Dataset Information

A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.

ABSTRACT: Sleep science is entering a new era, thanks to new data-driven analysis approaches that, combined with mouse gene-editing technologies, show a promise in functional genomics and translational research. However, the investigation of sleep is time consuming and not suitable for large-scale phenotypic datasets, mainly due to the need for subjective manual annotations of electrophysiological states. Moreover, the heterogeneous nature of sleep, with all its physiological aspects, is not fully accounted for by the current system of sleep stage classification. In this study, we present a new data-driven analysis approach offering a plethora of novel features for the characterization of sleep. This novel approach allowed for identifying several substages of sleep that were hidden to standard analysis. For each of these substages, we report an independent set of homeostatic responses following sleep deprivation. By using our new substages classification, we have identified novel differences among various genetic backgrounds. Moreover, in a specific experiment with the Zfhx3 mouse line, a recent circadian mutant expressing both shortening of the circadian period and abnormal sleep architecture, we identified specific sleep states that account for genotypic differences at specific times of the day. These results add a further level of interaction between circadian clock and sleep homeostasis and indicate that dissecting sleep in multiple states is physiologically relevant and can lead to the discovery of new links between sleep phenotypes and genetic determinants. Therefore, our approach has the potential to significantly enhance the understanding of sleep physiology through the study of single mutations. Moreover, this study paves the way to systematic high-throughput analyses of sleep.

SUBMITTER: Katsageorgiou VM

PROVIDER: S-EPMC5993302 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.

Katsageorgiou Vasiliki-Maria VM Sona Diego D Zanotto Matteo M Lassi Glenda G Garcia-Garcia Celina C Tucci Valter V Murino Vittorio V

PLoS biology 20180529 5

Sleep science is entering a new era, thanks to new data-driven analysis approaches that, combined with mouse gene-editing technologies, show a promise in functional genomics and translational research. However, the investigation of sleep is time consuming and not suitable for large-scale phenotypic datasets, mainly due to the need for subjective manual annotations of electrophysiological states. Moreover, the heterogeneous nature of sleep, with all its physiological aspects, is not fully account ...[more]

PMID: 29813050

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Project description:Infants are at risk for potentially life-threatening postoperative apnea (POA). We developed an Automated Unsupervised Respiratory Event Analysis (AUREA) to classify breathing patterns obtained with dual belt respiratory inductance plethysmography and a reference using Expectation Maximization (EM). This work describes AUREA and evaluates its performance. AUREA computes six metrics and inputs them into a series of four binary k-means classifiers. Breathing patterns were characterized by normalized variance, nonperiodic power, instantaneous frequency and phase. Signals were classified sample by sample into one of 5 patterns: pause (PAU), movement (MVT), synchronous (SYB) and asynchronous (ASB) breathing, and unknown (UNK). MVT and UNK were combined as UNKNOWN. Twenty-one preprocessed records obtained from infants at risk for POA were analyzed. Performance was evaluated with a confusion matrix, overall accuracy, and pattern specific precision, recall, and F-score. Segments of identical patterns were evaluated for fragmentation and pattern matching with the EM reference. PAU exhibited very low normalized variance. MVT had high normalized nonperiodic power and low frequency. SYB and ASB had a median frequency of respectively, 0.76Hz and 0.71Hz, and a mode for phase of 4o and 100o. Overall accuracy was 0.80. AUREA confused patterns most often with UNKNOWN (25.5%). The pattern specific F-score was highest for SYB (0.88) and lowest for PAU (0.60). PAU had high precision (0.78) and low recall (0.49). Fragmentation was evident in pattern events <2s. In 75% of the EM pattern events >2s, 50% of the samples classified by AUREA had identical patterns. Frequency and phase for SYB and ASB were consistent with published values for synchronous and asynchronous breathing in infants. The low normalized variance in PAU, was consistent with published scoring rules for pediatric apnea. These findings support the use of AUREA to classify breathing patterns and warrant a future evaluation of clinically relevant respiratory events.

Project description:Although at the organismal level sleep is defined as a behavioral state, at the level of the cerebral cortex sleep has a distinct local and use-dependent aspect. This observation raises the question whether sleep is a functional property of a complex brain or occurs at the level of neuronal assemblies with populations that were active more during wakefulness needing more intense sleep to recover. Here we show that primary cortical cultures have the capacity to change between sleep- and wake-like states that share key signatures with their in vivo counterparts. Cortical cultures initially exhibit random firing activity that is gradually replaced by a M-bM-^@M-^\sleep-likeM-bM-^@M-^] synchronized burst-pause firing activity as neurons mature and make connections. When stimulated with excitatory neurotransmitters, transient tonic firing is observed, followed by the reappearance of a M-bM-^@M-^\sleep-likeM-bM-^@M-^] state. Besides electrophysiological similarities also the transcriptional profile of stimulated cortical cultures greatly resembles that of the cortex of sleep deprived animals. We then used our in vitro model to map the metabolic pathways activated by the M-bM-^@M-^\wake-likeM-bM-^@M-^] state and found evidence for increased lysolipid release, strongly suggesting that sleep plays a role in neuronal membrane homeostasis. With our in vitro model the cellular and molecular consequences of sleep loss and the genetic determinants of disturbed sleep can now be investigated in a dish. Keywords: stress response For the in vivo transcriptome analyses mice were sleep deprived for 6 hours and brain harvested immediately afterwards. For the in vitro analyses, cortical cultures were stimulated with a neurotransmitter cocktail and cells harvested 3 hours afterwards. Control mice were kept undisturbed in their home cage and control cultures were sham stimulated with water. Also, another set of sleep deprived mice as well as stimulated cultures were allowed to recover before being sampled the next day at the time of day at which sleep deprivation or stimulation started the day before).

Dataset Information

A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.

Publications

A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.

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