytic theory as related to unconscious processes is beginning to find neurobiological confirmation during waking. Indeed, there are active processes that suppress (repress) unwanted memories from entering consciousness. In contrast, it is more difficult to find neurobiological evidence supporting an organized dream-work that would induce meaningful symbolic content, since dream mentation most often only shows psychotic-like activities.

Neonatal sensory deprivation promotes development of absence seizures in adult rats with genetic predisposition to epilepsy

Absence epilepsy has age-related onset. In a WAG/Rij rat genetic model, absence seizures appear after puberty and they are increased with age. It is known that (1) epileptic activity in WAG/Rij rats is initiated at the perioral area in the somatosensory cortex; (2) sensory deprivation, i.e., whisker trimming during the critical period of development, could enhance excitatory activity in the somatosensory cortex. It is hypothesized that the cortex may become more excitable after neonatal vibrissae removal, and this may precipitate absence seizures in adult rats. We found that whisker trimming during the first postnatal weeks caused more rapid development of EEG seizure activity in adult WAG/Rij rats. Epileptic discharges in the trimmed rats were more numerous (vs control), showed longer duration and often appeared in desynchronized and drowsy EEG. The number of absence-like spindle-shaped EEG events (spike-wave spindles) in the whisker-trimmed rats was higher than in control, especially during the intermediate sleep state. An age-dependent increase of intermediate sleep state was found in the trimmed rats, but not in the intact animals. We discuss epigenetic factors that can modulate absence epilepsy in genetically prone subjects.

An algorithm for real-time detection of spike-wave discharges in rodents

The automatic real-time detection of spike-wave discharges (SWDs), the electroencephalographic hallmark of absence seizures, would provide a complementary tool for rapid interference with electrical deep brain stimulation in both patients and animal models. This paper describes a real-time detection algorithm for SWDs based on continuous wavelet analyses in rodents. It has been implemented in a commercially available data acquisition system and its performance experimentally verified. ECoG recordings lasting 5-8h from rats (n=8) of the WAG/Rij strain were analyzed using the real-time SWD detection system. The results indicate that the algorithm is able to detect SWDs within 1s with 100% sensitivity and with a precision of 96.6% for the number of SWDs. Similar results are achieved for 24-h ECoG recordings of two rats. The dependence of accuracy and speed of detection on program settings and attributes of ECoG are discussed. It is concluded that the wavelet based real-time detecting algorithm is well suited for automatic, real-time detection of SWDs in rodents.

Is sleep in animals affected by prior waking experiences?

Methods to assess changes in the mental state of animals in response to their environment can be used to provide information to enhance animal welfare. One of the most profound changes of mental state observable in mammals is the change between wakefulness and sleep. Sleeping mammals have characteristics that are similar to one another and are measurable, such as specific behaviours, changes in responsiveness to external stimuli and changes in electrophysiology and neurochemistry. Although sleep is a ubiquitous behaviour in the life of mammals, there has been relatively little research on this topic in domesticated animals. All animals are motivated to sleep and this motivation increases after a prolonged period of wakefulness. In humans, sleep can be affected by what has occurred in the prior period of wakefulness and this has also been demonstrated in some non-human mammals. An important aspect of human sleep medicine is the association between stress and subsequent sleep disturbances. Studying changes in amount, bout length, distribution or type of sleep after exposure to potentially stressful events, could help us understand how animals respond to changes in their environment. It is possible that different types of stressors could affect sleep characteristics in different ways and that monitoring and identifying these changes could be useful in providing an additional way of identifying management procedures that have the potential to affect welfare. Sleep measurement is a potentially valuable tool in studies to assess animal welfare.