Development of a rule-based automatic five-sleep-stage scoring method for rats

The Fibromyalgia Pain Experience: A Scoping Review of the Preclinical Evidence for Replication and Treatment of the Affective and Cognitive Pain Dimensions

Fibromyalgia is a chronic, widespread pain disorder that is strongly represented across the affective and cognitive dimensions of pain, given that the underlying pathophysiology of the disorder is yet to be identified. These affective and cognitive deficits are crucial to understanding and treating the fibromyalgia pain experience as a whole but replicating this multidimensionality on a preclinical level is challenging. To understand the underlying mechanisms, animal models are used. In this scoping review, we evaluate the current primary animal models of fibromyalgia regarding their translational relevance within the affective and cognitive pain realms, as well as summarize treatments that have been identified preclinically for attenuating these deficits.

Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine

AIMS

Sleep disturbance is a prevalent nonmotor symptom of Parkinson's disease (PD), however, assessing sleep conditions is always time-consuming and labor-intensive. In this study, we performed an automatic sleep-wake state classification and early diagnosis of PD by analyzing the electrocorticography (ECoG) and electromyogram (EMG) signals of both normal and PD rats.

METHODS

The study utilized ECoG power, EMG amplitude, and corticomuscular coherence values extracted from normal and PD rats to construct sleep-wake scoring models based on the support vector machine algorithm. Subsequently, we incorporated feature values that could act as diagnostic markers for PD and then retrained the models, which could encompass the identification of vigilance states and the diagnosis of PD.

RESULTS

Features extracted from occipital ECoG signals were more suitable for constructing sleep-wake scoring models than those from frontal ECoG (average Cohen's kappa: 0.73 vs. 0.71). Additionally, after retraining, the new models demonstrated increased sensitivity to PD and accurately determined the sleep-wake states of rats (average Cohen's kappa: 0.79).

CONCLUSION

This study accomplished the precise detection of substantia nigra lesions and the monitoring of sleep-wake states. The integration of circadian rhythm monitoring and disease state assessment has the potential to improve the efficacy of therapeutic strategies considerably.

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.

Neonatal exposure to a neuroactive steroid alters low-frequency oscillations in the subiculum

Preclinical studies have established that neonatal exposure to contemporary sedative/hypnotic drugs causes neurotoxicity in the developing rodent and primate brains. Our group recently reported that novel neuroactive steroid (3β,5β,17β)-3-hydroxyandrostane-17-carbonitrile (3β-OH) induced effective hypnosis in both neonatal and adult rodents but did not cause significant neurotoxicity in vulnerable brain regions such as subiculum, an output region of hippocampal formation particularly sensitive to commonly used sedatives/hypnotics. Despite significant emphasis on patho-morphological changes, little is known about long-term effects on subicular neurophysiology after neonatal exposure to neuroactive steroids. Hence, we explored the lasting effects of neonatal exposure to 3β-OH on sleep macrostructure as well as subicular neuronal oscillations in vivo and synaptic plasticity ex vivo in adolescent rats. At postnatal day 7, we exposed rat pups to either 10 mg/kg of 3β-OH over a period of 12 h or to volume-matched cyclodextrin vehicle. At weaning age, a cohort of rats was implanted with a cortical electroencephalogram (EEG) and subicular depth electrodes. At postnatal day 30-33, we performed in vivo assessment of sleep macrostructure (divided into wake, non-rapid eye movement, and rapid eye movement sleep) and power spectra in cortex and subiculum. In a second cohort of 3β-OH exposed animals, we conducted ex vivo studies of long-term potentiation (LTP) in adolescent rats. Overall, we found that neonatal exposure to 3β-OH decreased subicular delta and sigma oscillations during non-rapid eye movement sleep without altering sleep macrostructure. Furthermore, we observed no significant changes in subicular synaptic plasticity. Interestingly, our previous study found that neonatal exposure to ketamine increased subicular gamma oscillations during non-rapid eye movement sleep and profoundly suppressed subicular LTP in adolescent rats. Together these results suggest that exposure to different sedative/hypnotic agents during a critical period of brain development may induce distinct functional changes in subiculum circuitry that may persist into adolescent age.

An attention-based temporal convolutional network for rodent sleep stage classification across species, mutants and experimental environments with single-channel electroencephalogram

Objective.Sleep perturbation by environment, medical procedure and genetic background is under continuous study in biomedical research. Analyzing brain states in animal models such as rodents relies on categorizing electroencephalogram (EEG) recordings. Traditionally, sleep experts have classified these states by visual inspection of EEG signatures, which is laborious. The heterogeneity of sleep patterns complicates the development of a generalizable solution across different species, genotypes and experimental environments.Approach.To realize a generalizable solution, we proposed a cross-species rodent sleep scoring network called CSSleep, a robust deep-learning model based on single-channel EEG. CSSleep starts with a local time-invariant information learning convolutional neural network. The second module is the global transition rules learning temporal convolutional network (TRTCN), stacked with bidirectional attention-based temporal convolutional network modules. The TRTCN simultaneously captures positive and negative time direction information and highlights relevant in-sequence features. The dataset for model evaluation comprises the single-EEG signatures of four cohorts of 16 mice and 8 rats from three laboratories.Main results.In leave-one-cohort-out cross-validation, our model achieved an accuracy of 91.33%. CSSleep performed well on generalization across experimental environments, mutants and rodent species by using single-channel EEG.Significance.This study aims to promote well-standardized cross-laboratory sleep studies to improve our understanding of sleep. Our source codes and supplementary materials will be disclosed later.

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.

Neonatal Ketamine Alters High-Frequency Oscillations and Synaptic Plasticity in the Subiculum But Does not Affect Sleep Macrostructure in Adolescent Rats

Exposure to sedative/hypnotic and anesthetic drugs, such as ketamine, during the critical period of synaptogenesis, causes profound neurotoxicity in the developing rodent and primate brains and is associated with poor cognitive outcomes later in life. The subiculum is especially vulnerable to acute neurotoxicity after neonatal exposure to sedative/hypnotic and anesthetic drugs. The subiculum acts as a relay center between the hippocampal complex and various cortical and subcortical brain regions and is also an independent generator of gamma oscillations. Gamma oscillations are vital in neuronal synchronization and play a role in learning and memory during wake and sleep. However, there has been little research examining long-term changes in subicular neurophysiology after neonatal exposure to ketamine. Here we explore the lasting effects of neonatal ketamine exposure on sleep macrostructure as well as subicular neuronal oscillations and synaptic plasticity in rats. During the peak of rodent synaptogenesis at postnatal day 7, rat pups were exposed to either 40 mg/kg of ketamine over 12 h or to volume matched saline vehicle. At weaning age, a subset of rats were implanted with a cortical and subicular electroencephalogram electrode, and at postnatal day 31, we performed in vivo experiments that included sleep macrostructure (divided into the wake, non-rapid eye movement, and rapid eye movement sleep) and electroencephalogram power spectra in cortex and subiculum. In a second subset of ketamine exposed animals, we conducted ex vivo studies of long-term potentiation (LTP) experiments in adolescent rats. Overall, we found that neonatal exposure to ketamine increased subicular gamma oscillations during non-rapid eye movement sleep but it did not alter sleep macrostructure. Also, we observed a significant decrease in subicular LTP. Gamma oscillations during non-rapid eye movement sleep are implicated in memory formation and consolidation, while LTP serves as a surrogate for learning and memory. Together these results suggest that lasting functional changes in subiculum circuitry may underlie neurocognitive impairments associated with neonatal exposure to anesthetic agents.