Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI.

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

White matter alterations and their associations with biomarkers and behavior in subjective cognitive decline individuals: a fixel-based analysis.

BACKGROUND: Subjective cognitive decline (SCD) is an early stage of dementia linked to Alzheimer's disease pathology. White matter changes were found in SCD using diffusion tensor imaging, but there are known limitations in voxel-wise tensor-based methods. Fixel-based analysis (FBA) can help understand changes in white matter fibers and how they relate to neurodegenerative proteins and multidomain behavior data in individuals with SCD. METHODS: Healthy adults with normal cognition were recruited in the Northeastern Taiwan Community Medicine Research Cohort in 2018-2022 and divided into SCD and normal control (NC). Participants underwent evaluations to assess cognitive abilities, mental states, physical activity levels, and susceptibility to fatigue. Neurodegenerative proteins were measured using an immunomagnetic reduction technique. Multi-shell diffusion MRI data were collected and analyzed using whole-brain FBA, comparing results between groups and correlating them with multidomain assessments. RESULTS: The final enrollment included 33 SCD and 46 NC participants, with no significant differences in age, sex, or education between the groups. SCD had a greater fiber-bundle cross-section than NC (pFWE < 0.05) at bilateral frontal superior longitudinal fasciculus II (SLFII). These white matter changes correlate negatively with plasma Aß42 level (r = -0.38, p = 0.01) and positively with the AD8 score for subjective cognitive complaints (r = 0.42, p = 0.004) and the Hamilton Anxiety Rating Scale score for the degree of anxiety (Ham-A, r = 0.35, p = 0.019). The dimensional analysis of FBA metrics and blood biomarkers found positive correlations of plasma neurofilament light chain with fiber density at the splenium of corpus callosum (pFWE < 0.05) and with fiber-bundle cross-section at the right thalamus (pFWE < 0.05). Further examination of how SCD grouping interacts between the correlations of FBA metrics and multidomain assessments showed interactions between the fiber density at the corpus callosum with letter-number sequencing cognitive score (pFWE < 0.01) and with fatigue to leisure activities (pFWE < 0.05). CONCLUSION: Based on FBA, our investigation suggests white matter structural alterations in SCD. The enlargement of SLFII's fiber cross-section is linked to plasma Aß42 and neuropsychiatric symptoms, which suggests potential early axonal dystrophy associated with Alzheimer's pathology in SCD. The splenium of the corpus callosum is also a critical region of axonal degeneration and cognitive alteration for SCD.

Micro-scale urbanization-based risk factors for dengue epidemics.

Dengue is one of the world's most rapidly spreading mosquito-borne viral diseases. As it is found mostly in urban and semi-urban areas, urbanization and associated human activities that affect the environment and larval habitats could become risk factors (e.g., lane width, conditions of street ditches) for the spread of dengue. However, there are currently no systematic studies of micro-scale urbanization-based risk factors for the spread of dengue epidemics. We describe the study area, two micro-scale environmental risk factors associated with urbanization, and meteorological data. Since the observations involve spatial and temporal correlations, we also use some statistical methods for the analysis of spatial and spatial-temporal data for the relationship between urbanization and dengue. In this study, we analyzed data from Kaohsiung, a densely populated city in southern Taiwan, and found a positive correlation between environmental risk factors associated with urbanization (ditches positive for mosquito larvae and closely packed streets termed "dengue lanes") and clustering effects in dengue cases. The statistical analysis also revealed that the occurrence of positive ditches was significantly associated with that of dengue lanes in the study area. The relationship between climate variables and positive ditches was also analyzed in this paper, indicating a relationship between dengue and both rainfall and temperature, with temperature having a greater effect. Overall, this work is immediately relevant and applicable for policymakers in government, who will need to reduce these favorable habitats for vector-born disease spreaders and implement regulations for new urban constructions to thus reduce dengue spread in future outbreaks.

Integrated diffusion image operator (iDIO): A pipeline for automated configuration and processing of diffusion MRI data.

The preprocessing of diffusion magnetic resonance imaging (dMRI) data involve numerous steps, including the corrections for head motion, susceptibility distortion, low signal-to-noise ratio, and signal drifting. Researchers or clinical practitioners often need to configure different preprocessing steps depending on disparate image acquisition schemes, which increases the technical threshold for dMRI analysis for nonexpert users. This could cause disparities in data processing approaches and thus hinder the comparability between studies. To make the dMRI data processing steps transparent and adapt to various dMRI acquisition schemes for researchers, we propose a semi-automated pipeline tool for dMRI named integrated diffusion image operator or iDIO. This pipeline integrates features from a wide range of advanced dMRI software tools and targets at providing a one-click solution for dMRI data analysis, via adaptive configuration for a set of suggested processing steps based on the image header of the input data. Additionally, the pipeline provides options for post-processing, such as estimation of diffusion tensor metrics and whole-brain tractography-based connectomes reconstruction using common brain atlases. The iDIO pipeline also outputs an easy-to-interpret quality control report to facilitate users to assess the data quality. To keep the transparency of data processing, the execution log and all the intermediate images produced in the iDIO's workflow are accessible. The goal of iDIO is to reduce the barriers for clinical or nonspecialist users to adopt the state-of-art dMRI processing steps.

Stock Market Forecasting Based on Spatiotemporal Deep Learning.

This study introduces the Spacetimeformer model, a novel approach for predicting stock prices, leveraging the Transformer architecture with a time-space mechanism to capture both spatial and temporal interactions among stocks. Traditional Long-Short Term Memory (LSTM) and recent Transformer models lack the ability to directly incorporate spatial information, making the Spacetimeformer model a valuable addition to stock price prediction. This article uses the ten minute stock prices of the constituent stocks of the Taiwan 50 Index and the intraday data of individual stock on the Taiwan Stock Exchange. By training the Timespaceformer model with multi-time-step stock price data, we can predict the stock prices at every ten minute interval within the next hour. Finally, we also compare the prediction results with LSTM and Transformer models that only consider temporal relationships. The research demonstrates that the Spacetimeformer model consistently captures essential trend changes and provides stable predictions in stock price forecasting. This article proposes a Spacetimeformer model combined with daily moving windows. This method has superior performance in stock price prediction and also demonstrates the significance and value of the space-time mechanism for prediction. We recommend that people who want to predict stock prices or other financial instruments try our proposed method to obtain a better return on investment.

Psychometric properties of the Chinese version of the Centrality of Event Scale across multiple trauma-exposed Taiwanese samples.

The widely used Centrality of Event Scale (CES) measures the extent that a traumatic event serves as a central component of self-identity, a reference point, and a turning point in an individual's life story. The present study aimed to develop a Chinese version of the CES and assess its reliability, criterion validity, and factor structure. Data were collected from three samples of trauma-exposed Taiwanese individuals (N = 939), including 420 earthquake survivors, 300 trauma-exposed community adults, and 219 trauma-exposed undergraduate students. We conducted an exploratory factor analysis and confirmatory factor analysis and compared the resulting models with a one-factor model and the originally proposed model. The results indicated that a new three-factor model, S-Bχ2 (167, N = 519) = 687.01, p < .001, CFI = .95, IFI = .95, NNFI = .94, RMSEA = .078, SRMR = .047, might better represent the construct compared to the one-factor or originally proposed model. Furthermore, the Chinese CES demonstrated excellent internal consistency, Cronbach's αs = .89-.94; adequate 1-month reliability, rs = .54-.64, and 6-month temporal stability, rs = .52-.67; and good concurrent and predictive validity. The findings indicate that the Chinese version of the CES demonstrates good psychometric properties with a three-factor structure, and it could be used to assess event centrality among nonclinical trauma-exposed Taiwanese adults.

Structural and functional connectivity mapping of the human corpus callosum organization with white-matter functional networks.

The corpus callosum serves as a crucial organization for understanding the information integration between the two hemispheres. Our previous study explored the functional connectivity between the corpus callosum and white-matter functional networks (WM-FNs), but the corresponding physical connectivity remains unknown. The current study uses the resting-state fMRI of Human Connectome Project data to identify ten WM-FNs in 108 healthy subjects, and then independently maps the structural and functional connectivity between the corpus callosum and above WM-FNs using the diffusion tensor images (DTI) tractography and resting-state functional connectivity (RSFC). Our results demonstrated that the structural and functional connectivity between the human corpus callosum and WM-FNs have the following high overall correspondence: orbitofrontal WM-FN, DTI map = 89% and RSFC map = 92%; sensorimotor middle WM-FN, DTI map = 47% and RSFC map = 77%; deep WM-FN, DTI map = 50% and RSFC map = 79%; posterior corona radiata WM-FN, DTI map = 82% and RSFC map = 73%. These findings reinforce the notion that the corpus callosum has unique spatial distribution patterns connecting to distinct WM-FNs. However, important differences between the structural and functional connectivity mapping results were also observed, which demonstrated a synergy between DTI tractography and RSFC toward better understanding the information integration of primary and higher-order functional systems in the human brain.

Quality Assessment of Deep-Frying Palm Oil by Impedimetric Sensing with a Simple and Economic Electrochemical Cell.

Quality control of deep-frying oil is a global public health concern. A simple and economic electrochemical chamber composed of two bare screen-printed carbon electrodes (working area: 78.54 × 102 cm2; distance: 0.0055 cm; cell constant: 0.70 × 10-2 cm-1) was constructed for precisely acquiring the impedimetric responses of a high-resistance palm oil sample (RSD < 7%, n = 3). Good correlations between the measured impedance data (charge transfer resistance and logarithmic output impedance (Log Z) obtained in the frequency region <0.1 Hz) and the regulatory quality indicators (total polar compounds and acid value) were achieved (R2 > 0.97), suggesting that the proposed impedimetric sensing method is useful for accurately assessing the deteriorated condition of repeated frying oil. Applications for rapid screening can also be realized because the measurement times of Log Z at any given perturbation frequency from 0.01-1 Hz were all less than 3 min.

Instability of brain connectivity during nonrapid eye movement sleep reflects altered properties of information integration.

Nonrapid eye movement (NREM) sleep is associated with fading consciousness in humans. Recent neuroimaging studies have demonstrated the spatiotemporal alterations of the brain functional connectivity (FC) in NREM sleep, suggesting the changes of information integration in the sleeping brain. However, the common stationarity assumption in FC does not satisfactorily explain the dynamic process of information integration during sleep. The dynamic FC (dFC) across brain networks is speculated to better reflect the time-varying information propagation during sleep. Accordingly, we conducted simultaneous EEG-fMRI recordings involving 12 healthy men during sleep and observed dFC across sleep stages using the sliding-window approach. We divided dFC into two aspects: mean dFC (dFCmean ) and variance dFC (dFCvar ). A high dFCmean indicates stable brain network integrity, whereas a high dFCvar indicates instability of information transfer within and between functional networks. For the network-based dFC, the dFCvar were negatively correlated with the dFCmean across the waking and three NREM sleep stages. As sleep deepened, the dFCmean decreased (N0~N1 > N2 > N3), whereas the dFCvar peaked during the N2 stage (N0~N1 < N3 < N2). The highest dFCvar during the N2 stage indicated the unstable synchronizations across the entire brain. In the N3 stage, the overall disrupted network integration was observed through the lowest dFCmean and elevated dFCvar, compared with N0 and N1. Conclusively, when the network specificity (dFCmean ) breaks down, the consciousness dissipates with increasing variability of information exchange (dFCvar ).

Prediction of annual dengue incidence by hydro-climatic extremes for southern Taiwan.

Dengue is one of the most rapidly spreading mosquito-borne viral diseases in the world. An increase in the incidence of dengue is commonly thought to be a consequence of variability of weather conditions. Taiwan, which straddles the Tropic of Cancer, is an excellent place to study the relationship between weather conditions and dengue fever cases since the island forms an isolated geographic environment. Therefore, clarifying the association between extreme weather conditions and annual dengue incidence is one of important issues for epidemic early warning. In this paper, we develop a Poisson regression model with extreme weather parameters for prediction of annual dengue incidence. A leave-one-out method is used to evaluate the performance of predicting dengue incidence. Our results indicate that dengue transmission has a positive relationship with the minimum temperature predictors during the early summer while a negative relationship with all the maximum 24-h rainfall predictors during the early epidemic phase of dengue outbreaks. Our findings provide a better understanding of the relationships between extreme weather and annual trends in dengue cases in Taiwan and it could have important implications for dengue forecasts in surrounding areas with similar meteorological conditions.

Gray matter changes related to medication overuse in patients with chronic migraine.

OBJECTIVE: The objective of this article is to investigate the neurological substrates associated with medication overuse (MO) in patients with chronic migraine (CM). METHODS: We recruited age- and sex-matched CM patients with MO (CMwMO), CM patients without MO (CMwoMO), and healthy controls (HCs). Magnetic resonance T1-weighted images were processed by voxel-based morphometry, and the findings were correlated with clinical variables and treatment responses. RESULTS: A total of 66 patients with CM (half with MO) and 33 HCs completed the study. Patients with CMwMO compared to the patients with CMwoMO showed gray matter volume (GMV) decrease in the orbitofrontal cortex and left middle occipital gyrus as well as GMV increase in the left temporal pole/parahippocampus. The GMV changes explained 31.1% variance of the analgesics use frequency. The patients who responded to treatment had greater GMV in the orbitofrontal cortex (p = 0.028). Patients with CM (with and without MO), compared with HCs, had decreased GMV at multiple brain areas including the frontal, temporal and occipital lobes, precuneus and cerebellum. CONCLUSIONS: Our study showed GMV changes in CMwMO patients compared to the CMwoMO patients. These three cerebral regions accounted for significant variance in analgesics use frequency. Moreover, the GMV of the orbitofrontal cortex was predictive of the response to MO treatments.

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan.

Genetic analyses of the FRNK motif function of Turnip mosaic virus uncover multiple and potentially interactive pathways of cross-protection.

Cross-protection triggered by a mild strain of virus acts as a prophylaxis to prevent subsequent infections by related viruses in plants; however, the underling mechanisms are not fully understood. Through mutagenesis, we isolated a mutant strain of Turnip mosaic virus (TuMV), named Tu-GK, that contains an Arg182Lys substitution in helper component-proteinase (HC-Pro(K)) that confers complete cross-protection against infection by a severe strain of TuMV in Nicotiana benthamiana, Arabidopsis thaliana Col-0, and the Arabidopsis dcl2-4/dcl4-1 double mutant defective in DICER-like ribonuclease (DCL)2/DCL4-mediated silencing. Our analyses showed that HC-Pro(K) loses the ability to interfere with microRNA pathways, although it retains a partial capability for RNA silencing suppression triggered by DCL. We further showed that Tu-GK infection triggers strong salicylic acid (SA)-dependent and SA-independent innate immunity responses. Our data suggest that DCL2/4-dependent and -independent RNA silencing pathways are involved, and may crosstalk with basal innate immunity pathways, in host defense and in cross-protection.

Duckweed-based optical biosensor for herbicide toxicity assessment.

In response to the pervasive issue of herbicide pollution in environmental water bodies, particularly from herbicides used extensively in agriculture, traditional chemical-based water quality analysis methods have proven costly and time-consuming, often failing to meet regulatory standards. To overcome these limitations, global environmental agencies have turned to rapidly-growing species like duckweed as bioindicators for herbicide and pesticide contamination. However, conventional biological assessment methods, such as the 168-h duckweed growth inhibition test, are slow and lack real-time monitoring capabilities. To address this challenge, we developed an innovative approach by integrating opto-mechanical technology with duckweed to create a cost-effective biosensor for herbicide detection, priced under $10 USD per system. This advancement allows for the rapid detection of herbicide impacts on duckweed growth within just 48 h, significantly improving upon traditional methods. Our biosensor achieves detection limits of 10 ppm (p < 0.05) for glyphosate and 1 ppm (p < 0.05) for glufosinate, both prominent herbicides globally. This mini-biosensing platform offers a practical alternative to the official method, which requires 168 h and higher thresholds (36.4 ppm for glyphosate and 34.0 ppm for glufosinate) for routine environmental analysis. Thus, these duckweed-based optical biosensors represent a promising advancement in environmental monitoring, enhancing accessibility and efficacy for widespread adoption globally.

Functional blindsight and its diagnosis.

Even when brain scans fail to detect a striate lesion, functional evidence for blindsight can be adduced. In the aftermath of an automobile accident, JK became blind. Results of ophthalmic exams indicated that the blindness must be cortical. Nevertheless, multiple MRI scans failed to detect structural damage to the striate cortex. Prior to the accident JK had been an athlete; after the accident he retained some athletic abilities, arousing suspicions that he might be engaged in fraud. His residual athletic abilities-e.g., hitting a handball or baseball, or catching a Frisbee-coupled with his experienced blindness, suggested blindsight. But due to the apparent absence of striate lesions, we designed a series of tasks for temporal and spatial dimensions in an attempt to detect functional evidence of his disability. Indeed, test results revealed compelling neural evidence that comport with his subjective reports. This spatiotemporal task-related method that includes contrasts with healthy controls, and detailed understanding of the patient's conscious experience, can be generalized for clinical, scientific and forensic investigations of blindsight.

Differential neuropsychiatric associations of plasma biomarkers in older adults with major depression and subjective cognitive decline.

Older adults with major depressive disorder (MDD) or early cognitive decline during the subjective cognitive decline (SCD) stage may exhibit neuropsychiatric symptoms such as anxiety, depression, and subtle cognitive impairment. The clinicopathological features and biological mechanisms of MDD differ from those of SCD among older adults; these conditions thus require different treatment strategies. This study enrolled 82 participants above 50 years old with normal cognitive levels from the communities to examine biomarker-behavior correlations between MDD (n = 23) and SCD (n = 23) relative to a normal control (NC) group (n = 36). Multidomain assessments were performed for all participants, including immunomagnetic reduction tests to detect plasma beta-amyloid (Aß), total tau (Tau), phosphorylated tau-181 (p-Tau181), neurofilament light chain, and glial fibrillary acidic protein (GFAP). This study observed that depressive symptoms in MDD were associated with amyloid pathology (plasma Aß40 vs. HADS-D: R = 0.45, p = 0.031; Aß42/Aß40 vs. HADS-D: R = -0.47, p = 0.024), which was not observed in the NC (group difference p < 0.05). Moreover, cognitive decline in MDD was distinguished by a mixed neurodegenerative process involving amyloid (plasma Aß42 vs. facial memory test: R = 0.48, p = 0.025), tau (Tau/Aß42 vs. digit symbol substitution test (DSST): R = -0.53, p = 0.01), and astrocytic injury (plasma GFAP vs. Montreal cognitive assessment score: R = -0.44, p = 0.038; plasma GFAP vs. DSST: R = -0.52, p = 0.014), findings that did not apply to the NC (group difference p < 0.05). Moreover, this study revealed different biomarker-behavior correlations between individuals with SCD and the NC. Compared with the NC, cognitive decline in the SCD group might be unrelated to amyloid pathology and instead might be early manifestations of tau pathology. This study underscores the difference in clinicopathological features between MDD and SCD among older adults, which differ from those of the NC. These findings enhance our understanding of the mechanisms underlying MDD and SCD in older individuals.

Enhanced anti-obesity activities of red mold dioscorea when fermented using deep ocean water as the culture water.

Deep ocean water (DOW) has, in previous studies, been found to be a novel anti-obesity drink and useful in raising Monascus-produced monascin and ankaflavin levels. This may resolve the limited anti-obesity ability of red mold dioscorea (RMD) known as the Monascus purpureus-fermented Disocorea batatas. This study aims to compare the anti-obesity effect of DOW-cultured RMD (DOW-RMD) and ultra-pure water-cultured RMD (UPW-RMD) in rats fed on a high fat diet. Moreover, the effect of ions composition of DOW and DOW-influenced functional metabolites change of RMD on the differentiation and lipogenesis regulation were investigated using 3T3-L1 pre-adipocytes. In the animal test, compared to UPW-RMD, DOW-RMD possessed better ability to inhibit increases in weight gain, and better feed efficiency, body-fat pad and cross-sectional area of adipocytes. In the cell test, the anti-obesity abilities of DOW-RMD in inhibiting PPARγ and C/EBPα expression in differentiation and lipoprotein lipase activity in lipogenesis were contributed to by the DOW-increased monascin and ankaflavin levels and the ions of DOW, respectively.

Potential of thermoresponsive hydrogel as an alternative therapy for rat knee osteoarthritis.

Osteoarthritis is a degenerative condition that is highly prevalent and primarily affects the joints. The knee is the most commonly affected site, impacting the lives of over 300 million individuals worldwide. This study presents a potential solution to address the unmet need for a minimally invasive technique in the treatment of osteoarthritis: a biocompatible, injectable, and thermoresponsive hydrogel. In comparison to commercially available products such as lyophilized platelets, dextrose, and triamcinolone, the thermoresponsive hydrogel exhibits significantly superior performance in dynamic behaviors, including print area, stability, and step cycle, when tested on rats with knee osteoarthritis. However, it demonstrates similar treatment efficacy to these products in static behaviors, as observed through histopathological and immunohistochemical analysis. Therefore, the thermoresponsive hydrogel holds promise as an effective alternative therapy for osteoarthritis. Moreover, by blending the hydrogel with drugs, controlled and sustained release can be achieved, thereby facilitating the long-term management of osteoarthritis symptoms.

Blood-cerebrospinal fluid barrier opening by modified single pulse transcranial focused shockwave.

Transcranial focused shockwave (FSW) is a novel noninvasive brain stimulation that can open blood-brain barriers (BBB) and blood-cerebrospinal fluid barriers (BCSFB) with a single low-energy (energy flux density 0.03 mJ/mm2) pulse and low-dose microbubbles (2 × 106/kg). Similar to focused ultrasound, FSW deliver highly precise stimulation of discrete brain regions with adjustable focal lengths that essentially covers the whole brain. By opening the BCSFB, it allows for rapid widespread drug delivery to the whole brain by cerebrospinal fluid (CSF) circulation. Although no definite adverse effect or permeant injury was noted in our previous study, microscopic hemorrhage was infrequently observed. Safety concerns remain the major obstacle to further application of FSW in brain. To enhance its applicability, a modified single pulse FSW technique was established that present 100% opening rate but much less risk of adverse effect than previous methods. By moving the targeting area 2.5 mm more superficially on the left lateral ventricle as compared with the previous methods, the microscopic hemorrhage rate was reduced to zero. We systemically examine the safety profiles of the modified FSW-BCSFB opening regarding abnormal behavior and brain injury or hemorrhage 72 hr after 0, 1, and 10 pulses of FSW-treatment. Animal behavior, physiological monitor, and brain MRI were examined and recorded. Brain section histology was examined for hemorrhage, apoptosis, inflammation, oxidative stress related immunohistochemistry and biomarkers. The single pulse FSW group demonstrated no mortality or gross/microscopic hemorrhage (N = 30), and no observable changes in all examined outcomes, while 10 pulses of FSW was found to be associated with microscopic and temporary RBC extravasation (N = 6/30), and abnormal immunohistochemistry biomarkers which showed a trend of recovery at 72 hrs. The results suggest that single pulse low-energy FSW-BCSFB opening is effective, safe and poses minimal risk of injury to brain tissue (Sprague Dawley, SD rats).

Temporal consistency of neurovascular components on awakening: preliminary evidence from electroencephalography, cerebrovascular reactivity, and functional magnetic resonance imaging.

Sleep inertia (SI) is a time period during the transition from sleep to wakefulness wherein individuals perceive low vigilance with cognitive impairments; SI is generally identified by longer reaction times (RTs) in attention tasks immediately after awakening followed by a gradual RT reduction along with waking time. The sluggish recovery of vigilance in SI involves a dynamic process of brain functions, as evidenced in recent functional magnetic resonance imaging (fMRI) studies in within-network and between-network connectivity. However, these fMRI findings were generally based on the presumption of unchanged neurovascular coupling (NVC) before and after sleep, which remains an uncertain factor to be investigated. Therefore, we recruited 12 young participants to perform a psychomotor vigilance task (PVT) and a breath-hold task of cerebrovascular reactivity (CVR) before sleep and thrice after awakening (A1, A2, and A3, with 20 min intervals in between) using simultaneous electroencephalography (EEG)-fMRI recordings. If the NVC were to hold in SI, we hypothesized that time-varying consistencies could be found between the fMRI response and EEG beta power, but not in neuron-irrelevant CVR. Results showed that the reduced accuracy and increased RT in the PVT upon awakening was consistent with the temporal patterns of the PVT-induced fMRI responses (thalamus, insula, and primary motor cortex) and the EEG beta power (Pz and CP1). The neuron-irrelevant CVR did not show the same time-varying pattern among the brain regions associated with PVT. Our findings imply that the temporal dynamics of fMRI indices upon awakening are dominated by neural activities. This is the first study to explore the temporal consistencies of neurovascular components on awakening, and the discovery provides a neurophysiological basis for further neuroimaging studies regarding SI.