Brain Sciences最新文献

Background/Objectives: Tripping is a major cause of falls and necessitates accessible training. This study aimed to fundamentally evaluate the biomechanical fidelity of a simplified simulated obstacle-crossing paradigm using visual height cues. Methods: Two experiments that included healthy young adults evaluated toe clearance (TC) responsiveness during simulated crossing to four visual cue heights (Experiment 1: n = 16) and compared it with actual crossing (4-16% leg length) to assess biomechanical fidelity (Experiment 2: n = 18). Linear mixed models were used to analyze the effects of obstacle height, task condition, and walking course on vertical TC metrics, including minimum and maximum clearance and quartile coefficient of variation (QCV) for both the lead and trail limbs. Results: In Experiment 1, TC parameters scaled systematically with cue height (p < 0.001), confirming that visual cues elicited adaptive gait adjustments. In Experiment 2, although the maximum TC scaled similarly across conditions, the minimum TC was systematically reduced in the simulated condition compared to actual obstacle crossing (p < 0.001). Furthermore, the simulated condition exhibited increased QCV (p < 0.001), particularly for the trail limb at the highest obstacle height. Conclusions: Motor intention and execution precision were dissociated in the simulated obstacle crossing. Without physical risk, the central nervous system appeared to prioritize effort economy over the precise fine-tuning of safety margins. These results suggest that task repetition in risk-free simulations alone may be insufficient for acquiring safe obstacle-crossing strategies and highlight the importance of task-relevant feedback for ensuring biomechanical fidelity in fall-prevention research.

Background: Sense of Time (SoT) refers to a range of cognitive abilities involved in the time processing (TP) and management (TM) of temporal durations. Impairments in these abilities can impact various domains of daily life, including academic, social, and recreational activities. Recent evidence suggests that children with neurodevelopmental disorders (NDDs), particularly ADHD and Developmental Dyscalculia (DD), often exhibit deficits in time-related cognitive functions. Adopting a transdiagnostic approach, the present study investigates the relationships among SoT skills, inattention and hyperactivity, and mathematical difficulties, considering both categorical and dimensional perspectives. Methods: A total of 811 children completed SoT assessments (computerized tasks and self- and proxy-report questionnaires), mathematical tests, and questionnaires measuring attention and hyperactivity traits (self and proxy report). Results: Correlational analyses revealed significant associations between SoT and attention/hyperactivity, as well as between SoT and mathematical abilities. Group differences in TP and TM variables were examined using both categorical (diagnostic groups) and dimensionally derived group approaches. The results indicated more marked contrasts using the dimensional approach. Specifically, attentional and executive control difficulties appeared to have greater associations with TP and TM skills than mathematical difficulties alone. No evidence for attentional X mathematical difficulties interaction emerged. Conclusions: The SoT abilities were impaired in children with both ADHD and DD. A transdiagnostic dimensional approach allows for a more nuanced understanding of SoT profiles across different types of atypical development within the NDDs spectrum. Practical and clinical implications are discussed.

Background/Objectives: Deficits in auditory change detection are well-known in psychiatric disorders such as schizophrenia. An abrupt change in sound feature during periodic sounds elicits both evoked potentials and a transient change in neural oscillations. Both of these cerebral responses are thought to reflect the automatic change detection. However, the similarities and dissimilarities between these cerebral responses are unclear. To clarify them, we compared the temporal dynamics of evoked potentials and low gamma oscillations under a paired-pulse paradigm. Methods: Healthy adults (n = 21) participated. The stimulus was a 2 s sound consisting of a train of 25 ms pure tones. The sound pressure was increased by 15 dB twice within a 600 ms interval. Electroencephalographic signals were recorded from Fz and Cz electrodes referenced to linked mastoids. The peak (N100)-to-peak (P200) amplitude and the inter-trial phase coherence (ITPC) of low gamma oscillations were analyzed. Results: Auditory steady-state responses were evoked around 40 Hz. An abrupt change in sound pressure transiently decreased the ITPC of the oscillations at 40 Hz, whereas it increased the ITPC at the remaining frequencies. Unlike the change-related potentials, the degree of ITPC responses did not differ between the two changes. Conclusions: The synchrony of low gamma oscillations transiently responded to an abrupt increase in sound pressure but did not show paired-pulse suppression. This novel neurophysiological approach enables a focus on the neural change detection from multiple angles, which could be useful for investigations of psychiatric disorders.

Background/Objectives: This study explored the heterogeneous distribution pattern of translocator protein 18kDa (TSPO)-PET/MRI using radioligand [¹⁸F] DPA-714 in temporal lobe epilepsy patients and identified clinical factors influencing imaging outcomes. Methods: The TSPO imaging in individual patient was evaluated with both visual reading and quantitative assessment using an asymmetry index based on cerebellum-normalized standardized uptake values. The association between clinical factors and TSPO imaging outcomes was assessed. Pathological evaluation was conducted in three patients. Results: Twenty-nine TLE patients and ten healthy controls were enrolled. Visual evaluation revealed increased [¹⁸F] DPA-714 uptake in twenty patients as compared to controls, predominantly in a unilateral regional brain, while the remaining nine patients showed visually undetectable uptake of [¹⁸F] DPA-714. Consistently, quantitative analysis revealed that 69% (20/29) patients exhibited at least one brain area with significant asymmetry index, notably in the temporal lobe (85%, 17/20). A high asymmetry index could also be observed in the parietal (13.8%, 4/29) and occipital lobe (17.2%, 5/29). Significant associations were identified between the asymmetry index and seizure frequency (p = 0.045, OR = 7.994), and the interval from last seizure to PET scan (p = 0.033, OR = 6.712). Moreover, we confirmed the pathology in three patients via immunohistochemistry, which underscored the potential of TSPO-PET in detecting minor lesion. Conclusions: TSPO-PET reveals patient-specific and network-level neuroinflammatory heterogeneity in MRI-negative TLE, supporting its potential role as a complementary tool for presurgical evaluation.

Background: Dynamic visual acuity (DVA) is functionally distinct from static visual acuity (SVA), though SVA is often used clinically as a reference. Methods: To identify EEG biomarkers for DVA, we presented participants with a high-contrast checkerboard moving horizontally at speeds ranging from 4°/s to 30°/s, engaging motion-sensitive pathways while preserving spatial detail. Six EEG features-ERPs (N200 and P300), TRCA, Hjorth activity, mean curve length, and Tsallis entropy-were extracted from eight occipito-parietal channels and evaluated for speed sensitivity. Results: Hjorth activity and Tsallis entropy showed consistent monotonic trends with respect to speed. Hjorth activity exhibited the strongest univariate correlation (r = 0.88, p < 0.05). In a Lasso regression model using all speed-sensitive features, the predicted speed correlated with actual speed at r = 0.588, with TRCA-weighted features retained for their multivariate contribution. Notably, Hjorth activity peaked at PO7/PO8 (3.558 and 1.478 µV² at 30°/s), aligning with V5/MT+ activation. Conclusion: Given its high sensitivity, neuroanatomical plausibility, and simplicity, Hjorth activity is recommended as a primary candidate for EEG-based DVA biomarker development. This study provides a foundation for objective neurophysiological evaluation of dynamic vision.

Background/objectives: A high-fat diet disrupts metabolic and neuroimmune balance in the brain, making neural tissue more reactive to inflammatory challenges. However, it is not well understood how this vulnerability varies across brain regions or how natural anti-inflammatory compounds influence it.

Methods: In this study, we examined how the garlic-derived molecule L-alliin modulates the inflammatory response triggered by lipopolysaccharide in the frontal cortex, hippocampus, and hypothalamus of mice fed either a standard or high-fat diet.

Results: Measurements of cytokine gene expression showed that the high-fat diet greatly increased the inflammatory response in the frontal cortex and hypothalamus, with the hypothalamus displaying the strongest overall activation. Treatment with L-alliin significantly reduced elevated cytokine levels in both regions, with the reductions most pronounced in animals on the high-fat diet. In contrast, the hippocampus showed a distinct pattern: expression of TNF-α and IL-1β changed very little across diets or treatments, whereas IL-6 and CCL2 were selectively altered by L-alliin, depending on the animals' metabolic state.

Conclusions: These findings demonstrate that diet-induced obesity does not affect the entire brain uniformly. Instead, inflammatory pathways are altered region-specifically, and L-alliin modulates these pathways with sensitivity to both brain region and metabolic condition. This work emphasizes the importance of accounting for neuroanatomical differences when developing strategies to reduce inflammation in obesity-associated conditions.

Background: Exercise is a key component in managing hypertension, yet adherence remains low. Beyond deliberate decision-making, implicit attitudes also play an important role in exercise behavior as automatic and unconscious evaluative processes. Traditional studies mostly rely on reaction time measures, which are susceptible to practice effects and fail to capture dynamic neural processing.

Objectives: This study aimed to examine whether the EEG entropy derived from implicit attitude processing can better predict exercise behavior than traditional reaction time measures in patients with hypertension.

Methods: Fifty-seven hypertensive patients completed affective and instrumental implicit association tests (IATs) with EEG recording. Seven entropy features were extracted. Multiple machine learning algorithms were applied to compare the predictive performance of reaction time with EEG entropy features. The random forest model was used to analyze the importance ranking of features from different brain regions.

Results: EEG entropy outperformed reaction times in distinguishing exercisers from non-exercisers. Affective implicit attitudes consistently demonstrated stronger accuracy than instrumental attitudes. Envelope entropy showed the most robust and significant group differences. For the random forest (RF) classifier of envelope entropy, classification accuracies were 71.9% for the affective IAT (incompatible task only), and 71.9% for the model combining affective and instrumental IAT features. Frontal and central regions contributed most to classification.

Conclusions: EEG entropy, particularly envelope entropy during affective IAT-incompatible tasks, provides superior discrimination of exercise behavior than reaction time measures. This suggests that exercise behavior is closely linked to the neural complexity underlying affective conflict processing. These findings advance our understanding of the neural dynamic patterns linking implicit attitudes and exercise behavior and suggest EEG entropy as a promising tool for assessing and intervening exercise behavior.

Background/Objectives: Response heterogeneity limits the implementation of dry needling for spasticity in multiple sclerosis (MS). This secondary analysis aimed to identify early responders and explore predictors of response. Methods: We conducted a responder analysis of a pilot randomized, double-blind, sham-controlled trial (NCT05956119) including 18 ambulatory MS patients with spasticity, randomized to a single session of dry needling (n = 9) or sham (n = 9). Sensitive responder criteria were defined as improvement ≥ 2.0 s in Timed Up-and-Go, ≥5 points in MSQOL-54 physical component, or ≥10% in 25-Foot Walk Test at 4 weeks. Results: Using these criteria, 33.3% (3/9) of dry needling recipients were classified as responders versus 0% (0/9) in the sham group (p = 0.214). Responders were more frequently observed among participants with relapsing-remitting MS (100% vs. 40%, p = 0.090) and lower baseline disability (Expanded Disability Status Scale 3.4 vs. 4.4). A positive association was observed between baseline pyramidal subscore and physical quality-of-life change, although this did not reach statistical significance (r = 0.52, p = 0.150) in the active group. Conclusions: Approximately one-third of participants met predefined responder criteria following dry needling; however, these findings should be interpreted as preliminary signals derived from an exploratory, underpowered pilot analysis. These results are hypothesis-generating and require confirmation in adequately powered trials.

Background/Objectives: The gut-brain axis and its role in neurological disorders have garnered increasing attention in recent years. However, studies assessing the association between microbiota and Alzheimer's disease in Japanese cohorts are scarce. This study investigated the potential role of the brain-gut axis in Japanese patients with Alzheimer's disease (AD), focusing specifically on the role of microbiota composition in AD pathogenesis. Methods: Ten patients with AD and 21 healthy adults across three different age groups were enrolled. Fecal microbiota composition was assessed using 16S rRNA gene sequencing. Results: We found that some bacterial species, such as Ruminococcus inulinivorans and Ruminococcus torques, were more abundant in the AD group, whereas others-including Agathobacter rectalis, Bacteroides uniformis, and Clostridium butyricum-were relatively more abundant in healthy adults. However, individual taxa differences did not reach statistical significance. Conclusions: Although our preliminary findings suggest no significant differences in fecal microbiota compositions between patients with AD and healthy individuals, they suggest that microbiota can identify a potential risk for AD development. Future research may help elucidate the bacterial species associated with AD pathogenesis, potentially enabling the use of microbiota composition as a screening tool to identify healthy individuals and those with AD or preclinical AD-an increasingly critical goal amid rising global dementia rates and the urgent need for preventive strategies.

Background/Objectives: Multimodal neuroimaging, particularly the integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), has emerged as a key methodology for investigating brain function and classifying neural activity. However, the efficient fusion of these two signals remains a formidable challenge due to their significant spatio-temporal heterogeneity. This paper presents the BiSTF-Net, which integrates decoupled and bi-directional spatio-temporal fusion mechanisms to enhance the performance of cognitive task recognition. Methods: In BiSTF-Net, the spatial features of EEG and fNIRS are mutually guided and enhanced through an efficient bi-directional cross modal guidance (Bi-CMG). Then, the temporal latencies of fNIRS signals are aligned in a data-driven manner using adaptive temporal alignment (ATA). Subsequently, the aligned features are deeply fused into a modality-invariant, discriminative representation via a symmetric cross-attention fusion (SCAF) module. Results: Evaluated on the mental arithmetic (MA), motor imagery (MI), and word generation (WG) tasks, the BiSTF-Net achieves average accuracies of 83.33%, 82.09%, and 84.99% respectively. Conclusions: The BiSTF-Net exhibits superior performance compared to the existing methods, offers a robust and interpretable solution for multimodal EEG-fNIRS cognitive task classification, and provides a methodological foundation for future extensions to other multimodal data and broader real-world clinical applications.