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1. Cortical astrocytes independently regulate sleep depth and duration via separate GPCR pathways

   https://doi.org/10.7554/eLife.63329  

   Vaidyanathan, Trisha V ; Collard, Max ; Yokoyama, Sae ; Reitman, Michael E ; Poskanzer, Kira E ( March 2021 , eLife)

   Sleep has many roles, from strengthening new memories to regulating mood and appetite. While we might instinctively think of sleep as a uniform state of reduced brain activity, the reality is more complex. First, over the course of the night, we cycle between a number of different sleep stages, which reflect different levels of sleep depth. Second, the amount of sleep depth is not necessarily even across the brain but can vary between regions. These sleep stages consist of either rapid eye movement (REM) sleep or non-REM (NREM) sleep. REM sleep is when most dreaming occurs, whereas NREM sleep ismore »particularly important for learning and memory and can vary in duration and depth. During NREM sleep, large groups of neurons synchronize their firing to create rhythmic waves of activity known as slow waves. The more synchronous the activity, the deeper the sleep. Vaidyanathan et al. now show that brain cells called astrocytes help regulate NREM sleep. Astrocytes are not neurons but belong to a group of specialized cells called glia. They are the largest glia cell type in the brain and display an array of proteins on their surfaces called G-protein-coupled receptors (GPCRs). These enable them to sense sleep-wake signals from other parts of the brain and to generate their own signals. In fact, each astrocyte can communicate with thousands of neurons at once. They are therefore well-poised to coordinate brain activity during NREM sleep. Using innovative tools, Vaidyanathan et al. visualized astrocyte activity in mice as the animals woke up or fell asleep. The results showed that astrocytes change their activity just before each sleep–wake transition. They also revealed that astrocytes control both the depth and duration of NREM sleep via two different types of GPCR signals. Increasing one of these signals (Gi-GPCR) made the mice sleep more deeply but did not change sleep duration. Decreasing the other (Gq-GPCR) made the mice sleep for longer but did not affect sleep depth. Sleep problems affect many people at some point in their lives, and often co-exist with other conditions such as mental health disorders. Understanding how the brain regulates different features of sleep could help us develop better – and perhaps more specific – treatments for sleep disorders. The current study suggests that manipulating GPCRs on astrocytes might increase sleep depth, for example. But before work to test this idea can begin, we must first determine whether findings from sleeping mice also apply to people.« less
2. Shorter Duration and Lower Quality Sleep Have Widespread Detrimental Effects on Developing Functional Brain Networks in Early Adolescence

   https://doi.org/10.1093/texcom/tgab062  

   Brooks, Skylar J ; Katz, Eliot S ; Stamoulis, Catherine ( January 2022 , Cerebral Cortex Communications)

   Abstract Sleep is critical for cognitive health, especially during complex developmental periods such as adolescence. However, its effects on maturating brain networks that support cognitive function are only partially understood. We investigated the impact of shorter duration and reduced quality sleep, common stressors during development, on functional network properties in early adolescence—a period of significant neural maturation, using resting-state functional magnetic resonance imaging from 5566 children (median age = 120.0 months; 52.1% females) in the Adolescent Brain Cognitive Development cohort. Decreased sleep duration, increased sleep latency, frequent waking up at night, and sleep-disordered breathing symptoms were associated with lower topological efficiency, flexibility, andmore »robustness of visual, sensorimotor, attention, fronto-parietal control, default-mode and/or limbic networks, and with aberrant changes in the thalamus, basal ganglia, hippocampus, and cerebellum (P < 0.05). These widespread effects, many of which were body mass index-independent, suggest that unhealthy sleep in early adolescence may impair neural information processing and integration across incompletely developed networks, potentially leading to deficits in their cognitive correlates, including attention, reward, emotion processing and regulation, memory, and executive control. Shorter sleep duration, frequent snoring, difficulty waking up, and daytime sleepiness had additional detrimental network effects in nonwhite participants, indicating racial disparities in the influence of sleep metrics.« less
3. The Impact of Sleep Disturbance on Regional Brain Volumes

   https://doi.org/10.1093/geroni/igaa057.1521  

   Burke, Shanna ; Li, Tan ; Grudzien, Adrienne ; Barnes, Christopher ; Hanson, Kevin ; DeKosky, Steven ( December 2020 , Innovation in Aging)

   Abstract Sleep disruption has been associated with increased beta-amyloid deposition and greater risk for later development of Alzheimer’s disease. Studies indicate that sleep disturbance correlates with regional brain volumes, but data are limited. We sought to determine the effect of sleep disturbance on regional brain volumes by cognitive and apolipoprotein e (APOE) e4 status. We conducted a secondary analysis of the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set using complete structural imaging data from 1,371 participants (mean age: 70.5; SD: 11.7). Multiple linear regression was used to estimate the adjusted effect of sleep disturbance (via Neuropsychiatric Inventory Questionnaire) onmore »regional brain volumes through measurement of 30 structural MRI biomarkers. Sleep disruption was associated with greater volumes in the right and left lateral ventricles and greater volume of total white matter hyperintensities (p<.05). Lower mean volumes in total brain, total gray matter, and total cerebrum grey matter volumes, and in 12 hippocampal, frontal, parietal, and temporal lobe volumes were observed among participants who reported sleep disturbance. Males, Hispanic participants, and those with less education were more likely to report sleep disruption. Cognitive status moderated the relationship between sleep disturbance and lateral ventricular volumes, while APOE e4 moderated the effect between sleep disturbance and parietal lobe volumes. These findings suggest that disrupted sleep is associated with atrophy across multiple brain regions and ventricular hydrocephalus ex vacuo, after controlling for intracranial volume and demographic covariates. The influence of cognition and APOE e4 status indicates that this relationship is affected by co-occurring physiological processes.« less
4. Phase model-based neuron stabilization into arbitrary clusters

   Matchen, Timothy D. ; Moehlis, Jeff ( January 2018 , Journal of computational neuroscience)

   Deep brain stimulation (DBS) is a common method of combating pathological conditions associated with Parkinson’s disease, Tourette syndrome, essential tremor, and other disorders, but whose mechanisms are not fully understood. One hypothesis, supported experimentally, is that some symptoms of these disorders are associated with pathological synchronization of neurons in the basal ganglia and thalamus. For this reason, there has been interest in recent years in finding efficient ways to desynchronize neurons that are both fast-acting and low-power. Recent results on coordinated reset and periodically forced oscillators suggest that forming distinct clusters of neurons may prove to be more effective thanmore »achieving complete desynchronization, in particular by promoting plasticity effects that might persist after stimulation is turned off. Current proposed methods for achieving clustering frequently require either multiple input sources or precomputing the control signal. We propose here a control strategy for clustering, based on an analysis of the reduced phase model for a set of identical neurons, that allows for real-time, single-input control of a population of neurons with low-amplitude, low total energy signals. After demonstrating its effectiveness on phase models, we apply it to full state models to demonstrate its validity. We also discuss the effects of coupling on the efficacy of the strategy proposed and demonstrate that the clustering can still be accomplished in the presence of weak to moderate electrotonic coupling.« less
5. SymptomID: A Framework for Rapid Symptom Identification in Pandemics Using News Reports

   https://doi.org/10.1145/3462441  

   Gu, Kang ; Vosoughi, Soroush ; Prioleau, Temiloluwa ( December 2021 , ACM Transactions on Management Information Systems)

   The ability to quickly learn fundamentals about a new infectious disease, such as how it is transmitted, the incubation period, and related symptoms, is crucial in any novel pandemic. For instance, rapid identification of symptoms can enable interventions for dampening the spread of the disease. Traditionally, symptoms are learned from research publications associated with clinical studies. However, clinical studies are often slow and time intensive, and hence delays can have dire consequences in a rapidly spreading pandemic like we have seen with COVID-19. In this article, we introduce SymptomID, a modular artificial intelligence–based framework for rapid identification of symptoms associatedmore »with novel pandemics using publicly available news reports. SymptomID is built using the state-of-the-art natural language processing model (Bidirectional Encoder Representations for Transformers) to extract symptoms from publicly available news reports and cluster-related symptoms together to remove redundancy. Our proposed framework requires minimal training data, because it builds on a pre-trained language model. In this study, we present a case study of SymptomID using news articles about the current COVID-19 pandemic. Our COVID-19 symptom extraction module, trained on 225 articles, achieves an F1 score of over 0.8. SymptomID can correctly identify well-established symptoms (e.g., “fever” and “cough”) and less-prevalent symptoms (e.g., “rashes,” “hair loss,” “brain fog”) associated with the novel coronavirus. We believe this framework can be extended and easily adapted in future pandemics to quickly learn relevant insights that are fundamental for understanding and combating a new infectious disease.« less