Sub-bundle based analysis reveals the role of human optic radiation in visual working memory.

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.

Neurovascular coupling dysfunction associated with cognitive impairment in presbycusis.

The neuropathological mechanism underlying presbycusis remains unclear. This study aimed to illustrate the mechanism of neurovascular coupling associated with cognitive impairment in patients with presbycusis. We assessed the coupling of cerebral blood perfusion with spontaneous neuronal activity by calculating the correlation coefficients between cerebral blood flow and blood oxygen level-dependent-derived quantitative maps (amplitude of low-frequency fluctuation, fractional amplitude of low-frequency fluctuation, regional homogeneity, degree centrality). Four neurovascular coupling metrics (cerebral blood flow-amplitude of low-frequency fluctuation, cerebral blood flow-fractional amplitude of low-frequency fluctuation, cerebral blood flow-regional homogeneity and cerebral blood flow-degree centrality) were compared at the global and regional levels between the presbycusis group and the healthy control group, and the intrinsic association between the altered neurovascular coupling metrics and the neuropsychological scale was further analysed in the presbycusis group. At the global level, neurovascular coupling was significantly lower in the presbycusis group than in the control group and partially related to cognitive level. At the regional level, neurovascular biomarkers were significantly elevated in three brain regions and significantly decreased in one brain region, all of which involved the Papez circuit. Regional neurovascular coupling provides more information than global neurovascular coupling, and neurovascular coupling dysfunction within the Papez circuit has been shown to reveal the causes of poor cognitive and emotional responses in age-related hearing loss patients.

Functional MRI-based biomarkers of insomnia with objective short sleep duration phenotype.

BACKGROUND: Insomnia disorder with objective short sleep duration (ISS) phenotype is a more serious biological subtype than insomnia with objective normal sleep duration (INS) phenotype, and the neuroimaging data is helpful to understand the pathophysiology of the ISS phenotype. This study was to compare the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) between the ISS phenotype and the INS phenotype. METHODS: In this cross-sectional study, 55 patients with insomnia disorder were recruited, and 22 of them were defined as the ISS phenotype by the objective cardiopulmonary coupling (CPC) technique. The blood oxygen level-dependent (BOLD) sequences of all participants were obtained using the 3.0 T magnetic resonance imaging system. We analyzed and compared the ALFF, ReHo, and FC between the ISS phenotype and the INS phenotype. We also conducted Pearson's correlation analysis between significant neuroimaging biomarkers and the CPC parameters. RESULTS: The differences were not significant in ALFF (PFWE-corr＞0.05) or ReHo (PFWE-corr＞0.05) between the ISS phenotype and the INS phenotype. For the FC analysis, the ISS phenotype had a Hub-node of the left inferior occipital gyrus (IOG.L), with significantly decreased connections (p＜0.001) in the bilateral occipital, parietal, and temporal regions. The significant FCs were closely related to sleep parameters. CONCLUSION: The left inferior occipital gyrus (IOG.L), as a Hub-node with decreased functional connections, may be a potential fMRI-based biomarker of the ISS phenotype.

Validation of a Novel Noninvasive Technology to Estimate Blood Oxygen Saturation Using Green Light: Observational Study.

BACKGROUND: Pulse oximeters work within the red-infrared wavelengths. Therefore, these oximeters produce erratic results in dark-skinned subjects and in subjects with cold extremities. Pulse oximetry is routinely performed in patients with fever; however, an elevation in body temperature decreases the affinity of hemoglobin for oxygen, causing a drop in oxygen saturation or oxyhemoglobin concentrations. OBJECTIVE: We aimed to determine whether our new investigational device, the Shani device or SH1 (US Patent 11191460), detects a drop in oxygen saturation or a decrease in oxyhemoglobin concentrations. METHODS: An observational study (phase 1) was performed in two separate groups to validate measurements of hemoglobin and oxygen concentrations, including 39 participants recruited among current university students and staff aged 20-40 years. All volunteers completed baseline readings using the SH1 device and the commercially available Food and Drug Administration-approved pulse oximeter Masimo. SH1 uses two light-emitting diodes in which the emitted wavelengths match with absorption peaks of oxyhemoglobin (hemoglobin combined with oxygen) and deoxyhemoglobin (hemoglobin without oxygen or reduced hemoglobin). Total hemoglobin was calculated as the sum of oxyhemoglobin and deoxyhemoglobin. Subsequently, 16 subjects completed the "heat jacket study" and the others completed the "blood donation study." Masimo was consistently used on the finger for comparison. The melanin level was accounted for using the von Luschan skin color scale (VLS) and a specifically designed algorithm. We here focus on the results of the heat jacket study, in which the subject wore a double-layered heated jacket and pair of trousers including a network of polythene tubules along with an inlet and outlet. Warm water was circulated to increase the body temperature by 0.5-0.8 °C above the baseline body temperature. We expected a slight drop in oxyhemoglobin concentrations in the heating phase at the tissue level. RESULTS: The mean age of the participants was 24.1 (SD 0.8) years. The skin tone varied from 12 to 36 on the VLS, representing a uniform distribution with one-third of the participants having fair skin, brown skin, and dark skin, respectively. Using a specific algorithm and software, the reflection ratio for oxyhemoglobin was displayed on the screen of the device along with direct hemoglobin values. The SH1 device picked up more minor changes in oxyhemoglobin levels after a change in body temperature compared to the pulse oximeter, with a maximum drop in oxyhemoglobin concentration detected of 6.5% and 2.54%, respectively. CONCLUSIONS: Our new investigational device SH1 measures oxygen saturation at the tissue level by reflectance spectroscopy using green wavelengths. This device fared well regardless of skin color. This device can thus eliminate racial disparity in these key biomarker assessments. Moreover, since the light is shone on the wrist, SH1 can be readily miniaturized into a wearable device.

Reduced coupling between global signal and cerebrospinal fluid inflow in patients with depressive disorder: A resting state functional MRI study.

BACKGROUND: Depressed patients often suffer from sleep disturbance, which has been recognized to be responsible for glymphatic dysfunction. The purpose of this study was to investigate the coupling strength of global blood­oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics, which is a biomarker for glymphatic function, in depressed patients and to explore its potential relationship with sleep disturbance by using resting-state functional MRI. METHODS: A total of 138 depressed patients (112 females, age: 34.70 ± 13.11 years) and 84 healthy controls (29 females, age: 36.6 ± 11.75 years) participated in this study. The gBOLD-CSF coupling strength was calculated to evaluate glymphatic function. Sleep disturbance was evaluated using the insomnia items (item 4 for insomnia-early, item 5 for insomnia-middle, and item 6 for insomnia-late) of The 17-item Hamilton Depression Rating Scale for depressed patients, which was correlated with the gBOLD-CSF coupling strength. RESULTS: The depressed patients exhibited weaker gBOLD-CSF coupling relative to healthy controls (p = 0.022), possibly due to impairment of the glymphatic system. Moreover, the gBOLD-CSF coupling strength correlated with insomnia-middle (r = 0.097, p = 0.008) in depressed patients. Limitations This study is a cross-sectional study. CONCLUSION: Our findings shed light on the pathophysiology of depression, indicating that cerebral waste clearance system deficits are correlated with poor sleep quality in depressed patients.

Multi-Echo Complex Quantitative Susceptibility Mapping and Quantitative Blood Oxygen Level-Dependent Magnitude (mcQSM + qBOLD or mcQQ) for Oxygen Extraction Fraction (OEF) Mapping.

Oxygen extraction fraction (OEF), the fraction of oxygen that tissue extracts from blood, is an essential biomarker used to directly assess tissue viability and function in neurologic disorders. In ischemic stroke, for example, increased OEF can indicate the presence of penumbra-tissue with low perfusion yet intact cellular integrity-making it a primary therapeutic target. However, practical OEF mapping methods are not currently available in clinical settings, owing to the impractical data acquisitions in positron emission tomography (PET) and the limitations of existing MRI techniques. Recently, a novel MRI-based OEF mapping technique, termed QQ, was proposed. It shows high potential for clinical use by utilizing a routine sequence and removing the need for impractical multiple gas inhalations. However, QQ relies on the assumptions of Gaussian noise in susceptibility and multi-echo gradient echo (mGRE) magnitude signals for OEF estimation. This assumption is unreliable in low signal-to-noise ratio (SNR) regions like disease-related lesions, risking inaccurate OEF estimation and potentially impacting clinical decisions. Addressing this, our study presents a novel multi-echo complex QQ (mcQQ) that models realistic Gaussian noise in mGRE complex signals. We implemented mcQQ using a deep learning framework (mcQQ-NET) and compared it with the existing QQ-NET in simulations, ischemic stroke patients, and healthy subjects, using identical training and testing datasets and schemes. In simulations, mcQQ-NET provided more accurate OEF than QQ-NET. In the subacute stroke patients, mcQQ-NET showed a lower average OEF ratio in lesions relative to unaffected contralateral normal tissue than QQ-NET. In the healthy subjects, mcQQ-NET provided uniform OEF maps, similar to QQ-NET, but without unrealistically high OEF outliers in areas of low SNR, such as SNR ≤ 15 (dB). Therefore, mcQQ-NET improves OEF accuracy by more accurately reflecting realistic Gaussian noise in complex mGRE signals. Its enhanced sensitivity to OEF abnormalities, based on more realistic biophysics modeling, suggests that mcQQ-NET has potential for investigating tissue variability in neurologic disorders.

Evaluation of Kidney Injury Using Arterial Spin Labeling and Blood Oxygen Level-Dependent MRI: An Experimental Study in Rats With Carbon Tetrachloride-Induced Liver Cirrhosis.

BACKGROUND: Serum creatinine (Scr) may be not suited to timely and accurately reflect kidney injury related to chronic liver disease. Currently, the ability of arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) sequences to evaluate renal blood flow (RBF) and blood oxygen in chronic liver disease remains to be verified. PURPOSE: To investigate the value of ASL and BOLD imaging in evaluating hemodynamics and oxygenation changes during kidney injury in an animal model of chronic liver disease. STUDY TYPE: Prospective. ANIMAL MODEL: Chronic liver disease model was established by subcutaneous injection of carbon tetrachloride. Forty-three male Sprague-Dawley rats (8 weeks) were divided into a pathological group (0, 2, 4, 6, 8, 12 weeks, each group: N = 6) and a continuous-scanning group (N = 7). FIELD STRENGTH/SEQUENCE: 3-T, ASL, BOLD, and T2W. ASSESSMENT: Regions of interest in the cortex (CO), outer stripe of the outer medulla (OSOM), and inner stripe of the outer medulla (ISOM) are manually delineated. The RBF and T2* values at each time point (0, 2, 4, 6, 8, 12 weeks) are measured and compared. Hematoxylin-eosin score (HE Score, damage area scoring method), alpha-smooth muscle actin (α-SMA), hypoxia-inducible factor-1alpha (HIF-1α), peritubular capillar (PTC) density, Scr, and neutrophil gelatinase-associated lipocalin were harvested. STATISTICAL TESTS: Analysis of variance, Spearman correlation analysis, Kruskal-Wallis tests, and receiver operating characteristic analysis with the area under the curve (AUC). A P-value <0.05 was considered statistically significant. RESULTS: Renal RBF and T2* values of CO, OSOM, and ISOM were significantly different from baseline. Both RBF and T2* were significantly correlated with HE Score, α-SMA, HIF-1α, and PTC density (|r| = 0.406-0.853). RBF demonstrated superior diagnostic capability in identifying severe kidney injury in this model of chronic liver disease (AUC = 0.964). DATA CONCLUSION: Imaging by ASL and BOLD may detect renal hemodynamics and oxygenation changes related to chronic liver disease early. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Exploring timescale-specific functional brain networks and their associations with aging and cognitive performance in a healthy cohort without dementia.

INTRODUCTION: Functional brain networks (FBNs) coordinate brain functions and are studied in fMRI using blood-oxygen-level-dependent (BOLD) signal correlations. Previous research links FBN changes to aging and cognitive decline, but various physiological factors influnce BOLD signals. Few studies have investigated the intrinsic components of the BOLD signal in different timescales using signal decomposition. This study aimed to explore differences between intrinsic FBNs and traditional BOLD-FBN, examining their associations with age and cognitive performance in a healthy cohort without dementia. MATERIALS AND METHODS: A total of 396 healthy participants without dementia (men = 157; women = 239; age range = 20-85 years) were enrolled in this study. The BOLD signal was decomposed into several intrinsic signals with different timescales using ensemble empirical mode decomposition, and FBNs were constructed based on both the BOLD and intrinsic signals. Subsequently, network features-global efficiency and local efficiency values-were estimated to determine their relationship with age and cognitive performance. RESULTS: The findings revealed that the global efficiency of traditional BOLD-FBN correlated significantly with age, with specific intrinsic FBNs contributing to these correlations. Moreover, local efficiency analysis demonstrated that intrinsic FBNs were more meaningful than traditional BOLD-FBN in identifying brain regions related to age and cognitive performance. CONCLUSIONS: These results underscore the importance of exploring timescales of BOLD signals when constructing FBN and highlight the relevance of specific intrinsic FBNs to aging and cognitive performance. Consequently, this decomposition-based FBN-building approach may offer valuable insights for future fMRI studies.

Modulation of temporal and occipital cortex by acupuncture in non-menstrual MWoA patients: a rest BOLD fMRI study.

OBJECTIVE: To investigate the changes in amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) values before and after acupuncture in young women with non-menstrual migraine without aura (MWoA) through rest blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI). METHODS: Patients with non-menstrual MWoA (Group 1, n = 50) and healthy controls (Group 2, n = 50) were recruited. fMRI was performed in Group 1 at 2 time points: before acupuncture (time point 1, TP1); and after the end of all acupuncture sessions (time point 2, TP2), and performed in Group 2 as a one-time scan. Patients in Group 1 were assessed with the Migraine Disability Assessment Questionnaire (MIDAS) and the Short-Form McGill Pain Questionnaire (SF-MPQ) at TP1 and TP2 after fMRI was performed. The ALFF and DC values were compared within Group 1 at two time points and between Group 1 and Group2. The correlation between ALFF and DC values with the statistical differences and the clinical scales scores were analyzed. RESULTS: Brain activities increased in the left fusiform gyrus and right angular gyrus, left middle occipital gyrus, and bilateral prefrontal cortex and decreased in left inferior parietal lobule in Group 1, which had different ALFF values compared with Group 2 at TP1. The bilateral fusiform gyrus, bilateral inferior temporal gyrus and right middle temporal gyrus increased and right angular gyrus, right superior marginal gyrus, right inferior parietal lobule, right middle occipital gyrus, right superior frontal gyrus, right middle frontal gyrus, right anterior central gyrus, and right supplementary motor area decreased in activity in Group 1 had different DC values compared with Group 2 at TP1. ALFF and DC values of right inferior temporal gyrus, right fusiform gyrus and right middle temporal gyrus were decreased in Group1 at TP1 compared with TP2. ALFF values in the left middle occipital area were positively correlated with the pain degree at TP1 in Group1 (correlation coefficient r, r = 0.827, r = 0.343; P < 0.01, P = 0.015). The DC values of the right inferior temporal area were positively correlated with the pain degree at TP1 in Group 1 (r = 0.371; P = 0.008). CONCLUSION: Spontaneous brain activity and network changes in young women with non-menstrual MwoA were altered by acupuncture. The right temporal area may be an important target for acupuncture modulated brain function in young women with non-menstrual MwoA.

The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity.

Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.

The value of functional magnetic resonance imaging in evaluating renal allograft function.

BACKGROUND: To explore the value of arterial spin labeled (ASL) and blood oxygen level dependent (BOLD) imaging in evaluating allogeneic kidney function after renal transplantation. METHODS: One hundred and thirty-five renal transplant patients were included. Demographic and imaging data were collected. Transplanted renal function, pathology, ASL and BOLD parameters were obtained. The patients were divided into normal, mild and severe injury group. The correlation between BOLD/ASL parameters and clinical data were evaluated. The prediction models were based on ASL and BOLD parameters using multivariate logistic analysis. Cox proportional hazards regression model was used to analyze the effects of gender, age, ASL and BOLD on the survival of renal transplant patients. RESULTS: ASL and BOLD parameters were independently associated with renal function injury and renal allograft positive pathology. The AUC of prediction model for renal allograft function based on ASL and BOLD parameters was 0.85, while the AUC based on BOLD parameters was 0.70. Renal transplantation time showed a positive correlation with age, BOLD parameters and SCr，while a negative correlation with ASL parameters and eGFR. ASL parameter was positively correlated with eGFR and negatively correlated with Scr. BOLD parameter was negatively correlated with eGFR, ASL and positively correlated with Scr. Cox proportional hazards regression model showed that the increase of age could reduce the risk of renal function injury and positive pathology. CONCLUSIONS: ASL and BOLD were associated with renal function injury and renal allograft positive pathology. ASL and BOLD had some value in predicting renal allograft function.

Phytomedicine Fructus Aurantii-derived two absorbed compounds unlock antidepressant and prokinetic multi-functions via modulating 5-HT3/GHSR.

ETHNOPHARMACOLOGICAL RELEVANCE: Fructus Aurantii (FA), a well-known phytomedicine, has been employed to evoke antidepressant and prokinetic multi-functions. Therein, systematically identifying bioactive components and the referred mechanism is essential for FA. AIM OF THE STUDY: This study was planned to answer "2 W" (What and Why), such as which components and pathways contribute to FA's multi-functions. We aimed to identify bioactive compounds as the key for opening the lock of FA's multi-functions, and the molecule mechanisms are their naturally matched lock cylinder. MATERIALS AND METHODS: The phytochemical content of FA extract was determined, and the compounds were identified in rats pretreated with FA using liquid chromatography with mass spectrometry (LC-MS). The contribution strategy was used to assess bioactive compounds' efficacy (doses = their content in FA) in model rats with the mechanism. The changes in functional brain regions were determined via 7.0 T functional magnetic resonance imaging-blood oxygen level-dependent (fMRI-BOLD). RESULT: Eight phytochemicals' content was detected, and merely six components were identified in rats in vivo. Meranzin hydrate + hesperidin (MH), as the primary contributor of FA, exerted antidepressant and prokinetic effects (improvement of indexes for immobility time, gastric emptying, intestinal transit, CRH, ghrelin, ACTH, DA, NA, 5-HT, CORT, and 5-HT3) by regulating 5-HT3/Growth hormone secretagogue receptor (GHSR) pathway. These results were validated by 5-HT2A, 5-HT3, and GHSR receptor antagonists combined with molecule docking. MH restored the excessive BOLD activation of the left accumbens nucleus, left corpus callosum and hypothalamus preoptic region. CONCLUSION: Absorbed MH accounts for FA's anti-depressant and prokinetic efficacy in acutely-stressed rats, primarily via 5-HT3/GHSR shared regulation.

Changes in the BOLD signal of S1 and BA3 per finger/phalanx as a response to high-frequency vibratory stimulation.

PURPOSE AND METHOD: The purpose of this study was to determine the changes in the Blood Oxygen Level Dependent signal of Primary somatosensory area (S1) and Brodmann area 3 (BA3) per finger and phalanx in comparison to the activation voxel when 250 Hz vibratory stimulation with high sensitivity for the Pacinian corpuscle was given to the four fingers and three phalanges. RESULTS: The result of analyzing the activation voxel showed a significant difference for S1 per finger and phalanx, but for BA3, no significant difference was observed despite a similar trend to S1. In contrast, the activation intensity (BOLD) displayed a significant difference for S1 per finger and phalanx and for BA3, where the activation voxel had no significant variation. In addition, while the result of S1 did not indicate whether the index or the little fingers had the highest sensitivity based on the BOLD signal per finger, the result of BA3 marked the strongest BOLD signal for the little finger as a response to 250 Hz vibratory stimulation. The activation intensity per phalanx was the highest for the intermediate phalanx for S1 and BA3, which was in line with a previous study comparing the activation voxel. CONCLUSIONS: The method based on the intensity of the nerve activation is presumed to have high sensitivity as the signal intensity is monitored within a specific, defined area. Thus, for the extraction of brain activation patterns of micro-domains, such as BA3, monitoring the BOLD signal that reflects the nerve activation intensity more sensitively is likely to be advantageous.

Functional-structural decoupling in visual network is associated with cognitive decline in patients with type 2 diabetes mellitus: evidence from a multimodal MRI analysis.

Type 2 diabetes mellitus (T2DM) and cognitive dysfunction are highly prevalent disorders worldwide. Although visual network (VN) alteration and functional-structural coupling are potential warning factors for mild cognitive impairment (MCI) in T2DM patients, the relationship between the three in T2DM without MCI is unclear. Thirty T2DM patients without MCI and twenty-nine healthy controls (HC) were prospectively enrolled. Visual components (VC) were estimated by independent component analysis (ICA). Degree centrality (DC), amplitude of low frequency fluctuation (ALFF) and fractional anisotropy (FA) were established to reflect functional and structural characteristics in these VCs respectively. Functional-structural coupling coefficients were further evaluated using combined FA and DC or ALFF. Partial correlations were performed among neuroimaging indicators and neuropsychological scores and clinical variables. Three VCs were selected using group ICA. Deteriorated DC, ALFF and DC-FA coefficients in the VC1 were observed in the T2DM group compared with the HC group, while FA and ALFF-FA coefficients in these three VCs showed no significant differences. In the T2DM group, DC in the VC1 positively correlated with 2 dimensions in the California Verbal Learning Test, including Trial 4 and Total trial 1-5. The impaired DC-FA coefficients in the VC1 markedly affected the Total perseverative responses % of the Wisconsin Card Sorting Test. These findings indicate that DC and DC-FA coefficients in VN may be potential imaging biomarkers revealing early cognitive deficits in T2DM.

Remote photoplethysmography-based human vital sign prediction using cyclical algorithm.

This article aims to predict vital signs like heart rate (HR), respiration rate, and arterial oxygen saturation using ambient light video, eliminating chronic distortions through improved frame quality with BER estimation. The study employs the cascade residual CNN-FPNR technique for preprocessing and SNR enhancement using energy variance maximization. The image cascade network (ICNet) facilitates segmentation, achieving strong segmentation in low-light ambient videos. Remote photoplethysmography (iPPG) enables noncontact vital sign monitoring, predicting HR and respiratory rate (RR). An innovative noninvasive temperature and cyclical algorithm, incorporating principal component analysis and fast Fourier transform, evaluate patient HR and RR. To address challenges related to involuntary movements, a dynamic time-warping-based optimization method is used for precise region selection. The study introduces an intensity variance-based threshold analysis for arterial oxygen saturation level determination. Ultimately, the support vector machine (SVM) classification technique evaluates the ground truth, showcasing the system's promising potential for remote and accurate vital sign assessment.

On a framework of data assimilation for hyperparameter estimation of spiking neuronal networks.

When handling real-world data modeled by a complex network dynamical system, the number of the parameters is often much more than the size of the data. Therefore, in many cases, it is impossible to estimate these parameters and the exact value of each parameter is frequently less interesting than the distribution of the parameters. In this paper, we aim to estimate the distribution of the parameters in the mesoscopic neuronal network model from the macroscopic experimental data, for example, the BOLD (blood oxygen level dependent) signal. Herein, we assume that the parameters of the neurons and synapses are inhomogeneous but independently and identically distributed from certain distributions with unknown hyperparameters. Thus, we estimate these hyperparameters of the distributions of the parameters, instead of estimating the parameters themselves. We formulate this problem under the framework of data assimilation and hierarchical Bayesian method and present an efficient method named Hierarchical Data Assimilation (HDA) to conduct the statistical inference on the neuronal network model with the BOLD signal data simulated by the hemodynamic model. We consider the Leaky Integral-Fire (LIF) neuronal networks with four synapses and show that the proposed algorithm can estimate the BOLD signals and the hyperparameters with high preciseness. In addition, we discuss the influence on the performance of the algorithm configuration and the LIF network model setup.

Multifaceted neural and vascular pathologies after pediatric mild traumatic brain injury.

Dynamic changes in neurodevelopment and cognitive functioning occur during adolescence, including a switch from reactive to more proactive forms of cognitive control, including response inhibition. Pediatric mild traumatic brain injury (pmTBI) affects these cognitions immediately post-injury, but the role of vascular versus neural injury in cognitive dysfunction remains debated. This study consecutively recruited 214 sub-acute pmTBI (8-18 years) and age/sex-matched healthy controls (HC; N = 186), with high retention rates (>80%) at four months post-injury. Multimodal imaging (functional MRI during response inhibition, cerebral blood flow and cerebrovascular reactivity) assessed for pathologies within the neurovascular unit. Patients exhibited increased errors of commission and hypoactivation of motor circuitry during processing of probes. Evidence of increased/delayed cerebrovascular reactivity within motor circuitry during hypercapnia was present along with normal perfusion. Neither age-at-injury nor post-concussive symptom load were strongly associated with imaging abnormalities. Collectively, mild cognitive impairments and clinical symptoms may continue up to four months post-injury. Prolonged dysfunction within the neurovascular unit was observed during proactive response inhibition, with preliminary evidence that neural and pure vascular trauma are statistically independent. These findings suggest pmTBI is characterized by multifaceted pathologies during the sub-acute injury stage that persist several months post-injury.

Predicting dissolved oxygen level using Young's double-slit experiment optimizer-based weighting model.

Accurate prediction of the dissolved oxygen level (DOL) is important for enhancing environmental conditions and facilitating water resource management. However, the irregularity and volatility inherent in DOL pose significant challenges to achieving precise forecasts. A single model usually suffers from low prediction accuracy, narrow application range, and difficult data acquisition. This study proposes a new weighted model that avoids these problems, which could increase the prediction accuracy of the DOL. The weighting constructs of the proposed model (PWM) included eight neural networks and one statistical method and utilized Young's double-slit experimental optimizer as an intelligent weighting tool. To evaluate the effectiveness of PWM, simulations were conducted using real-world data acquired from the Tualatin River Basin in Oregon, United States. Empirical findings unequivocally demonstrated that PWM outperforms both the statistical model and the individual machine learning models, and has the lowest mean absolute percentage error among all the weighted models. Based on two real datasets, the PWM can averagely obtain the mean absolute percentage errors of 1.0216%, 1.4630%, and 1.7087% for one-, two-, and three-step predictions, respectively. This study shows that the PWM can effectively integrate the distinctive merits of deep learning methods, neural networks, and statistical models, thereby increasing forecasting accuracy and providing indispensable technical support for the sustainable development of regional water environments.

Blood Oxygen Level-Dependent MR Imaging of Lower Extremities in Peripheral Artery Disease and Its Correlation With Walking Performance.

BACKGROUND: A noninvasive and reliable approach to quantitatively measure muscle perfusion of lower extremity is needed to aid the diagnosis and treatment of peripheral artery disease (PAD). PURPOSE: To verify the reproductivity of using blood oxygen level-dependent (BOLD) imaging to evaluate perfusion in lower extremities, and explore its correlation with walking performance in patients with PAD. STUDY TYPE: Prospective observational study. SUBJECTS: Seventeen patients with lower extremity PAD (mean age: 67 ± 6 years, 15 males) and eight older adults (controls). FIELD STRENGTH/SEQUENCE: Dynamic multi-echo gradient echo T2* weighted imaging at 3T. ASSESSMENT: Perfusion was analyzed in regions of interest according to muscle groups. Perfusion parameters were measured, such as minimum ischemia value (MIV), time to peak (TTP), and gradient during reactive hyperemia (Grad) by two independent users. Walking performance experiments including short physical performance battery (SPPB) and 6-minute walk were tested in patients. STATISTICAL TESTS: BOLD parameters were compared using Mann-Whitney U test and Kruskal-Wallis test. Relations between parameters and walking performance were assessed by Mann-Whitney U test and Spearman's correlation coefficient. RESULTS: Good to perfect agreement was demonstrated for all perfusion parameters of interuser reproducibility, and the interscan reproducibility of MIV, TTP, and Grad was good. The TTP of the patients was longer than that of the controls (87.85 ± 38.85 s vs. 36.54 ± 7.27 s), while the Grad of patients was smaller (0.16 ± 0.12 msec/s vs. 0.24 ± 0.11 msec/s). Among PAD patients, the MIV was significantly lower in the low SPPB subgroup (score 6-8) than in the high SPPB group (score 9-12), and the TTP was negatively correlated with 6-minute walk distance (ρ = -0.549). DATA CONCLUSION: BOLD imaging method had overall good reproducibility for the perfusion assessment of calf muscles. The perfusion parameters were different between PAD patients and controls, and were correlated with lower extremity function. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Hybrid deep learning model based smart IOT based monitoring system for Covid-19.

Recently, COVID-19 becomes a hot topic and explicitly made people follow social distancing and quarantine practices all over the world. Meanwhile, it is arduous to visit medical professionals intermittently by the patients for fear of spreading the disease. This IoT-based healthcare monitoring system is utilized by many professionals, can be accessed remotely, and provides treatment accordingly. In context with this, we designed an IoT-based healthcare monitoring system that sophisticatedly measures and monitors the parameters of patients such as oxygen level, blood pressure, temperature, and heart rate. This system can be widely used in rural areas that are linked to the nearest city hospitals to monitor the patients. The collected data from the monitoring system are stored in the cloud-based data storage and for the classification our approach proposes an innovative Recurrent Convolutional Neural Network (RCNN) based Puzzle optimization algorithm (PO). Based on the outcome further treatments are made with the assistance of physicians. Experimental analyses are made and analyzed the performance with state-of-art works. The availability of more data storage capacity in the cloud can make physicians access the previous data effortlessly.