Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms

We have developed an automatic sleep stage classification algorithm based on deep residual neural networks and raw polysomnogram signals. Briefly, the raw data is passed through 50 convolutional layers before subsequent classification into one of five sleep stages. Three model configurations were trained on 1850 polysomnogram recordings and subsequently tested on 230 independent recordings. Our best performing model yielded an accuracy of 84.1% and a Cohen's kappa of 0.746, improving on previous reported results by other groups also using only raw polysomnogram data. Most errors were made on non-REM stage 1 and 3 decisions, errors likely resulting from the definition of these stages. Further testing on independent cohorts is needed to verify performance for clinical use

A comparative study of methods for automatic detection of rapid eye movement abnormal muscular activity in narcolepsy

Objective: To evaluate rapid eye movement (REM) muscular activity in narcolepsy by applying five algorithms to electromyogram (EMG) recordings, and to investigate its value for narcolepsy diagnosis. Patients/methods: A modified version of phasic EMG metric (mPEM), muscle activity index (MAI), REM atonia index (RAI), supra-threshold REM EMG activit ymetric (STREAM), and Frandsen method (FR) were calculated from polysomnography recordings of 20 healthy controls, 18 clinic controls (subjects suspected with narcolepsy but finally diagnosed without any sleep abnormality), 16 narcolepsy type 1 without REM sleep behavior disorder (RBD), 9 narcolepsy type 1 with RBD, and 18 narcolepsy type 2. Diagnostic value of metrics in differentiating between groups was quantified by area under the receiver operating characteristic curve (AUC). Correlations among the metrics and cerebrospinal fluid hypocretin-1 (CSF-hcrt-1) values were calculated using linear models. Results: All metrics excluding STREAM found significantly higher muscular activity in narcolepsy 1 cases versus controls (p<0.05). Moreover, RAI showed high sensitivity in the detection of RBD. The mPEM achieved the highest AUC in differentiating healthy controls from narcoleptic subjects. The RAI best differentiated between narcolepsy 1 and 2. Lower CSF-hcrt-1 values correlated with high muscular activity quantified by mPEM, sMAI, lMAI, PEM and FR (p<0.05). Conclusions: This automatic analysis showed higher number of muscle activations in narcolepsy 1 compared to controls. This finding might play a supportive role in diagnosing narcolepsy and in discriminating narcolepsy subtypes. Moreover, the negative correlation between CSF-hcrt-1 level and REM muscular activity supported a role for hypocretin in the control of motor tone during REM sleep

Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes.

Microglia, the resident immune cells of the brain, rapidly change states in response to their environment, but we lack molecular and functional signatures of different microglial populations. Here, we analyzed the RNA expression patterns of more than 76,000 individual microglia in mice during development, in old age, and after brain injury. Our analysis uncovered at least nine transcriptionally distinct microglial states, which expressed unique sets of genes and were localized in the brain using specific markers. The greatest microglial heterogeneity was found at young ages; however, several states-including chemokine-enriched inflammatory microglia-persisted throughout the lifespan or increased in the aged brain. Multiple reactive microglial subtypes were also found following demyelinating injury in mice, at least one of which was also found in human multiple sclerosis lesions. These distinct microglia signatures can be used to better understand microglia function and to identify and manipulate specific subpopulations in health and disease

Analysis of Signaling Mechanisms Regulating Microglial Process Movement

Microglia, the brain’s innate immune cells, are extremely motile cells, continuously surveying the CNS to serve homeostatic functions and to respond to pathological events. In the healthy brain, microglia exhibit a small cell body with long, branched and highly motile processes, which constantly extend and retract, effectively ‘patrolling’ the brain parenchyma. Over the last decade, methodological advances in microscopy and the availability of genetically encoded reporter mice have allowed us to probe microglial physiology in situ. Beyond their classical immunological roles, unexpected functions of microglia have been revealed, both in the developing and the adult brain: microglia regulate the generation of newborn neurons, control the formation and elimination of synapses, and modulate neuronal activity. Many of these newly ascribed functions depend directly on microglial process movement. Thus, elucidating the mechanisms underlying microglial motility is of great importance to understand their role in brain physiology and pathophysiology. Two-photon imaging of fluorescently labelled microglia, either in vivo or ex vivo in acute brain slices, has emerged as an indispensable tool for investigating microglial movements and their functional consequences. This chapter aims to provide a detailed description of the experimental data acquisition and analysis needed to address these questions, with a special focus on key dynamic and morphological metrics such as surveillance, directed motility and ramification

Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain

A key aspect of nearly all single-cell sequencing experiments is dissociation of intact tissues into single-cell suspensions. While many protocols have been optimized for optimal cell yield, they have often overlooked the effects that dissociation can have on ex vivo gene expression. Here, we demonstrate that use of enzymatic dissociation on brain tissue induces an aberrant ex vivo gene expression signature, most prominently in microglia, which is prevalent in published literature and can substantially confound downstream analyses. To address this issue, we present a rigorously validated protocol that preserves both in vivo transcriptional profiles and cell-type diversity and yield across tissue types and species. We also identify a similar signature in postmortem human brain single-nucleus RNA-sequencing datasets, and show that this signature is induced in freshly isolated human tissue by exposure to elevated temperatures ex vivo. Together, our results provide a methodological solution for preventing artifactual gene expression changes during fresh tissue digestion and a reference for future deeper analysis of the potential confounding states present in postmortem human samples

The Spider Effect: Morphological and Orienting Classification of Microglia in Response to Stimuli in Vivo

The different morphological stages of microglial activation have not yet been described in detail. We transected the olfactory bulb of rats and examined the activation of the microglial system histologically. Six stages of bidirectional microglial activation (A) and deactivation (R) were observed: from stage 1A to 6A, the cell body size increased, the cell process number decreased, and the cell processes retracted and thickened, orienting toward the direction of the injury site; until stage 6A, when all processes disappeared. In contrast, in deactivation stages 6R to 1R, the microglia returned to the original site exhibiting a stepwise retransformation to the original morphology. Thin highly branched processes re-formed in stage 1R, similar to those in stage 1A. This reverse transformation mirrored the forward transformation except in stages 6R to 1R: cells showed multiple nuclei which were slowly absorbed. Our findings support a morphologically defined stepwise activation and deactivation of microglia cells