Importance:While hypoglossal nerve stimulators (HGNS) have been shown to be associated with reduced apnea-hypopnea index (AHI) scores in many continuous positive airway pressure-intolerant patients with obstructive sleep apnea (OSA), it is not effective for all patients, and it is unclear who would benefit most. Objective:To explore baseline factors associated with response to HGNS and create a prognostic stratification system. Design, Setting, and Participants:This retrospective cohort study included patients with OSA who underwent implant with an HGNS from April 2019 to October 2023 at a single tertiary care center and received a postimplant sleep study. During that time, 194 patients underwent HGNS implant. Data were analyzed from February 2024 to April 2024. Intervention or Exposure:HGNS implant and sleep study. Main Outcomes and Measures:Response according to the modified Sher criteria (>50% reduction in AHI score and AHI <15 postimplant). Results:Among the 119 patients included, the median (range) age was 63 (33-79) years, and 36 (30%) were female. Of the 119 included, 83 (70%) were responders. Neck size, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), AHI score, and comorbidity burden were associated with response and used to create a 4-category clinical severity staging system. Patients with small necks (≤14 inches for women or ≤16 inches for men), a BMI of less than 30, and an AHI score of 30 or less had the highest response rate (11 [91%]). Patients with large necks (>14 inches for women or >16 inches for men), a BMI of 30 or greater, an AHI score of 30 or greater, and comorbidities had the lowest response rate (16 [38%]). The staging system had moderate discriminative power, with a C statistic of 0.68 (95% CI, 0.57-0.78). Conclusions and Relevance:The results of this cohort study suggest that neck size, BMI, AHI score, and comorbidity burden are 4 clinically relevant and easily obtainable values that are associated with response to HGNS. While this staging system may help physicians identify patients who are most likely to benefit from implant, these results need to be validated in a separate cohort.

A central goal in translational stroke research is to identify neurophysiological biomarkers that index injury severity and provide information about subsequent functional outcome. Cortical slow oscillations (SOs; 0.1-1.0 Hz) are suppressed after ischemic stroke and recover over the following days to weeks. Whether SO recovery actually tracks behavioral recovery, and whether pre-stroke network organization relates to outcome, has not been tested within individual animals. Using longitudinal wide-field calcium imaging in Thy1-GCaMP6f mice (n = 25), we tracked ipsilateral and contralateral SO power across baseline, 24 hours, and one week after photothrombotic stroke of the left somatosensory forepaw cortex, classifying animals by the presence (STI+; n = 14) or absence (STI-; n = 11) of secondary thalamic injury. Acute ipsilateral SO power was suppressed and tracked concurrent behavioral deficit (ρ = -0.718, p < 0.001), remaining associated with deficit after adjustment for infarct volume (partial ρ = -0.448, p = 0.025). By one week SO power had partially recovered, yet its recovery was dissociated from forelimb use. Week 1 SO power showed no association with behavior in any region or hemisphere (all |ρ| ≤ 0.074, all p > 0.5), and SO recovery did not differ significantly between STI groups despite STI+ animals remaining more impaired (p = 0.011). Pre-stroke SO laterality was associated with week 1 behavioral outcome, independent of infarct size (ρ = -0.518, p = 0.008; partial ρ = -0.446, p = 0.026). Acute SO suppression therefore indexes injury severity beyond infarct volume, whereas spontaneous recovery of SO power is not a reliable surrogate biomarker of week 1 functional outcome. Pre-stroke interhemispheric SO balance emerged as an exploratory candidate source of prognostic information, identifying pre-injury brain state as a dimension that warrants prospective validation.

Maintaining energy balance requires coordination between food intake and energy expenditure, yet the neural pathways that regulate energy expenditure remain unclear. This study identifies kappa opioid receptor-expressing neurons in the preoptic area of the hypothalamus as a key regulator of whole-body metabolism. Using mouse models combined with fiber photometry, chemogenetic activation and inhibition, and chronic disruption of synaptic output, the results show that activity of these neurons follows daily pattern, are suppressed during feeding, and their inhibition acutely increases energy expenditure, body temperature, and activity levels. Long-term inhibition of this population produces sustained weight loss, selective reduction of white fat, preservation of lean mass and brown fat, and improved glucose tolerance even during high-fat feeding. These findings reveal a previously unrecognized circuit that links metabolic state with daily timing cues and suggest that targeting this neuronal population may offer new strategies for treating obesity and related metabolic disorders.

Background:Advances in medicine depend on analyzing large and complex data sources, but discovery is partly constrained by the limited time and domain expertise of human researchers. Agentic artificial intelligence (agentic AI) can accelerate discovery by automating components of the scientific workflow, including information retrieval, data analysis, and knowledge synthesis. Aim:OpenScientist, an open-source agentic AI co-scientist, aims to accelerate biomedical discovery by semi-autonomously investigating scientist-defined queries and generating clinically relevant, verifiable scientific insights. Methods:Domain experts evaluated OpenScientist for novel discoveries in four clinical case studies: (1) a prespecified analysis in a community-based Alzheimer's disease biomarker cohort, (2) unsupervised modeling for plasma proteomic survival prediction, (3) hypothesis investigation in single-cell transcriptomic data from neurons with neurofibrillary tangles, and (4) hypothesis generation with validation in a multiple myeloma dataset with a randomized negative control. Results:OpenScientist completed analyses in minutes that otherwise would take weeks to months of human time and expertise. It identified %ptau217 as the best predictor of amyloid PET status, generated a plasma proteomic survival model with performance comparable to published models, proposed a mechanism linking tau pathology to altered lysosomal acidification, and generated multiple myeloma hypotheses that were validated in an external cohort while distinguishing true signal from randomized controls. Conclusion:OpenScientist demonstrates that open, auditable, agentic AI can support real-world clinical research by generating hypotheses, executing analyses, and discovering insights from complex datasets.

Neural activity in the delta range (1.0-4.5 Hz) during non-rapid eye movement (NREM) sleep is crucial for brain plasticity and overall brain health. Recent research has shown that changes in NREM delta activity can occur locally, and activity can vary across different brain regions. Ischemic stroke results in focal brain injury and long-term disability. While sleep disruption during the acute phase of stroke is known to hinder recovery, the relationship between region-specific changes in NREM delta activity and functional recovery remains poorly understood. To investigate these localized changes in NREM delta activity with high spatial resolution, we utilized wide-field optical imaging (WFOI) in mice that expressed GCaMP6f, a fluorescent calcium indicator, in cortical excitatory pyramidal neurons. Sleep was longitudinally recorded before and at 24 hours, one week, and four weeks after photothrombotic stroke in the left somatosensory forepaw cortex. In the acute phase of stroke (24 hours post stroke), mice exhibited decreased delta activity in the infarct and peri-infarct regions during NREM sleep. Increased delta activity in the contralesional hemisphere and decreased delta activity in the perilesional region during NREM sleep in the acute phase were associated with poor behavioral recovery, as measured by performance on the cylinder rearing test. These findings suggest that region-specific NREM delta activity may play a crucial role in stroke recovery and warrant further investigation to determine whether modulating delta activity in targeted brain areas during NREM sleep could aid recovery.

BACKGROUND:Affective instability is a form of emotion dysregulation and a known precursor to affective disorders. Sleep plays a critical role in emotional regulation. Survivors of stroke frequently experience disrupted sleep that contributes to affective disturbances, but the specific dimensions of sleep health associated with affective instability remain unclear. OBJECTIVE:To examine the associations between dimensions of sleep health and affective instability in survivors of stroke. METHODS:A secondary analysis of a 7-day prospective study involving 40 community-dwelling survivors of stroke who completed daily sleep diaries and eight daily ecological momentary assessments (EMA). Affective instability was assessed with EMA and quantified using mean squared successive difference (MSSD) and probability of acute change (PAC). Six dimensions of sleep health were assessed via EMA, sleep diaries, and the Pittsburgh Sleep Quality Index. Multivariable linear regression analyses were conducted to examine associations of sleep health with affective instability. RESULTS:Higher mental fatigue (MSSD: β = .55, p = .001; PAC: β = .76, p < .001), lower sleep efficiency (PAC: β = -.35, p = .036), and longer sleep latency (PAC: β = .38, p = .030) were associated with greater depressed affect instability. More irregular mid-sleep timing (MSSD: β = .57, p < .001; PAC: β = .48, p = .004), more irregular sleep duration (MSSD: β = .43, p = .012), later sleep timing (MSSD: β = .51, p = .002), and longer sleep latency (MSSD: β = .39, p = .020; PAC: β = .39, p = .021) were associated with greater cheerful affect instability. CONCLUSIONS:Poorer sleep efficiency, higher mental fatigue, later sleep timing, and more irregular sleep patterns were associated with greater affective instability. Designing behavioral therapies targeting these sleep health dimensions may reduce affective instability and prevent post-stroke affective disorders.

Understanding the experiences of stroke survivors with sleep disturbances is essential for developing effective interventions for addressing post-stroke sleep disturbances. To explore the experiences, coping strategies, and wishes and needs of stroke survivors with sleep disturbances. Semi-structured interviews were conducted with 15 community-dwelling stroke survivors experiencing sleep disturbances. The thematic content analysis was used to identify key themes. Nine themes about experiences emerged: (a)impact of stroke on sleep, (b)sleep aggravating factors, (c)sleep enhancing factors, (d)sleep disturbances, (e)consequences of sleep disturbances, (f)medication, (g)napping, (h)sleep partner, and (i)help-seeking behaviors. Three themes about coping strategies emerged: (a)adaptive strategies, (b)maladaptive strategies, and (c)health care provider recommended strategies. Three themes reflected wishes and needs: (a)sleep interventions and knowledge of sleep and stroke, (b)health care system communication and support, and (c)medication and equipment usage. These findings emphasize the need for tailored, multifaceted interventions and improved health care support to address post-stroke sleep disturbances effectively.

Introduction Recovery following ischemic stroke is highly variable and often incomplete, underscoring the urgent need to develop novel targeted poststroke treatments. While the mechanisms underlying poststroke recovery remain incompletely understood, sleep fragmentation, a common consequence of stroke, has been linked to worse patient outcomes. Lemborexant is a dual orexin receptor antagonist that promotes sleep by suppressing wakefulness and enhancing sleep continuity. We hypothesized that lemborexant would reduce poststroke sleep disturbances and promote recovery in a rodent model of stroke. Methods We examined the effects of lemborexant (10 mg/kg and 30 mg/kg) and zolpidem (30 mg/kg) on sleep macrostructure, fragmentation, and EEG spectra in both healthy mice and in stroke model mice, which underwent photothrombotic ischemia of the forelimb somatosensory cortex. We also evaluated whether 12 days of drug administration altered infarct volume and functional recovery following the experimental induction of stroke in model mice. Results Lemborexant treatment (30 mg/kg) increased the percentage of NREM sleep, while preserving sleep continuity, in both healthy and stroke model mice. In contrast, zolpidem increased NREM sleep after stroke, but also increased sleep fragmentation in both groups. Lemborexant treatment at 10 mg/kg and 30 mg/kg significantly reduced infarct volume eight weeks after the induction of stroke. In addition, lemborexant-treated mice showed greater use of the impaired limb four weeks after stroke. Interpretation These preclinical findings suggest that lemborexant stabilizes sleep and promotes structural and functional recovery following the experimental induction of stroke in model mice, supporting its potential as a novel therapeutic intervention following ischemic stroke. Summary for Social Media if Published If you and/or a co-author has a X handle that you would like to be tagged, please enter it here. (format: @AUTHORSHANDLE). @EricLandsness What is the current knowledge on the topic? Sleep plays a critical role in structural and functional recovery after stroke, but most pharmacologic sleep aids, such as benzodiazepines and zolpidem, can fragment sleep and impair neuroplasticity. Dual orexin receptor antagonists like lemborexant may offer a newer, mechanistically distinct approach with potential neuroprotective benefits. What question did this study address? This study investigated whether the dual orexin receptor antagonist lemborexant could improve sleep quality, reduce ischemic injury, and enhance functional recovery following stroke in adult mice, compared with the sleep-promoting agent zolpidem. What does this study add to our knowledge? Lemborexant increased NREM sleep without causing fragmentation, reduced infarct volume, and improved motor recovery when administered. These findings suggest that modulating sleep architecture through orexin antagonism during the subacute phase after stroke can promote neural repair and functional recovery. How might this potentially impact on the practice of neurology? Since lemborexant is already FDA-approved for insomnia, these results could be rapidly translated into a therapeutic opportunity to improve stroke recovery through targeted sleep modulation. This approach may shift poststroke care toward integrating neurorestorative, sleep-based interventions during the subacute phase.

Despite major advances in Alzheimer's disease and related diseases (ADRD) research, the translation of discoveries into impactful clinical interventions remains slow. Overwhelming data complexity, fragmented knowledge, and prolonged research cycles hinder progress in understanding and treating neurodegenerative diseases. Artificial intelligence (AI) offers a promising path forward, particularly when developed as a scientist-in-the-loop system that collaborates with researchers throughout the scientific discovery process. This paper introduces the concept of an AI Biomedical Scientist, an intelligent platform designed to support literature synthesis, hypothesis generation, experimental design, and data interpretation. This platform aims to function as a holistic scientific partner, integrating diverse biomedical data and expert reasoning to accelerate discovery. We review commercial and academic efforts and introduce targeted Minimum Viable Products (MVPs) needed for general biomedical research lab utilization of AI, such as robust and accurate tools for literature and data analysis, negative data models, and virtual peer review, with a longer-term vision of foundation models trained directly on biomedical datasets. In AD and neurodegeneration research, such tools are anticipated to deliver efficiency gains ranging from modest improvements in specific research tasks to potential multi-fold accelerations in discovery workflows as systems mature and scale. This review examines the technical foundations, challenges, and anticipated impacts of AI and aims to inform and engage researchers in utilizing these systems to transform biomedical discovery, starting with AD and extending to other complex conditions.

BACKGROUND:Stroke is a leading cause of long-term adult disability. Behavioral testing with animal stroke models, which offers a way to evaluate the effectiveness of new interventions, currently relies on methods that are time- and labor-intensive. Automated behavioral assessments of locomotion and gait have been proposed as an alternative, but it is currently unknown whether they are sensitive enough to assess behavioral deficits following stroke of the forepaw somatosensory cortex. The purpose of this study was to compare a validated, manually assessed behavioral test, cylinder rearing (a measure of forepaw asymmetry during exploration), with automated behavior tests of locomotion in a rodent photothrombotic stroke model. METHODS:We induced a focal photothrombotic stroke in young (12-16 week old) male mice over the left forepaw somatosensory cortex, conducted behavioral testing at acute (48 h) and sub-acute (4 weeks) time points post-stroke, and then correlated behavior deficits to histological measures. RESULTS:Three automated behavioral tests were used in comparison to cylinder rearing: CatWalk (spontaneous gait), DigiGait (forced treadmill locomotion), and open field (a measure of general locomotor activity). Cylinder rearing testing showed significant forepaw asymmetry between stroke and sham groups acutely and sub-acutely after stroke. Catwalk, DigiGait, and open field tests showed no significant differences between groups. When correlating behavior to histological measures of stroke, the presence of secondary thalamic injury (STI) was associated with forepaw asymmetry on cylinder rearing. CONCLUSIONS:These findings illustrate the need to find alternative automated behavioral measures for mouse photothrombotic stroke of the forepaw somatosensory cortex.

Neural activity in the delta range (1.0-4.5 Hz) during non-rapid eye movement (NREM) sleep is crucial for brain plasticity and overall brain health. Recent research has shown that changes in NREM delta activity can occur locally, and activity can vary across different brain regions. Ischemic stroke results in focal brain injury and long-term disability. While sleep disruption during the acute phase of stroke is known to hinder recovery, the relationship between region-specific changes in NREM delta activity and functional recovery remains poorly understood. To investigate these localized changes in NREM delta activity with high spatial resolution, we utilized wide-field optical imaging (WFOI) in mice that expressed GCaMP6f, a fluorescent calcium indicator, in cortical excitatory pyramidal neurons. Sleep was longitudinally recorded before and at 24 hours, 1 week, and 4 weeks after photothrombotic stroke in the left somatosensory forepaw cortex. In the acute phase of stroke (24 hours post-stroke), mice exhibited decreased delta activity in the infarct and peri-infarct regions during NREM sleep. Increased delta activity in the contralesional hemisphere and decreased delta activity in the perilesional region during NREM sleep in the acute phase were associated with poor behavioral recovery, as measured by performance on the cylinder rearing test. These findings suggest that region-specific NREM delta activity may play a crucial role in stroke recovery and warrant further investigation to determine whether modulating delta activity in targeted brain areas during NREM sleep could aid recovery.

Sleep disturbances are associated with the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and primary tauopathies. Here we demonstrate that administration of the dual orexin receptor antagonist lemborexant in the P301S/E4 mouse model of tauopathy improves tau-associated impairments in sleep-wake behavior. It also protects against chronic reactive microgliosis and brain atrophy in male P301S/E4 mice by preventing abnormal phosphorylation of tau. These neuroprotective effects in males were not observed after administration of the nonorexinergic drug zolpidem that similarly promoted nonrapid eye movement sleep. Furthermore, both genetic ablation of orexin receptor 2 and lemborexant treatment reduced wakefulness and decreased seeding and spreading of phosphorylated tau in the brain of wild-type mice. These findings raise the therapeutic potential of targeting sleep by orexin receptor antagonism to prevent abnormal tau phosphorylation and limit tau-induced damage.

Therapeutic hypothermia for stroke has been limited by shivering, increased metabolic demand, and poor patient tolerance. Engaging endogenous thermoregulatory circuits to lower body temperature may overcome these limitations and modulate metabolism, offering an integrated approach to cerebroprotection. Here, we show that chemogenetic activation of neurons in the preoptic area (POA) elicits a torpor-like state in mice, characterized by sustained hypothermia and hypometabolism. In an animal stroke model, this endogenous hypothermic state significantly reduced infarct volume and improved motor outcomes compared to controls, whereas maintaining normothermia attenuated these protective effects. To explore metabolic mechanisms contributing to this state, we performed untargeted metabolomic profiling 30 minutes after POA activation and identified coordinated shifts in nucleotide, phospholipid, and sphingolipid pathways. These rapid, temperature-dependent changes indicate a metabolically reprogrammed state that may enhance neuronal resilience during ischemic stress. Together, our findings suggest that POA-driven hypothermia confers cerebroprotection through specific metabolic adaptations with translational potential.

Sleep disturbances are associated with the pathogenesis of neurodegenerative diseases including Alzheimer’s disease (AD) and primary tauopathies. We have previously shown that APOE4, the strongest genetic risk factor for AD, directly influences the severity of key pathological hallmarks of neurodegeneration including tau deposition, microglial reactivity and brain atrophy. Sleep loss influences tau accumulation and microglial reactivity in both mice and humans, suggesting that sleep loss may contribute to neurodegeneration not only by influencing protein aggregation, but also through an immune mechanism. Therefore, we aimed to investigate whether promoting sleep as a therapeutic strategy could mitigate the damaging effects of chronic microglial reactivity that contribute to tau-mediated neurodegeneration. We used lemborexant, a dual orexin receptor antagonist that promotes sleep in both mice and humans. We orally gavaged P301S/APOE4 mice, a model of tauopathy with brain atrophy, and non-tau depositing APOE4 knock-in mice daily with 30mg/kg lemborexant or vehicle (n = 16-20/genotype and treatment group) at one-hour post-dark onset. Mice were treated from 7.5 months (M), when tau-mediated neuroinflammation is observed without overt neuronal loss in P301S/APOE4 mice, until 9.5M. In P301S/APOE4 mice, lemborexant not only improved tau-associated sleep loss, specifically non-rapid eye movement sleep, but also dramatically reduced pathological tau deposition. Antagonizing orexin receptor signaling improved tau-mediated neurodegeneration noted by a decrease in plasma neurofilament light chain levels, as well as brain atrophy compared to vehicle-treated P301S/APOE4 controls. In support of these findings, lemborexant-treated P301S/APOE4 mice displayed reduced microglial reactivity of disease-associated microglia including immunostaining for CD68 and Clec7a compared to controls. Both astroglial and microglial APOE co-localization were significantly reduced in lemborexant-treated P301S/APOE4 mice, the latter of which is more commonly observed during elevated inflammatory and damaging conditions. Unbiased transcriptome profiling provided potential mechanistic insights into functional pathways influenced by lemborexant in P301S/APOE4 mice, including those regulating synaptic activity such as Slc17a7, Shank1, Shank2 , which was further accompanied by reduced pre- and post-synaptic loss. Our study provides novel therapeutic evidence that antagonizing the orexin signaling pathway using lemborexant is neuroprotective by restoring sleep deficits as well as limiting tau-mediated neuronal and synaptic damage, potentially by suppressing chronic neuroinflammation.

Historically, stroke and ageing have been associated with changes in narrow-band periodic neuronal activity, but recent work has highlighted the importance of broad-band aperiodic activity. Aperiodic activity is represented by the 1/f slope of power spectral density generated by cortical activity. Here we explored changes in both periodic and aperiodic cortical activity in neurologically intact individuals and individuals with stroke, across the lifespan. We compared 'resting state' electroencephalograms from all participants after applying the specparam algorithm, which decomposes the power spectrum into aperiodic and periodic components. We also correlated motor outcomes to average whole cortex spectral slopes within the stroke group. We found a significant flattening (decrease in exponent) of power spectral slope with normal ageing. We found that both ageing and stroke were associated with fewer periodic peaks. Interestingly, we found that stroke was associated with a significant increase in spectral slope, but age moderated this effect. Younger stroke patients showed minimal difference in slope while older stroke patients had significantly steeper slopes (opposite to the direction in normal ageing). We next investigated the lesion locations most associated with changes in slope. Deep lesions were observed to have the greatest influence on cortical spectral slope. Finally, the slope in the stroke group was associated with performance on a test of manual dexterity, but this association was stronger in older individuals, and varied by scalp region. Our data suggest that stroke in the aged brain has unique effects on aperiodic activity possibly reflecting unique influence of injury on cerebral excitation/inhibition balance in aged individuals.

BACKGROUND:Wide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjunct EEG and EMG recordings. However, this process is time-consuming, invasive and often suffers from low inter- and intra-rater reliability. Therefore, an automated sleep state classification method that operates on spatiotemporal WFCI data is desired.NEW METHOD:A hybrid network architecture consisting of a convolutional neural network (CNN) to extract spatial features of image frames and a bidirectional long short-term memory network (BiLSTM) with attention mechanism to identify temporal dependencies among different time points was proposed to classify WFCI data into states of wakefulness, NREM and REM sleep.RESULTS:Sleep states were classified with an accuracy of 84% and Cohen's kappa of 0.64. Gradient-weighted class activation maps revealed that the frontal region of the cortex carries more importance when classifying WFCI data into NREM sleep while posterior area contributes most to the identification of wakefulness. The attention scores indicated that the proposed network focuses on short- and long-range temporal dependency in a state-specific manner.COMPARISON WITH EXISTING METHOD:On a 3-hour WFCI recording, the CNN-BiLSTM achieved a kappa of 0.67, comparable to a kappa of 0.65 corresponding to the human EEG/EMG-based scoring.CONCLUSIONS:The CNN-BiLSTM effectively classifies sleep states from spatiotemporal WFCI data and will enable broader application of WFCI in sleep.

Abstract Introduction Affective instability, a form of emotion dysregulation, is defined by rapid and intense shifts in affect and a known precursor of affective disorders. Poor sleep health leads to emotional dysregulation and affective instability. Poor sleep health is common after stroke, but which specific aspects of sleep health are important is unclear. We hypothesized that a multidimensional assessment of sleep health would identify specific factors that contribute to affective instability in stroke survivors. Methods Forty community-dwelling stroke survivors underwent multidimensional sleep health assessment with sleep diaries, the Pittsburgh Sleep Quality Index and ecological momentary assessment of affect and alertness eight times daily for seven days. Sleep health was quantified into 6 domains of the Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration (RU-SATED) framework. Affective instability was quantified using probability of acute change (PAC) and mean squared successive difference (MSSD). Multivariable linear regressions were used to identify sleep health factors associated with affective instability, adjusting for age, sex, and race. Results Instability of depressed affect was associated with lower alertness (MSSD: B=.55, p=.001; PAC: B=.76, p<.001), lower sleep efficiency (B=.35, p=.036), and longer sleep latency (B=.38, p=0.30). Instability of cheerful affect was associated with less regular mid-sleep time (MSSD: B=.57, p<.001; PAC: B=.48, p=.004), less regular sleep duration (B=.43, p=.012), and longer sleep latency (MSSD: B=.39, p=.020; PAC: B=.39, p=.021). Conclusion Lower sleep efficiency, longer sleep latency, lower alertness, and irregular sleep contribute to affective instability among stroke survivors. Future intervention efforts managing these specific factors of sleep health to stabilize affective changes and prevent affective disorders after stroke are needed. Support (if any)

Normal aging is associated with widespread changes in neuronal structure, function, and activity. The consequences of focal brain injury on global neuronal activity in aged individuals are poorly understood. Historically, stroke and aging have been associated with changes in narrow-band periodic neuronal activity, however recent work has highlighted the importance of broad-band aperiodic activity. Aperiodic activity is represented by the 1/f slope of power spectral density generated by cortical activity. Abnormalities in aperiodic activity have been identified in psychiatric disorders and stroke, are associated with cognitive dysfunction in aging, and have been hypothesized to reflect changes in excitation/inhibition balance. Here we sought to further explore changes in both periodic and aperiodic cortical activity in neurotypical intact young and aged healthy individuals and individuals with stroke. We compared resting state electroencephalograms from all participants after applying the specparam algorithm, which decomposes the power spectrum into aperiodic and periodic components. We also correlated stroke outcomes using previously obtained tests of motor outcome (box and block) to average whole cortex spectral slopes within the stroke group. Consistent with prior work we found a significant flattening (decrease in exponent) of power spectral slope with normal aging. We also found that both aging and stroke were associated with fewer periodic peaks within the power spectrum. Interestingly, we found that stroke was associated with a significant increase in spectral slope, but age moderated this effect. Younger stroke patients showed minimal difference in slope while older stroke patients had significantly steeper slopes (opposite to the direction in normal aging). Using MRIs from stroke participants we investigated the lesion locations most associated with changes in slope. Interestingly deep lesions were observed to have the greatest influence on cortical spectral slope. Finally, slope in the stroke group was correlated with performance on a test of manual dexterity, however this correlation was much more significant in aged individuals. Our data suggest that stroke in the aged brain has unique effects on aperiodic activity possibly reflecting unique influence of injury on cerebral excitation/inhibition balance in aged individuals and that the degree of these changes may be related to stroke outcomes. ### Competing Interest Statement The authors have declared no competing interest.

Wide-field calcium imaging (WFCI) that records neural calcium dynamics allows for identification of functional brain networks (FBNs) in mice that express genetically encoded calcium indicators. Estimating FBNs from WFCI data is commonly achieved by use of seed-based correlation (SBC) analysis and independent component analysis (ICA). These two methods are conceptually distinct and each possesses limitations. Recent success of unsupervised representation learning in neuroimage analysis motivates the investigation of such methods to identify FBNs. In this work, a novel approach referred as LSTM-AER, is proposed in which a long short-term memory (LSTM) autoencoder (AE) is employed to learn spatial-temporal latent embeddings from WFCI data, followed by an ordinary least square regression (R) to estimate FBNs. The goal of this study is to elucidate and illustrate, qualitatively and quantitatively, the FBNs identified by use of the LSTM-AER method and compare them to those from traditional SBC and ICA. It was observed that spatial FBN maps produced from LSTM-AER resembled those derived by SBC and ICA while better accounting for intra-subject variation, data from a single hemisphere, shorter epoch lengths and tunable number of latent components. The results demonstrate the potential of unsupervised deep learning-based approaches to identifying and mapping FBNs.