Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data.

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 κ 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 held out, repeated 3-hour WFCI recording, the CNN-BiLSTM achieved a κ of 0.67, comparable to a κ 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 research.

Evaluating the interaction between hemorrhagic transformation and cerebral edema on functional outcome after ischemic stroke.

BACKGROUND: Hemorrhagic transformation (HT) and cerebral edema (CED) are both major complications following ischemic stroke, but few studies have evaluated their overlap. We evaluated the frequency and predictors of CED/HT overlap and whether their co-occurrence impacts functional outcome more than each in isolation. METHODS: 892 stroke patients enrolled in a prospective study had follow-up CT imaging evaluated for HT and CED; the latter was quantified using the ratio of hemispheric CSF volumes (with hemispheric CSF ratio < 0.90 used as the CED threshold). The interaction between HT and CED on functional outcome (using modified Rankin Scale at 3 months) was compared to that for each condition separately. RESULTS: Among the 275 (31%) who developed HT, 233 (85%) manifested hemispheric CSF ratio < 0.9 (CED/HT), with this overlap group representing half of the 475 with measurable CED. Higher baseline NIHSS scores and larger infarct volumes were observed in the CED/HT group compared with those with CED or HT alone. Functional outcome was worse in those with CED/HT [median mRS 3 (IQR 2-5)] than those with CED [median 2 (IQR 1-4)] or HT alone [median 1 (IQR 0-2), p < 0.0001]. Overlap of CED/HT independently predicted worse outcome [OR 1.89 (95% CI: 1.12-3.18), p = 0.02] while HT did not; however, CED/HT was no longer associated with worse outcome after adjusting for severity of CED [adjusted OR 0.35 (95% CI: 0.23, 0.51) per 0.21 lower hemispheric CSF ratio, p < 0.001]. CONCLUSIONS: Most stroke patients with HT also have measurable CED. The co-occurrence of CED and HT occurs in larger and more severe strokes and is associated with worse functional outcome, although this is driven by greater severity of stroke-related edema in those with HT.

Intracranial aneurysms in sickle cell disease are associated with hemodynamic stress and anemia.

While hemodynamic stress plays a key role in aneurysm formation outside of SCD, its role is understudied in patients with SCD. We hypothesized that tissue-based markers of hemodynamic stress are associated with aneurysm presence in a prospective SCD cohort. Children and adults with SCD, with and without aneurysms, underwent longitudinal brain MRI/MRA to assess cerebral blood flow (CBF) and oxygen extraction fraction (OEF). Baseline characteristics were recorded. In the subgroup of adults, stepwise mixed-effect logistic regression examined clinical variables, CBF, and OEF as predictors of aneurysm presence. Cumulative rates of new aneurysm formation were estimated using Kaplan-Meier analyses. Forty-three aneurysms were found in 27 of 155 patients (17%). Most aneurysms were ≤ 3 mm and in the intracranial internal carotid artery. On univariate analysis, older age (p=0.07), lower hemoglobin (p=0.002), higher CBF (p=0.03), and higher OEF (p=0.02) were associated with aneurysm presence. On multivariable analysis, age and CBF remained independently associated with aneurysm presence. Seventy-six patients (49% of enrollment) received follow-up MRAs (median 3.5 years). No aneurysm grew or ruptured, however, seven new aneurysms developed in six patients. The three-year cumulative rate of aneurysm formation was 3.5%. In 155 patients with SCD, 17% had intracranial aneurysms. Three-year aneurysm formation rate was 3.5%, although limited by small longitudinal sample size and short follow-up duration. Aneurysm presence was associated with elevated CBF in adults, as a tissue-based marker of cerebral hemodynamic stress. Future studies may examine the predictive role of CBF in aneurysm development in SCD.

Effects of Amyloid Beta (Aß) Oligomers on Blood-Brain Barrier Using a 3D Microfluidic Vasculature-on-a-Chip Model.

The disruption of the blood-brain barrier (BBB) in Alzheimer's Disease (AD) is largely influenced by amyloid beta (Aß). In this study, we developed a high-throughput microfluidic BBB model devoid of a physical membrane, featuring endothelial cells interacting with an extracellular matrix (ECM). This paper focuses on the impact of varying concentrations of Aß1-42 oligomers on BBB dysfunction by treating them in the luminal. Our findings reveal a pronounced accumulation of Aß1-42 oligomers at the BBB, resulting in the disruption of tight junctions and subsequent leakage evidenced by a barrier integrity assay. Additionally, cytotoxicity assessments indicate a concentration-dependent increase in cell death in response to Aß1-42 oligomers (LC50 ~ 1 µM). This study underscores the utility of our membrane-free vascular chip in elucidating the dysfunction induced by Aß with respect to the BBB.

Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

Transcutaneous electrical nerve stimulation (TENS) for pain control in women with primary dysmenorrhoea.

BACKGROUND: Transcutaneous electrical nerve stimulation (TENS) is a non-pharmacological treatment that works by delivering electrical currents via electrodes attached to the skin at the site of pain. It can be an alternative to pharmacological treatments. The mechanism of action of TENS for pain relief is related to the inhibition of the transmission of painful stimuli, release of endogenous opioids, and reduced muscle ischaemia of the uterus. Although it has been used for primary dysmenorrhoea ((PD); period pain or menstrual cramps), evidence of the efficacy and safety of high-frequency TENS, low-frequency TENS, or other treatments for PD is limited. OBJECTIVES: To evaluate the effectiveness and safety of transcutaneous electrical nerve stimulation (TENS) in comparison with placebo, no treatment, and other treatments for primary dysmenorrhoea (PD). SEARCH METHODS: We searched the Gynaecology and Fertility Group's Specialized Register of controlled trials, CENTRAL, MEDLINE, Embase, PsycINFO, AMED, CINAHL, and the Korean and Chinese language databases up to 9 April 2024. We also searched for ongoing trials in trials registries and the reference lists of relevant studies for additional trials. Language restrictions were not applied. SELECTION CRITERIA: We included randomized controlled trials (RCTs) that included women (aged 12 to 49 years) with PD. Included trials compared low-frequency TENS or high-frequency TENS with other TENS, placebo, or other treatment. DATA COLLECTION AND ANALYSIS: Four review authors screened the trials, extracted the data according to the protocol, assessed the risk of bias using RoB 2, and assessed the certainty of evidence for all review comparisons and primary outcomes (i.e. pain relief and adverse effects) using the GRADE approach. MAIN RESULTS: This review replaces the current review, published in 2009. We included 20 RCTs involving 585 randomized women with high-frequency TENS, low-frequency TENS, placebo or no treatment, or other treatment. We included five comparisons: high-frequency TENS versus placebo or no treatment, low-frequency TENS versus placebo or no treatment, high-frequency TENS versus low-frequency TENS, high-frequency TENS versus other treatments, and low-frequency TENS versus other treatments. High-frequency TENS versus placebo or no treatment High-frequency TENS may reduce pain compared with placebo or no treatment (mean difference (MD) -1.39, 95% confidence interval (CI) -2.51 to -0.28; 10 RCTs, 345 women; low-certainty evidence; I2 = 88%). Two out of three RCTs reported no adverse effects and hence we were unable to estimate the effect of high-frequency TENS on adverse effects. Low-frequency TENS versus placebo or no treatment Low-frequency TENS may reduce pain compared with placebo or no treatment (MD -2.04, 95% CI -2.95 to -1.14; 3 RCTs, 645 women; low-certainty evidence; I2 = 0%). No trials reported adverse effects for this comparison. High-frequency TENS versus low-frequency TENS It is uncertain whether high-frequency TENS had an effect on pain relief compared with low-frequency TENS (MD 0.89, 95% CI -0.19 to 1.96; 3 RCTs, 54 women; low-certainty evidence; I2 = 0%). One trial contributed data on adverse effects but no adverse events occurred. High-frequency TENS versus other treatments It is uncertain whether high-frequency TENS had an effect on pain relief compared to acupressure (MD -0.66, 95% CI -1.72 to 0.40; 1 RCT, 18 women; very low-certainty evidence), acetaminophen (paracetamol) (MD -0.98, 95% CI -3.30 to 1.34; 1 RCT, 20 women; very low-certainty evidence), and interferential current therapy (MD -0.03, 95% CI -1.04 to 0.98; 2 RCTs, 62 women; low-certainty evidence; I2 = 0%). The occurrence of adverse effects did not differ significantly between high-frequency TENS and NSAIDs (OR 12.06, 95% CI 0.26 to 570.62; 2 RCTs, 88 women; low-certainty evidence; I2 = 78%). Low-frequency TENS versus other treatments It is uncertain whether low-frequency TENS had an effect on pain relief compared with acetaminophen (MD -1.48, 95% CI -3.61 to 0.65; 1 RCT, 20 women; very low-certainty evidence). No trials reported adverse effects for this comparison. AUTHORS' CONCLUSIONS: High-frequency TENS and low-frequency TENS may reduce pain compared with placebo or no treatment. We downgraded the certainty of the evidence because of the risk of bias. Future RCTs should focus more on secondary outcomes of this review (e.g. requirement for additional analgesics, limitation of daily activities, or health-related quality of life) and should be designed to ensure a low risk of bias.

Reversibility of Cognitive Deficits and Functional Connectivity With Transfusion in Children With Sickle Cell Disease.

BACKGROUND AND OBJECTIVES: People with sickle cell disease (SCD) are at risk of cognitive dysfunction independent of stroke. Diminished functional connectivity in select large-scale networks and white matter integrity reflect the neurologic consequences of SCD. Because chronic transfusion therapy is neuroprotective in preventing stroke and strengthening executive function abilities in people with SCD, we hypothesized that red blood cell (RBC) transfusion facilitates the acute reversal of disruptions in functional connectivity while white matter integrity remains unaffected. METHODS: Children with SCD receiving chronic transfusion therapy underwent a brain MRI measuring white matter integrity with diffusion tensor imaging and resting-state functional connectivity within 3 days before and after transfusion of RBCs. Cognitive assessments with the NIH Toolbox were acquired after transfusion and then immediately before the following transfusion cycle. RESULTS: Sixteen children with a median age of 12.5 years were included. Global assessments of functional connectivity using homotopy (p = 0.234) or modularity (p = 0.796) did not differ with transfusion. Functional connectivity within the frontoparietal network significantly strengthened after transfusion (median intranetwork Z-score 0.21 [0.17-0.30] before transfusion, 0.29 [0.20-0.36] after transfusion, p < 0.001), while there was not a significant change seen within the sensory motor, visual, auditory, default mode, dorsal attention, or cingulo-opercular networks. Corresponding to the change within the frontoparietal network, there was a significant improvement in executive function abilities after transfusion (median executive function composite score 87.7 [81.3-90.7] before transfusion, 90.3 [84.3-93.7] after transfusion, p = 0.021). Participants with stronger connectivity in the frontoparietal network before transfusion had a significantly greater improvement in the executive function composite score with transfusion (r = 0.565, 95% CI 0.020-0.851, p = 0.044). While functional connectivity and executive abilities strengthened with transfusion, there was not a significant change in white matter integrity as assessed by fractional anisotropy and mean diffusivity within 16 white matter tracts or globally with tract-based spatial statistics. DISCUSSION: Strengthening of functional connectivity with concomitant improvement in executive function abilities with transfusion suggests that functional connectivity MRI could be used as a biomarker for acutely reversible neurocognitive injury as novel therapeutics are developed for people with SCD.

Chimeric antigen receptor macrophages target and resorb amyloid plaques.

Substantial evidence suggests a role for immunotherapy in treating Alzheimer's disease (AD). While the precise pathophysiology of AD is incompletely understood, clinical trials of antibodies targeting aggregated forms of ß amyloid (Aß) have shown that reducing amyloid plaques can mitigate cognitive decline in patients with early-stage AD. Here, we describe what we believe to be a novel approach to target and degrade amyloid plaques by genetically engineering macrophages to express an Aß-targeting chimeric antigen receptor (CAR-Ms). When injected intrahippocampally, first-generation CAR-Ms have limited persistence and fail to significantly reduce plaque load, which led us to engineer next-generation CAR-Ms that secrete M-CSF and self-maintain without exogenous cytokines. Cytokine secreting "reinforced CAR-Ms" have greater survival in the brain niche and significantly reduce plaque load locally in vivo. These findings support CAR-Ms as a platform to rationally target, resorb, and degrade pathogenic material that accumulates with age, as exemplified by targeting Aß in AD.

Comparison of cerebral oxygen extraction fraction using ASE and TRUST methods in patients with sickle cell disease and healthy controls.

Abnormal oxygen extraction fraction (OEF), a putative biomarker of cerebral metabolic stress, may indicate compromised oxygen delivery and ischemic vulnerability in patients with sickle cell disease (SCD). Elevated OEF was observed at the tissue level across the brain using an asymmetric spin echo (ASE) MR method, while variable global OEFs were found from the superior sagittal sinus (SSS) using a T2-relaxation-under-spin-tagging (TRUST) MRI method with different calibration models. In this study, we aimed to compare the average ASE-OEF in the SSS drainage territory and TRUST-OEF in the SSS from the same SCD patients and healthy controls. 74 participants (SCD: N = 49; controls: N = 25) underwent brain MRI. TRUST-OEF was quantified using the Lu-bovine, Bush-HbA and Li-Bush-HbS models. ASE-OEF and TRUST-OEF were significantly associated in healthy controls after controlling for hematocrit using the Lu-bovine or the Bush-HbA model. However, no association was found between ASE-OEF and TRUST-OEF in patients with SCD using either the Bush-HbA or the Li-Bush-HbS model. Plausible explanations include a discordance between spatially volume-averaged oxygenation brain tissue and flow-weighted volume-averaged oxygenation in SSS or sub-optimal calibration in SCD. Further work is needed to refine and validate non-invasive MR OEF measurements in SCD.

Attention-Based CNN-BiLSTM for Sleep State Classification of Spatiotemporal Wide-Field Calcium Imaging Data.

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.

Impact of Sleep Disorders and Disturbed Sleep on Brain Health: A Scientific Statement From the American Heart Association.

Accumulating evidence supports a link between sleep disorders, disturbed sleep, and adverse brain health, ranging from stroke to subclinical cerebrovascular disease to cognitive outcomes, including the development of Alzheimer disease and Alzheimer disease-related dementias. Sleep disorders such as sleep-disordered breathing (eg, obstructive sleep apnea), and other sleep disturbances, as well, some of which are also considered sleep disorders (eg, insomnia, sleep fragmentation, circadian rhythm disorders, and extreme sleep duration), have been associated with adverse brain health. Understanding the causal role of sleep disorders and disturbances in the development of adverse brain health is complicated by the common development of sleep disorders among individuals with neurodegenerative disease. In addition to the role of sleep disorders in stroke and cerebrovascular injury, mechanistic hypotheses linking sleep with brain health and biomarker data (blood-based, cerebrospinal fluid-based, and imaging) suggest direct links to Alzheimer disease-specific pathology. These potential mechanisms and the increasing understanding of the "glymphatic system," and the recognition of the importance of sleep in poststroke recovery, as well, support a biological basis for the indirect (through the worsening of vascular disease) and direct (through specific effects on neuropathology) connections between sleep disorders and brain health. Given promising evidence for the benefits of treatment and prevention, sleep disorders and disturbances represent potential targets for early treatment that may improve brain health more broadly. In this scientific statement, we discuss the evidence supporting an association between sleep disorders and disturbances and poor brain health ranging from stroke to dementia and opportunities for prevention and early treatment.

Intraindividual variability in post-stroke cognition and its relationship with activities of daily living and social functioning: an ecological momentary assessment approach.

INTRODUCTION: Ecological momentary assessment (EMA) is a methodological approach to studying intraindividual variation over time. This study aimed to use EMA to determine the variability of cognition in individuals with chronic stroke, identify the latent classes of cognitive variability, and examine any differences in daily activities, social functioning, and neuropsychological performance between these latent classes. METHODS: Participants (N = 202) with mild-to-moderate stroke and over 3-month post-stroke completed a study protocol, including smartphone-based EMA and two lab visits. Participants responded to five EMA surveys daily for 14 days to assess cognition. They completed patient-reported measures and neuropsychological assessments during lab visits. Using latent class analysis, we derived four indicators to quantify cognitive variability and identified latent classes among participants. We used ANOVA and Chi-square to test differences between these latent classes in daily activities, social functioning, and neuropsychological performance. RESULTS: The latent class analysis converged on a three-class model. The moderate and high variability classes demonstrated significantly greater problems in daily activities and social functioning than the low class. They had significantly higher proportions of participants with problems in daily activities and social functioning than the low class. Neuropsychological performance was not statistically different between the three classes, although a trend approaching statistically significant difference was observed in working memory and executive function domains. DISCUSSION: EMA could capture intraindividual cognitive variability in stroke survivors. It offers a new approach to understanding the impact and mechanism of post-stroke cognitive problems in daily life and identifying individuals benefiting from self-regulation interventions.

Arousal as a universal embedding for spatiotemporal brain dynamics.

Neural activity in awake organisms shows widespread and spatiotemporally diverse correlations with behavioral and physiological measurements. We propose that this covariation reflects in part the dynamics of a unified, arousal-related process that regulates brain-wide physiology on the timescale of seconds. Taken together with theoretical foundations in dynamical systems, this interpretation leads us to a surprising prediction: that a single, scalar measurement of arousal (e.g., pupil diameter) should suffice to reconstruct the continuous evolution of multimodal, spatiotemporal measurements of large-scale brain physiology. To test this hypothesis, we perform multimodal, cortex-wide optical imaging and behavioral monitoring in awake mice. We demonstrate that spatiotemporal measurements of neuronal calcium, metabolism, and blood-oxygen can be accurately and parsimoniously modeled from a low-dimensional state-space reconstructed from the time history of pupil diameter. Extending this framework to behavioral and electrophysiological measurements from the Allen Brain Observatory, we demonstrate the ability to integrate diverse experimental data into a unified generative model via mappings from an intrinsic arousal manifold. Our results support the hypothesis that spontaneous, spatially structured fluctuations in brain-wide physiology-widely interpreted to reflect regionally-specific neural communication-are in large part reflections of an arousal-related process. This enriched view of arousal dynamics has broad implications for interpreting observations of brain, body, and behavior as measured across modalities, contexts, and scales.