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GorillaFACS: The Facial Action Coding System for the Gorilla spp.
The Facial Action Coding System (FACS) is an objective observation tool for measuring human facial behaviour. It avoids subjective attributions of meaning by objectively measuring independent movements linked to facial muscles, called Action Units (AUs). FACS has been adapted to 11 other taxa, including most apes, macaques and domestic animals, but not yet gorillas. To carry out cross species studies of facial expressions within and beyond apes, gorillas need to be included in such studies. Hence, we developed the GorillaFACS for the Gorilla spp. We followed similar methodology as previous FACS: First, we examined the facial muscular plan of the gorilla. Second, we analysed gorilla videos in a wide variety of contexts to identify their spontaneous facial movements. Third, we classified the individual facial movements according to appearance changes produced by the corresponding underlying musculature. A diverse repertoire of 42 facial movements was identified in the gorilla, including 28 AUs and 14 Action Descriptors, with several new movements not identified in the HumanFACS. Although some of the movements in gorillas differ from humans, the total number of AUs is comparable to the HumanFACS (32 AUs). Importantly, the gorilla’s range of facial movements was larger than expected, suggesting a more relevant role in social interactions than what was previously assumed. GorillaFACS is a scientific tool to measure facial movements, and thus, will allow us to better understand the gorilla’s expressions and communication. Furthermore, GorillaFACS has the potential be used as an important tool to evaluate this species welfare, particularly in settings of close proximity to humans.
Expert navigators deploy rational complexity–based decision precaching for large-scale real-world planning
Efficient planning is a distinctive hallmark of intelligence in humans, who routinely make rapid inferences over complex world contexts. However, studies investigating how humans accomplish this tend to focus on naive participants engaged in simplistic tasks with small state spaces, which do not reflect the intricacy, ecological validity, and human specialization in real-world planning. In this study, we examine the street-by-street route planning of London taxi drivers navigating across more than 26,000 streets in London (United Kingdom). We explore how planning unfolded dynamically over different phases of journey construction and identify theoretic principles by which these expert human planners rationally precache decisions at prioritized environment states in an early phase of the planning process. In particular, we find that measures of path complexity predict human mental sampling prioritization dynamics independent of alternative measures derived from the real spatial context being navigated. Our data provide real-world evidence for complexity-driven remote state access within internal models and precaching during human expert route planning in very large structured spaces.
Electroconvulsive shock and transcranial magnetic stimulation do not alter the survival or spine density of adult-born striatal neurons
Adult neurogenesis has most often been studied in the hippocampus and subventricular zone-olfactory bulb, where newborn neurons contribute to a variety of behaviors. A handful of studies have also investigated adult neurogenesis in other brain regions, but relatively little is known about the properties of neurons added to non-canonical areas. One such region is the striatum. Adult-born striatal neurons have been described in both rodents and humans, but the regulation of these neurons is poorly understood. Since striatal dysfunction occurs in Parkinson’s disease, which is amenable to neurostimulation therapies, we investigated whether electroconvulsive shock (ECS) or transcranial magnetic stimulation (rTMS) modulate neuroplasticity of adult-born striatal neurons. Adult-born cells were labelled in transgenic mice and 8 days later mice were given 10 stimulations over the course of 3 weeks. Adult-born striatal neurons were consistently observed in all groups. Their dendritic morphology and expression of DARPP32 and NeuN indicated a medium spiny neuron phenotype. However, neither ECS nor rTMS altered the number of new neurons, and both treatments also had no effect on the density of dendritic spines compared to unstimulated controls. These results suggest that neither ECS nor rTMS alter early neuronal survival or morphological plasticity at postsynaptic sites in the striatum.
Governing in the face of a global crisis: When do voters punish and reward incumbent governments?
The recent COVID-19 pandemic offers a rare opportunity to understand how citizens attribute responsibility for governments’ responses to unanticipated negative—and in this case, systemic—exogenous shocks. Classical accounts of responsibility are complicated when crises are pervasive, involve multiple valence dimensions, and where individuals can make relative assessments of performance. We fielded a conjoint experiment in 16 countries with 22,147 respondents. In this experiment, subjects made re-election decisions regarding 178,184 randomly assigned incumbent profiles. We find that incumbents’ performance along both health and economic dimensions drives these hypothetical reelection decisions. Using machine learning techniques, we find only muted heterogeneity in the magnitude and distribution of these treatment effects. This result suggests that these widely reported performance signals have consistent political effects across countries. In a complementary analysis, we also find that subjects’ intentions to vote for incumbent governments are positively correlated with subjective and relative evaluations of the government’s pandemic performance, along both health and economic dimensions. These results provide consistent evidence that evaluations of pandemic performance matter politically.
The liminal space between hope and grief: The phenomenon of uncertainty as experienced by people living with relapsing-remitting multiple sclerosis
Background People with the chronic disease Multiple Sclerosis are subjected to different degrees of profound uncertainty. Uncertainty has been linked to adverse psychological effects such as feelings of heightened vulnerability, avoidance of decision-making, fear, worry, anxiety disorders, and even depression. Research into Multiple Sclerosis has a predominant focus on the scientific, practical, and psychosocial issues of uncertainty. In comparison, existential uncertainty has been under-researched, even though it might pose a greater burden to those experiencing it. Objective To understand the lived experience of uncertainty for people living with relapsing-remitting Multiple Sclerosis. Methods This study followed a phenomenological research design, employing elements of both the Reflective Lifeworld Approach and Phenomenology of Practice. Seventeen people with a recent (<1 year) diagnosis of relapsing-remitting Multiple Sclerosis were included. In-depth interviews were conducted immediately after inclusion. Results The lived experience of uncertainty can be described as a stumbling motion across the liminal space between hope and grief while dealing with oscillating feelings of unrest concerning the body, self, and others. The following four constituents further illuminate the meaning of the phenomenon: Having to constantly (re)define unfamiliar and intangible bodily changes on one’s own; Unsteady navigating amidst a destabilization of the imagined life; Relating to others as a source of, mirror or buffer for uncertainty; Going through overwhelming fears and worries while clinging to one’s own logic. Conclusion Adding to existing qualitative and phenomenological research into MS and theories on uncertainty, this study portrays uncertainty as a multifaceted experience. The findings imply the need for a continuous attunement of healthcare practitioners to the expectations, fears, avoidance techniques, and other uniquely personal circumstances of people with Multiple Sclerosis.
Enhancing drug solubility through competitive adsorption on silica nanosurfaces with ultrahigh silanol densities
We develop a technology based on competitive adsorption between drug molecules and water, specifically designed to address the critical issue of poor drug solubility. By specially engineering silica nanosurfaces with ultrahigh densities of silanol, we significantly enhance their affinity for both drug molecules and water, with a notably greater increase in water affinity. Such surfaces can effectively adsorb a variety of drug molecules under dry conditions. Upon exposure to water, these surfaces preferentially bind to water molecules, initiating a competitive adsorption process with the drug molecules. This competitive process turns water molecules from obstacles into catalysts for drug dissolution by actively displacing drug molecules from the surface, causing their rapid desorption and potentially enhancing their solubility by two to three orders of magnitude. The method is general, applicable to a wide array of drugs, stable for long-time storage, cost-effective, and scalable for mass production. Consequently, it has the potential to emerge as a next-generation platform for drug formulation and delivery.
Evidence that flocking behavior is rewarded by singing, flock mates, and mu opioid receptors in the nucleus accumbens
It has been proposed that social groups are maintained both by reward resulting from positive social interactions and by the reduction of a negative state that would otherwise be caused by social separation. European starlings, Sturnus vulgaris, develop strong conditioned place preferences for places associated with the production of song in flocks outside the breeding season (gregarious song) and singers are motivated to rejoin the flock following removal. This indicates that the act of singing in flocks is associated with a positive affective state and raises the possibility that reward induced by song in flocks may play a role in flock maintenance. The goal of this study was to begin to test this hypothesis. We found that birds that sang full songs developed stronger conditioned place preferences than non-singing birds for places associated with flock mates, indicating that singers find the presence of flock mates to be rewarding. Regardless of song rate, the presence of flock mates also induced analgesia (a reflection of the reduction of a negative state). This form of analgesia has been shown to be an indirect measure of opioid release, suggesting that the presence of flock mates may induce opioid-mediated reward. Consistent with this possibility, the numbers of mu opioid receptor immunolabeled cells in the nucleus accumbens correlated positively with measurements of gregarious song and other social behaviors. Results suggest that both gregarious song and social contact promote flock cohesion and that opioids released onto mu opioid receptors in the nucleus accumbens may play an important role.
A carnitine transporter at the blood–brain barrier modulates sleep via glial lipid metabolism in <i>Drosophila</i>
To regulate brain function, peripheral compounds must traverse the blood–brain barrier (BBB), an interface between the brain and the circulatory system. To determine whether specific transport mechanisms are relevant for sleep, we conducted a BBB-specific inducible RNAi knockdown (iKD) screen for genes affecting sleep in Drosophila . We observed reduced sleep with knockdown of solute carrier CG6126 , a carnitine transporter, as determined by isotope flux. Our findings suggest that CG6126 regulation of sleep is through the role of the carnitine shuttle in regulating fatty acid metabolism as lipid droplets accumulate in the brains of CG6126 BBB iKD flies. Knocking down mitochondrial carnitine transferases in non-BBB glial cells mimicked the reduced sleep of the CG6126 BBB iKD flies, while bypassing the necessity of carnitine transport with dietary medium-chain fatty acids or palmitoylcarnitine rescued sleep. We propose that carnitine transport via CG6126 promotes brain fatty acid metabolism necessary for maintaining sleep.
The international trial of nasal oxygen therapy after cardiac surgery (NOTACS) in patients at high risk of postoperative pulmonary complications: Economic evaluation protocol and analysis plan
Introduction High-Flow Nasal Therapy (HFNT) is an innovative non-invasive form of respiratory support. Compared to standard oxygen therapy (SOT), there is an equipoise regarding the effect of HFNT on patient-centred outcomes among those at high risk of developing postoperative pulmonary complications after undergoing cardiac surgery. The NOTACS trial aims to determine the clinical and cost-effectiveness of HFNT compared to SOT within 90 days of surgery in the United Kingdom, Australia, and New Zealand. This protocol describes the methods and analyses planned for economic evaluation embedded within the ongoing NOTACS trial. Methods and analysis The economic evaluation will identify, measure and value resources and health outcomes in both trial arms and compare changes in costs with ‘days alive and at home’ and EQ-5D-5L quality adjusted life years (QALYs) from the perspective most relevant to the decision-making country. Results from pooling data across the trial will use health and social care sector perspective. All patient-specific data including hospital/community care and health outcomes will be collected prospectively. Unit costs will be sourced from national, published or local data. Missing data will be assessed, with values replaced depending on assumed mechanism of missingness, and impact of replacement on cost-effectiveness assessed. Costs and outcomes by trial arm will be presented as components and totals per patient using a range of descriptive statistics. Regression models for costs and effects will account for patient characteristics, quality of life and health service utilization at baseline. Uncertainty in parameters, sampling and heterogeneity will be addressed through deterministic, probabilistic and subgroup analyses to assess the impact of varying methods and assumptions for costs, outcomes and approaches used in base-case analysis. Results will be interpreted using recommended national cost-effectiveness thresholds. Registration details The study is registered with ISRCTN (ISRCTN14092678) on 13/05/2020. ISRCTN is a primary registry of the WHO ICTRP network and includes all items from the WHO Trial Registration data set.
Behavioral nudges prevent loan delinquencies at scale: A 13-million-person field experiment
Americans collectively hold over $1.6 trillion in student loan debt, and over the last decade millions of borrowers have defaulted on loans, with serious consequences for their financial health. In a 13-million-person field experiment with the U.S. Department of Education, we tested the effectiveness of different email interventions to inform borrowers about alternative repayment options after a missed loan payment. Our interventions tested whether sending monthly behaviorally-informed emails, providing follow-up reminders, framing benefits in percentage (vs. dollar) terms, and providing just one recommended action step at a time (vs. two) affected borrower outcomes. We find that i) behaviorally-informed emails reduce estimated 60-d delinquencies by 0.42 pp, ii) reminders boost the efficacy of such emails by 0.57 pp, iii) describing potential savings in percentage terms is more effective than describing these benefits in dollar terms, reducing estimated delinquencies by 0.14 pp, and iv) encouraging two actions (i.e., enrollment in income-driven repayment plans and auto debit programs) repeatedly across two emails is marginally more effective than encouraging one action at-a-time across two emails, reducing estimated delinquencies by 0.05 pp. Overall, if scaled to all 13-million borrowers in our experiment, we estimate that our best-performing intervention would have averted approximately 79,800 60-d delinquencies. Our findings i) highlight the benefits of describing potential savings in percentage terms, which may magnify perceived savings for recipients, ii) underscore the risks of oversimplification, and iii) demonstrate that nudges can be an effective, low-cost complement to other policies for reducing delinquencies and supporting borrowers with student loan debt.
Smart home technology to support engagement in everyday activities while ageing: A focus group study with current and future generations of older adults
Despite the potential of smart home technologies (SHT) to support everyday activities, the implementation rate of such technology in the homes of older adults remains low. The overall aim of this study was to explore factors involved in the decision-making process in adopting SHT among current and future generations of older adults. We also aimed to identify and understand barriers and facilitators that can better support older adults’ engagement in everyday activities. Focus group discussions were used to explore the perspectives of people from diverse age groups (30–39, 50–59, and 70-79-year-olds). Three focus groups met twice at a lab designed as a two-room home equipped with SHT. Our findings revealed that the participants’ decision-making process for adopting SHT involved designs that must be adapted to the changing physical abilities and diverse needs of users. Some conditions, such as ideas for re-invention, were identified after the integration of SHT. Concerns about reliability, complicated interfaces, and value to the user influenced the decision to adopt SHT, highlighting the importance of these factors for successful implementation. Some participants did not fully understand what SHT is nor perceive its benefits, but they expressed a desire to acquire the skills and knowledge to operate SHT. Furthermore, participants desired SHT that can support an active lifestyle. The perceived advantages of SHT include enhancing the sense of security and safety, which can facilitate engagement in everyday activity. Some participants experienced a positive impact on quality of life, related to comfortable living with the implementation of SHT. Adults across age groups perceive that SHT can enhance engagement in everyday activity and the sense of safety and security. However, it is essential to identify solutions for better usability. More collaborative efforts involving diverse stakeholders are vital to bridge the disconnect between SHT design and users’ needs and preferences.
Spreading dynamics of information on online social networks
Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information-spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.45 billion users, we uncover a ubiquitous mechanism that the information-spreading dynamics are basically driven by the interplay of social reinforcement and social weakening effects. Accordingly, we propose a concise equation, which, surprisingly, can well describe all the empirical large-scale spreading trajectories. Our theory resolves a number of controversial claims and satisfactorily explains many phenomena previously observed. It also reveals that the highly clustered nature of social networks can lead to rapid and high-frequency information bursts with relatively small coverage per burst. This vital feature enables social media to have a high capacity and diversity for information dissemination, beneficial for its ecological development.
Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models
Diabetic retinopathy, a retinal disorder resulting from diabetes mellitus, is a prominent cause of visual degradation and loss among the global population. Therefore, the identification and classification of diabetic retinopathy are of utmost importance in the clinical diagnosis and therapy. Currently, these duties are extensively carried out by manual examination utilizing the human visual system. Nevertheless, manual examination is sometimes arduous, time-consuming, and prone to errors. Deep learning-based methods have recently demonstrated encouraging results in several areas, such as image categorization and natural language mining. The majority of deep learning techniques developed for medical image analysis rely on convolutional modules to extract the inherent structure of images within a certain local receptive field. Furthermore, transformer-based models have been utilized to tackle medical image processing problems by capitalizing on global connections among distant pixels in the images. Considering these analyses, this work presents a comprehensive deep learning model that combines convolutional neural network and vision mamba models. This model is designed to accurately identify and classify diabetic retinopathy lesions displayed in fundus images. Furthermore, the vision mamba component incorporates the bidirectional state space method and positional embedding to enable the location sensitivity of visual data samples and meet the conditions for global relationship context. An evaluation of the suggested method was carried out by comparison experiments between state-of-the-art algorithms and the proposed methodology. Empirical findings demonstrate that the suggested methodology surpasses the most advanced algorithms on the datasets that are accessible openly. Hence, the suggested approach may be regarded as a helpful tool for therapeutic processes.
Light signal regulates endoreduplication and tomato fruit expansion through the SlPIF1a-SlTLFP8-SlCDKB2 module
Light serves as an energy source for cell division and expansion during fruit development. Cell expansion significantly influences fruit size and is closely linked to endoreduplication, a unique cell cycle variation characterized by DNA replication without cytokinesis. Paradoxically, under conditions of ample photosynthates, light signaling suppresses cell expansion. The intricate regulation of endoreduplication in response to light signaling during fruit development has remained an intriguing question. Here, our study revealed that Tubby-like F-box protein 8 (SlTLFP8) orchestrated endoreduplication to facilitate fruit cell expansion. As an Skp1-Cullin-F-box (SCF)-type E3 ligase, SlTLFP8 promoted the ubiquitination and subsequent degradation of CYCLIN-DEPENDENT KINASE B2 (SlCDKB2), thereby elevating DNA ploidy. The light signaling component PHYTOCHROME-INTERACTING FACTOR 1a (SlPIF1a), identified as a pivotal negative regulator in the plant’s light response, was found to directly interact with the promoter of the SlTLFP8 gene, thereby stimulating its transcriptional activation. Indeed, SlPIF1a contributed to a faster expansion rate of tomato fruit during nighttime. Altogether, our results elucidate the connection between light signals and fruit size regulation through endoreduplication.
Beyond the jab: Unravelling the complexities of vaccine adoption for East Coast Fever in rural Kenya
East Coast Fever (ECF) is one of the leading causes of livestock mortality and reduced productivity across Eastern Africa, and while a live vaccine against it known as the Infection and Treatment Method has existed for three decades now, its adoption by affected communities remains low. This study sought to provide a detailed examination of the dynamics that shape Infection Treatment Method (ITM) vaccine adoption behaviours. The study examined individual, socio-cultural and ecological- level factors influencing ITM adoption using the socio-ecological model. Analyzing data obtained from 18 focus group discussions, 30 in-depth interviews with livestock keepers, and 25 key informant interviews conducted with community stakeholders, the study identified factors associated with vaccine adoption within pastoralist communities in rural Kenya. These factors included knowledge and awareness of the Infection Treatment Method vaccine, its cost, livestock keepers’ perceptions of East Coast fever relative to other livestock diseases, wildlife-livestock interactions, climate as contributing factors, and wildlife-livestock interactions influencing ECF risk and severity. Overall, the study findings emphasize the need for multifaceted strategies to increase vaccine adoption among livestock keepers.
The perceptual primacy of feeling: Affectless visual machines explain a majority of variance in human visually evoked affect
Looking at the world often involves not just seeing things, but feeling things. Modern feedforward machine vision systems that learn to perceive the world in the absence of active physiology, deliberative thought, or any form of feedback that resembles human affective experience offer tools to demystify the relationship between seeing and feeling, and to assess how much of visually evoked affective experiences may be a straightforward function of representation learning over natural image statistics. In this work, we deploy a diverse sample of 180 state-of-the-art deep neural network models trained only on canonical computer vision tasks to predict human ratings of arousal, valence, and beauty for images from multiple categories (objects, faces, landscapes, art) across two datasets. Importantly, we use the features of these models without additional learning, linearly decoding human affective responses from network activity in much the same way neuroscientists decode information from neural recordings. Aggregate analysis across our survey, demonstrates that predictions from purely perceptual models explain a majority of the explainable variance in average ratings of arousal, valence, and beauty alike. Finer-grained analysis within our survey (e.g. comparisons between shallower and deeper layers, or between randomly initialized, category-supervised, and self-supervised models) point to rich, preconceptual abstraction (learned from diversity of visual experience) as a key driver of these predictions. Taken together, these results provide further computational evidence for an information-processing account of visually evoked affect linked directly to efficient representation learning over natural image statistics, and hint at a computational locus of affective and aesthetic valuation immediately proximate to perception.
Measurement of inferior colliculus volume based on MRI image stacks and its relationship with age and hearing status
The inferior colliculus is a key nucleus in the central auditory pathway, integrating acoustic stimuli from both cochleae and playing a crucial role in sound localization. It undergoes functional and structural development in childhood and experiences age-related degeneration later in life, contributing to the progression of age-related hearing loss. This study aims at finding out, whether the volume of the human inferior colliculus can be determined by analysis of routinely performed MRIs and whether there is any age-related variation. A further goal is to detect correlations between volume and existing hearing loss of the patients. A retrospective search in the data of the Regensburg ENT department was done. 123 MRI datasets were used to mark the voxels of the inferior colliculus on the MRI layers. The volumes could then be calculated by using the respective DICOM data and were correlated with age, gender and hearing status of the patients. Results suggested that a voxel-based method on routine clinical MRI stacks to determine the volume of the inferior colliculus is possible. The volume shows an age-dependency. There is a growth from infancy until adulthood and a significant decrease in patients over the age of 60 years. Left and right inferior colliculi do not show any systematic asymmetry in volume. There is no difference between females and males. In the group with asymmetric hearing (n = 13) a significant reduction of the volume on the deprived side (p = 0.036) was found. The proportion of subjects with severe hearing loss at least on one side was significantly higher in the old (>60 years) as compared to younger adults (10 to 60 years), suggesting that severe hearing loss may be associated with a reduced volume of the inferior colliculus in aged humans.
Iron limitation triggers roseoceramide biosynthesis and membrane remodeling in marine roseobacter
Chemical communication between marine bacteria and their algal hosts drives population dynamics and ultimately determines the fate of major biogeochemical cycles in the ocean. To gain deeper insights into this small molecule exchange, we screened niche-specific metabolites as potential modulators of the secondary metabolome of the roseobacter, Roseovarius tolerans . Metabolomic analysis led to the identification of a group of cryptic lipids that we have termed roseoceramides. The roseoceramides are elicited by iron-binding algal flavonoids, which are produced by macroalgae that Roseovarius species associate with. Investigations into the mechanism of elicitation show that iron limitation in R. tolerans initiates a stress response that results in lowered oxidative phosphorylation, increased import and catabolism of algal exudates, and reconfiguration of lipid synthesis to prioritize production of roseoceramides over phospholipids, likely to fortify membrane integrity as well as promote a sessile and symbiotic lifestyle. Our findings add new small molecule words and their “meanings” to the algal-bacterial lexicon and have implications for the initiation of these interactions.
Development, validation, and reliability testing of the College Perspectives around Food Insecurity survey
The objective of this study was to develop and to test the validity and reliability of a survey aimed to evaluate internal and external factors associated with college food insecurity. Researchers used a mixed methods approach to evaluate the College Perspectives around Food Insecurity survey. Survey items were constructed from interview data and assigned a social cognitive theory concept (environment, personal, or behavior). Two rounds of expert reviews established content validity (Round 1, n = 3; Round 2, n = 2). Researchers evaluated face validity through two rounds of cognitive interviews with college students 18+ years old (Round 1, n = 9; Round 2, n = 16) and tested survey reliability (n = 105). Researchers used descriptive statistics, test-retest reliability statistics, and Cronbach’s alpha scores for data analysis. The initial survey contained 143 items. After feedback from expert reviewers and cognitive interviews, the final survey contained 99 items. Test-retest reliability was 0.99, and Cronbach’s alpha scores were 0.74 for environment, 0.47 for personal, and 0.39 for behavior. The College Perspectives around Food Insecurity survey can be used to better understand internal and external factors associated with food insecurity in college students, which can inform interventions aimed at assisting this population.
Calcineurin governs baseline and homeostatic regulations of non–rapid eye movement sleep in mice
Sleep need accumulates during waking and dissipates during sleep to maintain sleep homeostasis (process S). Besides the regulation of daily (baseline) sleep amount, homeostatic sleep regulation commonly refers to the universal phenomenon that sleep deprivation (SD) causes an increase of sleep need, hence, the amount and intensity of subsequent recovery sleep. The central regulators and signaling pathways that govern the baseline and homeostatic sleep regulations in mammals remain unclear. Here, we report that enhanced activity of calcineurin Aα (CNAα)—a catalytic subunit of calcineurin—in the mouse brain neurons sharply increases the amount (to ~17-h/d) and delta power—a measure of intensity—of non–rapid eye movement sleep (NREMS). Knockout of the regulatory ( CnB1 ) or catalytic ( CnAα and CnAβ ) subunits of calcineurin diminishes the amount (to ~4-h/d) and delta power of baseline NREMS, but also nearly abrogates the homeostatic recovery NREMS following SD. Accordingly, mathematical modeling of process S reveals an inability to accumulate sleep need during spontaneous or forced wakefulness in calcineurin deficient mice. Moreover, calcineurin promotes baseline NREMS by antagonizing wake-promoting protein kinase A and, in part, by activating sleep-promoting kinase SIK3. Together, these results indicate that calcineurin is an important regulator of sleep need and governs both baseline and homeostatic regulations of NREMS in mice.