Brain Sciences最新文献

Background: Brain tumors present a significant clinical problem due to high mortality and strong heterogeneity in size, shape, location, and tissue characteristics, complicating reliable MRI analysis. Existing automated methods are limited by non-selective skip connections that propagate noise, axis-separable attention modules that poorly integrate channel and spatial cues, shallow encoders with insufficiently discriminative features, and isolated optimization of segmentation or classification tasks. Methods: We propose a model using an EfficientNetV2S backbone with a Hierarchical Hybrid Attention (HHA) mechanism. The HHA couples a global-context pathway with a local-spatial pathway, employing a correlation-driven, per-pixel fusion gate to explicitly model interactions between them. Multi-scale dilated blocks are incorporated to enlarge the effective receptive field. The model is applied to a multiclass brain tumor MRI dataset, leveraging shared representation learning for joint segmentation and classification. Results: The design attains a Dice score of 92.25% and a Jaccard index of 86% for segmentation. For classification, it achieves an accuracy of 99.53%, with precision, recall, and F1 scores all close to 99%. These results indicate sharper tumor boundaries, stronger noise suppression in segmentation, and more robust discrimination in classification. Conclusions: The proposed framework effectively overcomes key limitations in brain tumor MRI analysis. The integrated HHA mechanism and shared representation learning yield superior segmentation quality with enhanced boundary delineation and noise suppression, alongside highly accurate tumor classification, demonstrating strong clinical utility.

Background/Objectives: Heart failure with reduced ejection fraction (HFrEF) is associated with significant neuropsychological burden, including cognitive impairment and mood disturbances. While sacubitril/valsartan has demonstrated cardiovascular benefits, its effects on cognitive and emotional functioning remain underexplored, particularly in Middle Eastern populations. We aimed to evaluate the impact of sacubitril/valsartan on intellectual capacity, cognitive function and mood in patients with HFrEF using an idiographic study design. Methods: This study was conducted in adult patients with HFrEF selected to take sacubitril/valsartan to improve their clinical status. Participants were assessed at baseline and 3 months after treatment initiation using Al Khoudh Cognitive Test, PHQ-9 and Raven's Progressive Colored Matrices. Results: Following three months of treatment, participants showed a statistically significant improvement in left ventricular ejection fraction (LVEF) (p = 0.043), depression severity (p = 0.025) and a non-significant trend toward improvement in abstract reasoning scores (p = 0.051). On the other hand, participants did not demonstrate significant improvements in the cognitive subdomains assessed by the Al Khoudh Test. Among these subdomains, the largest improvement was observed with verbal fluency (p = 0.057). Improvements in LVEF were not significantly associated with the changes in mood (p = 0.93), cognitive function (p = 0.34) or verbal fluency (p = 0.46). Conclusions: This study provides preliminary, hypothesis-generating evidence of potential short-term improvement in mood and reasoning scores in HFrEF patients treated with sacubitril/valsartan. Notably, these changes were not attributed to the observed improvements in cardiac function. These findings underscore the need for further investigation into the neurocognitive benefits of sacubitril/valsartan in larger and more diverse populations.

Objectives: Women with Premenstrual Syndrome (PMS) tend to exhibit an excessive attention bias toward negative stimuli during the luteal phase. This study intends to investigate the effect of regular yoga on attention bias of women with PMS during the luteal phase and explore the mechanisms underlying such changes. Methods: Sixty-four women with PMS were recruited, coded and randomly assigned to either a 12-week yoga group (n = 32) or a control group (n = 32). The dot-probe task was used to assess attention bias at baseline and 12 weeks later. Data analysis was performed using SPSS 27.0 software, with analytical methods including descriptive statistics, repeated-measures analysis of variance (RM-ANOVA), simple effect analysis, cluster-based permutation test and Pearson correlation analysis. The Holm-Bonferroni method was used to correct for multiple comparison errors. Results: RM-ANOVA revealed significant time × group interaction effects for attention orientation, attention disengagement, P1 component, and P3 component. Simple effect analysis indicated that, compared with the control group, the yoga group exhibited significant modulations in attention orientation (t = -7.33, p < 0.001), P1 (t = 8.94, p < 0.001), attention disengagement (t = 6.89, p < 0.001), and P3 (t = 4.42, p = 0.002) after 12 weeks of intervention. Cluster-based permutation tests demonstrated that the yoga group showed significant reductions in P1 and P3 amplitudes after 12 weeks. Pearson correlation analysis indicated that attention orientation was significantly negatively correlated with P1 amplitude, while attention disengagement was significantly positively correlated with P3 amplitude. Conclusion: Regular yoga can regulate the behavioral indicators and electroencephalographic (EEG) indicators related to attention bias and exerts a positive effect on modulating attention bias toward negative stimuli in women with PMS during the luteal phase.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Recent findings suggest that long-term and heavy alcohol consumption can aggravate several pathological processes associated with AD, whereas the impact of light or moderate consumption remains uncertain. Excessive alcohol exposure impairs the structure and function of key brain regions involved in cognition, particularly the hippocampus, prefrontal cortex, amygdala, cerebellum, Basolateral amygdala (BLA), and hypothalamus. Several studies indicate that chronic alcohol consumption affects the brain by multiple mechanisms like increased oxidative stress, microglial activation, neuroinflammation, microtubule instability, tau hyperphosphorylation, and modified amyloid-β turnover. Disruption of cholinergic transmission further contributes to memory deficits and neuronal susceptibility. These alcohol-related alterations closely resemble core features of AD pathology and may accelerate disease progression. Although some epidemiological studies report the potential benefits of low alcohol intake, their interpretation is limited by inconsistent definitions of drinking patterns and the influence of confounding variables. Overall, current evidence supports a dose-dependent relationship in which alcoholism increases vulnerability to AD-related neurodegeneration. Reducing harmful alcohol use may therefore represent a practical approach to lowering long-term dementia risk. This review summarizes the current mechanisms of alcohol induced neuronal damage across different brain regions. Prolonged alcohol consumption accelerates cerebral aging by enhancing oxidative stress, neuroinflammation, disrupting tau protein degradations, and other neuronal damages that intersect with the pathogenesis of AD.

Background: Diffusion-prepared pseudo-continuous arterial spin labelling (DP-pCASL) can quantify the cerebral blood flow (CBF) and the water exchange rate (kw) across the blood-brain barrier (BBB). Little is known about the BBB water exchange in major depressive disorder (MDD). Objective: We aimed to explore the associations between kw, CBF, peripheral inflammation, and MDD. Methods: Using DP-pCASL, we measured the global and selected regional kw and CBF together with blood plasma levels of lipopolysaccharide (LPS) and inflammatory cytokines in 85 patients with MDD and 51 controls. Results: The global CBF was significantly lower in MDD patients compared with controls (means of 51 and 57 mL/100 g/min, respectively; p = 0.006), with similar reductions found in the dorsolateral and ventromedial prefrontal, anterior, and posterior cingulate regions, while no differences were found in the amygdala and the isthmic cingulate. There were no differences in the kw between groups globally (means of 128 min^-1; p = 0.958) and in the studied regions. Among MDD patients, the kw was weakly correlated with the MADRS scores (r = 0.231, p = 0.034). There were no associations between kw, CBF, and inflammatory markers (LPS, IL-6, IL-10, TNF-α, IFN-γ). Logistic regression showed that a combination of the regional CBF < 59.22 mL/100 g/min together with LPS > 143.58 pg/mL and/or IL-10 > 0 pg/mL distinguished MDD patients from controls with a moderate accuracy of 83.1% (sensitivity = 94.1%, specificity = 64.7%, AUC = 0.876). Conclusions: DP-pCASL imaging confirmed previous findings of reduced CBF in MDD, which together with LPS and IL-10 concentrations were independent significant predictors of MDD. However, no changes in the BBB water exchange were found, suggesting that it may not be as significant as CBF in MDD pathophysiology.

Parkinson's disease (PD) ranks as the second most frequent neurodegenerative disorder [...].

Depression and anxiety disorders are associated with deficits in several cognitive domains. This meta-analytic review assessed the effects of emotional working memory training (eWMT) on depression and anxiety and their related emotional and cognitive domains. Eligible studies were assessed for changes in depression, anxiety, emotion and cognition after eWMT. Methodological quality was assessed using Cochrane Collaboration's guidelines, and random-effects models aggregated the results of individual studies. Of 1314 studies identified, 16 were included (883 participants; mean age range, 14.35-68.79 years; 70.44% female). Nine studies were high quality, seven were moderate quality, and none were low quality. There was relatively high heterogeneity across studies and study populations. The eWMT significantly reduced depression (standardized mean difference [SMD], -2.04; 95% confidence interval [CI], -3.68 to -0.39; p = 0.02) and anxiety (SMD, -0.44; 95% CI = -0.23 to -0.17; p < 0.001) and significantly enhanced reappraisal (SMD, 0.38; 95% CI, 0.11 to 0.66; p = 0.03) and working memory capacity (SMD, 0.31; 95% CI, 0.10 to 0.53; p < 0.001), with no significant effect on rumination. Training frequency, training environment, and type of control group differentially affected working memory capacity. Our results demonstrated that eWMT alleviated depression and anxiety, but not rumination, and improved the related factors of reappraisal and working memory. Given the limited number of studies and substantial heterogeneity in the data, further research is needed to support these results.

Background/Objectives: Several imaging scores have been developed for subarachnoid hemorrhage (SAH), but their prognostic performance for long-term functional outcome and post-hospital complications remains insufficiently characterized. We evaluated whether five admission imaging scores (modified Fisher, Claassen, Hijdra, Graeb, IVH) independently predict 12-month functional outcome and major secondary endpoints. Methods: We performed a retrospective cohort study of 479 consecutive patients with atraumatic SAH recorded in a prospectively maintained institutional registry. Admission CT/MRI was scored by two board-certified neuroradiologists blinded to clinical outcomes. The primary endpoint was unfavorable functional outcome at 12 months (modified Rankin scale [mRS] 4-6). Secondary endpoints included 12-month mortality, delayed cerebral ischemia (DCI), post-hemorrhagic epilepsy, shunt-dependent hydrocephalus, return to work, and patient-reported health. Receiver operating characteristic (ROC) analyses and multivariable logistic regression adjusted for established predictors were conducted. Results: All imaging scores were significantly associated with the primary endpoint and demonstrated adequate discrimination (area under the curve [AUC] ~0.70-0.74), with the Graeb and IVH scores performing highest for long-term functional outcome, mortality, and shunt dependence. Associations with DCI and epilepsy were modest. In multivariable analyses, all imaging scores remained independently associated with mRS 4-6. Subgroup analyses showed stronger prognostic performance in good-grade SAH, aneurysmal SAH, and cases with concomitant intraventricular hemorrhage. Conclusions: Admission imaging burden independently predicts 12-month functional outcome, mortality, and shunt dependence after SAH. Incorporating IVH-oriented measures alongside established clinical grading may improve individualized risk stratification, particularly in good-grade and aneurysmal SAH.

Background: Previous research has shown that video gaming experience is associated with changes in cognitive and perceptual functions as well as neural structure and function. However, how the different types of video games differentially influence cognitive function and neuroplasticity remains unclear. Methods: In this 30-week longitudinal study, participants were randomly assigned to an action video game group or a strategy card game group. Behavioral assessments and resting-state electroencephalography (EEG) recordings were administered at six time points to evaluate changes in attention, working memory, executive function, and their neural correlates. Results: Both groups showed significant improvements in multiple cognitive tasks, but the underlying neural mechanisms differed. The action video game group showed greater increases in low-frequency EEG relative power (delta and theta bands) and more pronounced decreases in alpha-band functional connectivity at the 10-week follow-up after the end of training. Conclusions: These findings suggest that different types of video games improve cognition through distinct neuroplasticity pathways, with action games effective in optimizing neural efficiency and producing sustained effects. This study provides new insights into the cognitive and neural mechanisms of game-based enhancements and offers implications for the design of targeted digital cognitive interventions.