Journal Article Call to action: an open-source pipeline for standardized performance evaluation of sleep-tracking technology Get access Davide Benedetti, Davide Benedetti Center for Health Sciences, SRI International, Menlo Park, CA, USADepartment of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy Corresponding author. Davide Benedetti, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA. Email: d.benedetti5@studenti.unipi.it; davide.benedetti@sri.com. https://orcid.org/0000-0003-3881-5742 Search for other works by this author on: Oxford Academic Google Scholar Luca Menghini, Luca Menghini Department of General Psychology, University of Padova, Padova, Italy https://orcid.org/0000-0001-6494-3970 Search for other works by this author on: Oxford Academic Google Scholar Raphael Vallat, Raphael Vallat Center for Human Sleep Science, Department of Psychology, University of California, Berkeley, Berkeley, CA, USA https://orcid.org/0000-0003-1779-7653 Search for other works by this author on: Oxford Academic Google Scholar Remington Mallett, Remington Mallett Department of Psychology, Northwestern University, Evanston, IL, USA https://orcid.org/0000-0001-6183-3098 Search for other works by this author on: Oxford Academic Google Scholar Orsolya Kiss, Orsolya Kiss Center for Health Sciences, SRI International, Menlo Park, CA, USA https://orcid.org/0000-0003-2643-773X Search for other works by this author on: Oxford Academic Google Scholar Ugo Faraguna, Ugo Faraguna Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, ItalyDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy https://orcid.org/0000-0002-4814-7218 Search for other works by this author on: Oxford Academic Google Scholar Fiona C Baker, Fiona C Baker Center for Health Sciences, SRI International, Menlo Park, CA, USA https://orcid.org/0000-0001-9602-6165 Search for other works by this author on: Oxford Academic Google Scholar Massimiliano de Zambotti Massimiliano de Zambotti Center for Health Sciences, SRI International, Menlo Park, CA, USA https://orcid.org/0000-0002-0057-5977 Search for other works by this author on: Oxford Academic Google Scholar Sleep, Volume 46, Issue 2, February 2023, zsac304, https://doi.org/10.1093/sleep/zsac304 Published: 05 January 2023

Insufficient sleep impairs glucose regulation, increasing the risk of diabetes. However, what it is about the human sleeping brain that regulates blood sugar remains unknown. In an examination of over 600 humans, we demonstrate that the coupling of non-rapid eye movement (NREM) sleep spindles and slow oscillations the night before is associated with improved next-day peripheral glucose control. We further show that this sleep-associated glucose pathway may influence glycemic status through altered insulin sensitivity, rather than through altered pancreatic beta cell function. Moreover, we replicate these associations in an indepen-dent dataset of over 1,900 adults. Of therapeutic significance, the coupling between slow oscillations and spindles was the most significant sleep predictor of next-day fasting glucose, even more so than traditional sleep markers, relevant to the possibility of an electroencephalogram (EEG) index of hyperglycemia. Taken together, these findings describe a sleeping-brain-body framework of optimal human glucose homeostasis, offering a potential prognostic sleep signature of glycemic control.

ObjectivePoor sleep is associated with hypertension, a major risk factor for cardiovascular disease. However, the mechanism(s) through which sleep loss affects cardiovascular health remains largely unknown, including the brain and body systems that regulate vascular function.MethodsSixty-six healthy adults participated in a repeated-measures, crossover, experimental study involving assessments of cardiovascular function and brain connectivity after a night of sleep and a night of sleep deprivation.ResultsFirst, sleep deprivation significantly increased blood pressure-both systolic and diastolic. Interestingly, this change was independent of any increase in heart rate, inferring a vasculature-specific rather than direct cardiac pathway. Second, sleep loss compromised functional brain connectivity within the vascular control network, specifically the insula, anterior cingulate, amygdala, and ventral and medial prefrontal cortices. Third, sleep loss-related changes in brain connectivity and vascular tone were not independent, but significantly interdependent, with changes within the vascular control brain network predicting the sleep-loss shift toward hypertension.ConclusionsThese findings establish an embodied framework in which sleep loss confers increased risk of cardiovascular disease through an impact upon central brain control of vascular tone, rather than a direct impact on accelerated heart rate itself.

Background Alzheimer’s disease (AD) pathology impairs cognitive function. Yet some individuals with high amounts of AD pathology suffer marked memory impairment, while others with the same degree of pathology burden show little impairment. Why is this? One proposed explanation is cognitive reserve i.e., factors that confer resilience against, or compensation for the effects of AD pathology. Deep NREM slow wave sleep (SWS) is recognized to enhance functions of learning and memory in healthy older adults. However, that the quality of NREM SWS (NREM slow wave activity, SWA) represents a novel cognitive reserve factor in older adults with AD pathology, thereby providing compensation against memory dysfunction otherwise caused by high AD pathology burden, remains unknown. Methods Here, we tested this hypothesis in cognitively normal older adults ( N = 62) by combining 11 C-PiB (Pittsburgh compound B) positron emission tomography (PET) scanning for the quantification of β-amyloid (Aβ) with sleep electroencephalography (EEG) recordings to quantify NREM SWA and a hippocampal-dependent face-name learning task. Results We demonstrated that NREM SWA significantly moderates the effect of Aβ status on memory function. Specifically, NREM SWA selectively supported superior memory function in individuals suffering high Aβ burden, i.e., those most in need of cognitive reserve ( B = 2.694, p = 0.019). In contrast, those without significant Aβ pathological burden, and thus without the same need for cognitive reserve, did not similarly benefit from the presence of NREM SWA ( B = -0.115, p = 0.876). This interaction between NREM SWA and Aβ status predicting memory function was significant after correcting for age, sex, Body Mass Index, gray matter atrophy, and previously identified cognitive reserve factors, such as education and physical activity ( p = 0.042). Conclusions These findings indicate that NREM SWA is a novel cognitive reserve factor providing resilience against the memory impairment otherwise caused by high AD pathology burden. Furthermore, this cognitive reserve function of NREM SWA remained significant when accounting both for covariates, and factors previously linked to resilience, suggesting that sleep might be an independent cognitive reserve resource. Beyond such mechanistic insights are potential therapeutic implications. Unlike many other cognitive reserve factors (e.g., years of education, prior job complexity), sleep is a modifiable factor. As such, it represents an intervention possibility that may aid the preservation of cognitive function in the face of AD pathology, both present moment and longitudinally.

Introduction Several results suggest that the frequency of dream recall is positively correlated with personality traits such as creativity and openness to experience. In addition, neuroimaging results have evidenced different neurophysiological profiles in high dream recallers (HR) and low dream recallers (LR) during both sleep and wakefulness, specifically within regions of the default mode network (DMN). These findings are consistent with the emerging view that dreaming and mind wandering pertain to the same family of spontaneous mental processes, subserved by the DMN. Methods To further test this hypothesis, we measured the DMN functional connectivity during resting wakefulness, together with personality and cognitive abilities (including creativity) in 28 HR and 27 LR. Results As expected, HR demonstrated a greater DMN connectivity than LR, higher scores of creativity, and no significant difference in memory abilities. However, there was no significant correlation between creativity scores and DMN connectivity. Discussion These results further demonstrate that there are trait neurophysiological and psychological differences between individuals who frequently recall their dreams and those who do not. They support the forebrain and the DMN hypotheses of dreaming and leave open the possibility that increased activity in the DMN promotes creative-thinking during both wakefulness and sleep. Further work is needed to test whether activity in the DMN is causally associated with creative-thinking.

Event-related potentials (ERPs) associated with the involuntary orientation of (bottom-up) attention toward an unexpected sound are of larger amplitude in high dream recallers (HR) than in low dream recallers (LR) during passive listening, suggesting different attentional functioning. We measured bottom-up and top-down attentional performance and their cerebral correlates in 18 HR (11 women, age = 22.7 years, dream recall frequency = 5.3 days with a dream recall per week) and 19 LR (10 women, age = 22.3, DRF = 0.2) using EEG and the Competitive Attention Task. Between-group differences were found in ERPs but not in behavior. The results show that HR present larger ERPs to distracting sounds than LR even during active listening, arguing for enhanced bottom-up processing of irrelevant sounds. HR also presented larger contingent negative variation during target expectancy and P3b to target sounds than LR, speaking for an enhanced recruitment of top-down attention. The attentional balance seems preserved in HR since their performances are not altered, but possibly at a higher resource cost. In HR, increased bottom-up processes would favor dream recall through awakening facilitation during sleep and enhanced top-down processes may foster dream recall through increased awareness and/or short-term memory stability of dream content.

How people wake up and regain alertness in the hours after sleep is related to how they are sleeping, eating, and exercising. Here, in a prospective longitudinal study of 833 twins and genetically unrelated adults, we demonstrate that how effectively an individual awakens in the hours following sleep is not associated with their genetics, but instead, four independent factors: sleep quantity/quality the night before, physical activity the day prior, a breakfast rich in carbohydrate, and a lower blood glucose response following breakfast. Furthermore, an individual’s set-point of daily alertness is related to the quality of their sleep, their positive emotional state, and their age. Together, these findings reveal a set of non-genetic (i.e., not fixed) factors associated with daily alertness that are modifiable.

Humans help each other. This fundamental feature of homo sapiens has been one of the most powerful forces sculpting the advent of modern civilizations. But what determines whether humans choose to help one another? Across 3 replicating studies, here, we demonstrate that sleep loss represents one previously unrecognized factor dictating whether humans choose to help each other, observed at 3 different scales (within individuals, across individuals, and across societies). First, at an individual level, 1 night of sleep loss triggers the withdrawal of help from one individual to another. Moreover, fMRI findings revealed that the withdrawal of human helping is associated with deactivation of key nodes within the social cognition brain network that facilitates prosociality. Second, at a group level, ecological night-to-night reductions in sleep across several nights predict corresponding next-day reductions in the choice to help others during day-to-day interactions. Third, at a large-scale national level, we demonstrate that 1 h of lost sleep opportunity, inflicted by the transition to Daylight Saving Time, reduces real-world altruistic helping through the act of donation giving, established through the analysis of over 3 million charitable donations. Therefore, inadequate sleep represents a significant influential force determining whether humans choose to help one another, observable across micro- and macroscopic levels of civilized interaction. The implications of this effect may be non-trivial when considering the essentiality of human helping in the maintenance of cooperative, civil society, combined with the reported decline in sufficient sleep in many first-world nations.

The clinical and societal measurement of human sleep has increased exponentially in recent years. However, unlike other fields of medical analysis that have become highly automated, basic and clinical sleep research still relies on human visual scoring. Such human-based evaluations are time-consuming, tedious, and can be prone to subjective bias. Here, we describe a novel algorithm trained and validated on +30,000 hr of polysomnographic sleep recordings across heterogeneous populations around the world. This tool offers high sleep-staging accuracy that matches human scoring accuracy and interscorer agreement no matter the population kind. The software is designed to be especially easy to use, computationally low-demanding, open source, and free. Our hope is that this software facilitates the broad adoption of an industry-standard automated sleep staging software package.

Sleep, diet and exercise are fundamental to metabolic homeostasis. In this secondary analysis of a repeated measures, nutritional intervention study, we tested whether an individual’s sleep quality, duration and timing impact glycaemic response to a breakfast meal the following morning. Healthy adults’ data (N = 953 [41% twins]) were analysed from the PREDICT dietary intervention trial. Participants consumed isoenergetic standardised meals over 2 weeks in the clinic and at home. Actigraphy was used to assess sleep variables (duration, efficiency, timing) and continuous glucose monitors were used to measure glycaemic variation (>8000 meals). Sleep variables were significantly associated with postprandial glycaemic control (2 h incremental AUC), at both between- and within-person levels. Sleep period time interacted with meal type, with a smaller effect of poor sleep on postprandial blood glucose levels when high-carbohydrate (low fat/protein) (pinteraction = 0.02) and high-fat (pinteraction = 0.03) breakfasts were consumed compared with a reference 75 g OGTT. Within-person sleep period time had a similar interaction (high carbohydrate: pinteraction = 0.001, high fat: pinteraction = 0.02). Within- and between-person sleep efficiency were significantly associated with lower postprandial blood glucose levels irrespective of meal type (both p < 0.03). Later sleep midpoint (time deviation from midnight) was found to be significantly associated with higher postprandial glucose, in both between-person and within-person comparisons (p = 0.035 and p = 0.051, respectively). Poor sleep efficiency and later bedtime routines are associated with more pronounced postprandial glycaemic responses to breakfast the following morning. A person’s deviation from their usual sleep pattern was also associated with poorer postprandial glycaemic control. These findings underscore sleep as a modifiable, non-pharmacological therapeutic target for the optimal regulation of human metabolic health. Trial registration ClinicalTrials.gov NCT03479866.

Eye movement desensitization and reprocessing (EMDR) is a psychotherapy for the treatment of posttraumatic stress disorder (PTSD). It is still unclear whether symptoms remission through EMDR therapy is associated with a beneficial effect on one of the PTSD symptoms, sleep disturbance. Our objective was therefore to study sleep parameters before and after symptom remission in soldiers with PTSD. The control group consisted of 20 healthy active duty military men who slept in a sleep lab with standard polysomnography (PSG) on two sessions separated by one month. The patient group consisted of 17 active duty military with PTSD who underwent EMDR therapy. PSG-recorded sleep was assessed 1 week before the EMDR therapy began and 1 week after PTSD remission. We found that the increased REMs density after remission was positively correlated with a greater decrease of symptoms. Also, the number of EMDR sessions required to reach remission was correlated with intra-sleep awakenings before treatment. These results confirm the improvement of some sleep parameters in PTSD after symptoms remission in a soldier's population and provide a possible predictor of treatment success. Further experiments will be required to establish whether this effect is specific to the EMDR therapy.

The creation of a completely automated sleep-scoring system that is highly accurate, flexible, well validated, free and simple to use by anyone has yet to be accomplished. In part, this is due to the difficulty of use of existing algorithms, algorithms having been trained on too small samples, and paywall demotivation. Here we describe a novel algorithm trained and validated on +27,000 hours of polysomnographic sleep recordings across heterogeneous populations around the world. This tool offers high sleep-staging accuracy matching or exceeding human accuracy and interscorer agreement no matter the population kind. The software is easy to use, computationally low-demanding, open source, and free. Such software has the potential to facilitate broad adoption of automated sleep staging with the hope of becoming an industry standard.

Sleep loss amplifies basic emotional reactivity, increasing negative mood states (e.g., anxiety, depression, suicidality), yet impairing the accurate recognition and outward expression of emotions. Inadequate sleep further impacts higher-order, complex socio-emotional functioning, decreasing prosocial behaviors, increasing social withdrawal, triggering marital and workplace conflict, and enfeebling leadership skills. The emotional dysfunction experienced by sleep-deprived individuals, such as loneliness or lack of work motivation, can be ‘transmitted’ to well-rested others who come in contact with an under-slept individual, reflecting viral contagion. The underlying neural mechanisms include a loss of top-down prefrontal regulation of amygdala, aberrant cortical processing in the salience network, including insula and cingulate cortex, and sympathovagal changes in the body. Are you feeling emotionally fragile, moody, unpredictable, even ungenerous to those around you? Here, we review how and why these phenomena can occur as a result of insufficient sleep. Sleep loss disrupts a broad spectrum of affective processes, from basic emotional operations (e.g., recognition, responsivity, expression), through to high-order, complex socio-emotional functioning (e.g., loneliness, helping behavior, abusive behavior, and charisma). Translational insights further emerge regarding the pervasive link between sleep disturbance and psychiatric conditions, including anxiety, depression, and suicidality. More generally, such findings raise concerns regarding society’s mental (ill)health and the prevalence of insufficient and disrupted sleep. Are you feeling emotionally fragile, moody, unpredictable, even ungenerous to those around you? Here, we review how and why these phenomena can occur as a result of insufficient sleep. Sleep loss disrupts a broad spectrum of affective processes, from basic emotional operations (e.g., recognition, responsivity, expression), through to high-order, complex socio-emotional functioning (e.g., loneliness, helping behavior, abusive behavior, and charisma). Translational insights further emerge regarding the pervasive link between sleep disturbance and psychiatric conditions, including anxiety, depression, and suicidality. More generally, such findings raise concerns regarding society’s mental (ill)health and the prevalence of insufficient and disrupted sleep. an evidence-based treatment of insomnia that consists of a multicomponent intervention designed to target the behavioral and cognitive underpinnings of insomnia. abnormal sleep that can be described in measures of deficient sleep quantity, structure (e.g., sleep-cycle architecture), and/or sleep quality [e.g., spectral electroencephalogram (EEG) power]. the statistical association between the fMRI time series of blood-oxygen-level-dependent signal in two or more anatomically distinct brain regions. acting without sufficient deliberation. a type of sleep that consists of sleep stages N1–3 (previously NREM 1–4). Each NREM sleep stage has distinct (electro)physiological characteristics. High amplitude, slow-frequency synchronized EEG oscillations predominate in stage N3 (previously NREM 3 + 4, also known as slow-wave sleep, or deep sleep), and reflecta homeostatic sleep process. a unique phase of sleep characterized by high-frequency, low-amplitude desynchronized EEG oscillations, rapid eye movements, muscle paralysis, and vivid dreaming. going to bed later than intended due to self-choice. a metric of sleep evaluation often gauged from either subjective self-report (e.g., how satisfying and refreshing sleep was) or objective sleep features (e.g., sleep stage transitions, night-time awakenings/arousals, sleep stage amounts, and EEG sleep physiology). the reduction (but not total absence) of sleep in the prior night or nights, usually ranging from 1 to 6 hours of sleep reduction, relative to the norm of 8 hours. Typically, sleep restriction is chronic if it persists for more than 24 hours. an electrophysiological signature of slow (typically 0.5–4.0 Hz), synchronized, oscillatory neocortical activity. SWA is maximally expressed during NREM sleep and intensifies as a function of prior wake duration. the complete absence of sleep in the prior night or nights. in humans, relating to corporeal signals communicated by the spinal cord to brain regions that enable homeostatic coordination of bodily functions and associated behaviors.

Why does poor-quality sleep lead to atherosclerosis? In a diverse sample of over 1,600 individuals, we describe a pathway wherein sleep fragmentation raises inflammatory-related white blood cell counts (neutrophils and monocytes), thereby increasing atherosclerosis severity, even when other common risk factors have been accounted for. Improving sleep quality may thus represent one preventive strategy for lowering inflammatory status and thus atherosclerosis risk, reinforcing public health policies focused on sleep health.

Why do some individuals recall dreams every day while others hardly ever recall one? We hypothesized that sleep inertia-the transient period following awakening associated with brain and cognitive alterations-could be a key mechanism to explain interindividual differences in dream recall at awakening. To test this hypothesis, we measured the brain functional connectivity (combined electroencephalography-functional magnetic resonance imaging) and cognition (memory and mental calculation) of high dream recallers (HR, n = 20) and low dream recallers (LR, n = 18) in the minutes following awakening from an early-afternoon nap. Resting-state scans were acquired just after or before a 2 min mental calculation task, before the nap, 5 min after awakening from the nap, and 25 min after awakening. A comic was presented to the participants before the nap with no explicit instructions to memorize it. Dream(s) and comic recall were collected after the first post-awakening scan. As expected, between-group contrasts of the functional connectivity at 5 min post-awakening revealed a pattern of enhanced connectivity in HR within the default mode network (DMN) and between regions of the DMN and regions involved in memory processes. At the behavioral level, a between-group difference was observed in dream recall, but not comic recall. Our results provide the first evidence that brain functional connectivity right after awakening is associated with interindividual trait differences in dream recall and suggest that the brain connectivity of HR at awakening facilitates the maintenance of the short-term memory of the dream during the sleep-wake transition.

Are you feeling emotionally fragile, moody, unpredictable, even ungenerous to those around you? Here, we review how and why these phenomena can occur as a result of insufficient sleep. Sleep loss disrupts a broad spectrum of affective processes, from basic emotional operations (e.g., recognition, responsivity, expression), through to high-order, complex socio-emotional functioning (e.g., loneliness, helping behavior, abusive behavior, and charisma). Translational insights further emerge regarding the pervasive link between sleep disturbance and psychiatric conditions, including anxiety, depression, and suicidality. More generally, such findings raise concerns regarding society's mental (ill)health and the prevalence of insufficient and disrupted sleep.

We present Visbrain, a Python open-source package that offers a comprehensive visualization suite for neuroimaging and electrophysiological brain data. Visbrain consists of two levels of abstraction: (1) objects which represent highly configurable neuro-oriented visual primitives (3D brain, sources connectivity, etc.) and (2) graphical user interfaces for higher level interactions. The object level offers flexible and modular tools to produce and automate the production of figures using an approach similar to that of Matplotlib with subplots. The second level visually connects these objects by controlling properties and interactions through graphical interfaces. The current release of Visbrain (version 0.4.2) contains 14 different objects and three responsive graphical user interfaces, built with PyQt: Signal, for the inspection of time-series and spectral properties, Brain for any type of visualization involving a 3D brain and Sleep for polysomnographic data visualization and sleep analysis. Each module has been developed in tight collaboration with end-users, i.e., primarily neuroscientists and domain experts, who bring their experience to make Visbrain as transparent as possible to the recording modalities (e.g., intracranial EEG, scalp-EEG, MEG, anatomical and functional MRI). Visbrain is developed on top of VisPy, a Python package providing high-performance 2D and 3D visualization by leveraging the computational power of the graphics card. Visbrain is available on Github and comes with a documentation, examples, and datasets (http://visbrain.org).