Brain Sciences最新文献

Background/Objectives: Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is a safe and established therapy for management of refractory motor fluctuations and dyskinesia in Parkinson's disease (PD). However, the relationship between stimulation site connectivity and improvement of axial gait symptoms remains poorly understood, particularly when stimulating in the GPi. This study investigated functional and structural connectivity patterns specifically associated with axial symptom outcomes following bilateral GPi-DBS, and, as a secondary exploratory analysis, examined whether Volumes of tissue activated (VTAs)-based connectivity related to overall UPDRS-III change. Methods: We retrospectively analyzed 19 PD patients who underwent bilateral GPi-DBS at the University of Florida (2002-2017). Unified Parkinson's Disease Rating Scale (UPDRS-III) axial gait subscores were assessed at baseline and 36-month follow-up. VTAs were reconstructed using Lead-DBS and coregistered to Montreal Neurological Institute (MNI) space. Structural connectivity was evaluated with diffusion tractography, and functional connectivity was estimated using normative resting-state fMRI datasets. Correlations between VTA connectivity and clinical improvement were examined using Spearman correlation and voxelwise analyses. Results: Patients with axial improvement in motor scales demonstrated specific VTA connectivity to sensorimotor and supplementary motor networks, particularly lobule V and lobules I-IV of the cerebellum. These associations were specific to axial gait subscores. In contrast, worsening axial gait symptoms correlated with connectivity to cerebellar Crus II, cerebellum VIII, calcarine cortex, and thalamus (p < 0.05). Total UPDRS-III scores did not show a significant positive correlation with supplementary motor area or primary motor cortex connectivity; a non-significant trend was observed for VTA-M1 connectivity (R = 0.41, p = 0.078). Worsening total motor scores were associated with cerebellar Crus II and frontal-parietal networks. These findings suggest that distinct connectivity patterns underlie differential trajectories in axial and global motor outcomes following GPi-DBS. Conclusions: Distinct connectivity profiles might underlie axial gait symptom outcomes following GPi-DBS. Connectivity to motor and sensorimotor pathways supports improvement, whereas involvement of Crus II and occipital networks predicts worsening. Additional studies to confirm and expand on these findings are needed, but our results highlight the value of connectomic mapping for refining patient-specific targeting and developing future programming strategies.

Purpose: This study aims to develop a method for detecting referable (intermediate and advanced) age-related macular degeneration (AMD) and neovascular AMD, as well as providing an automatic segmentation of choroidal neovascularisation (CNV) on colour fundus retinal images. We also demonstrated that brain health risk scores estimated by AI-based Retinal Image Analysis (ARIA), such as white matter hyperintensities and depression, are significantly associated with AMD and neovascular AMD. Methods: A primary dataset of 1480 retinal images was collected from Zhongshan Hospital of Fudan University for training and 10-fold cross-validation. Additionally, two validation subdataset comprising 238 images (retinal images and wide-field images) were used. Using fluorescein angiography-based labels, we applied the InceptionResNetV2 deep network with the ARIA method to detect AMD, and a transfer ResNet50_Unet was used to segment CNV. The risks of cerebral white matter hyperintensities and depression were estimated using an AI-based Retinal Image Analysis approach. Results: In a 10-fold cross-validation, we achieved sensitivities of 97.4% and 98.1%, specificities of 96.8% and 96.1%, and accuracies of 97.0% and 96.4% in detecting referable AMD and neovascular AMD, respectively. In the external validation, we achieved accuracies of 92.9% and 93.7% and AUCs of 0.967 and 0.967, respectively. The performances on two validation sub-datasets show no statistically significant difference in detecting referable AMD (p = 0.704) and neovascular AMD (p = 0.213). In the segmentation of CNV, we achieved a global accuracy of 93.03%, a mean accuracy of 91.83%, a mean intersection over union (IoU) of 68.7%, a weighted IoU of 89.63%, and a mean boundary F1 (BF) of 67.77%. Conclusions: The proposed method shows promising results as a highly efficient and cost-effective screening tool for detecting neovascular and referable AMD on both retinal and wide-field images, and providing critical insights into CNV. Its implementation could be particularly valuable in resource-limited settings, enabling timely referrals, enhancing patient care, and supporting decision-making across AMD classifications. In addition, we demonstrated that AMD and neovascular AMD are significantly associated with increased risks of WMH and depression.

Treatment-resistant psychiatric disorders represent a major clinical challenge, with a significant proportion of patients remaining refractory to conventional pharmacological and psychotherapeutic interventions. Deep brain stimulation (DBS), a neurosurgical technique delivering targeted electrical impulses to specific brain regions, has emerged as a promising intervention across a spectrum of refractory psychiatric conditions. This comprehensive narrative review synthesizes current evidence on the efficacy, safety, and practical considerations of DBS for treatment-resistant major depressive disorder, obsessive-compulsive disorder, bipolar disorder, schizophrenia, addictions, Tourette's syndrome, anorexia nervosa, post-traumatic stress disorder, and refractory aggression in autism spectrum disorder with severe intellectual disability. Across most conditions, DBS demonstrates clinically meaningful symptom reductions, with response and remission rates in depression and obsessive-compulsive disorder approaching 48% and 35%, respectively. For Tourette's syndrome and refractory aggression in autism, over two-thirds of patients' experience > 50% symptom reduction. Preliminary data in bipolar disorder, schizophrenia, addictions, and anorexia nervosa are encouraging but limited by small sample sizes and methodological heterogeneity. Safety profiles are generally acceptable, with the majority of adverse events being device- or procedure-related; psychiatric adverse effects and rare serious complications underscore the importance of careful patient selection and monitoring. However, the literature is constrained by inconsistent study designs, a paucity of randomized controlled trials, heterogeneity in DBS targets and stimulation parameters, and limited long-term and quality-of-life outcomes. Optimization of anatomical targeting, stimulation protocols, and patient selection criteria remains an ongoing challenge. Future directions require larger, rigorously controlled trials with standardized outcome measures, integration of neurobiological biomarkers, and multidisciplinary collaboration. In summary, while DBS offers transformative potential for select cases of refractory psychiatric illness, its application must be guided by scientific rigor, ethical prudence, and individualized patient-centered care.

Objectives: Neuronavigation may improve the precision and reproducibility of repetitive transcranial magnetic stimulation (rTMS) by aligning stimulation with individualized targets. Whether navigation-guided rTMS benefits post-stroke upper-limb recovery is unclear. We conducted a PRISMA-compliant systematic review and meta-analysis to estimate the effect of navigated rTMS, added to standard rehabilitation, versus sham. Methods: The protocol was registered in PROSPERO (CRD420251165052). Two reviewers independently searched CENTRAL, MEDLINE, Embase, CINAHL, Web of Science, and Google Scholar (October 2025), screened records, extracted data, and assessed risk of bias (Cochrane RoB-1). The prespecified primary endpoint was changed in Fugl-Meyer Assessment of the upper extremity (FMA-UE) from baseline to end of treatment. Effects were pooled as mean differences under random-effects models. When change-score standard deviations (SDs) were unavailable, they were derived from pre/post SDs assuming within-person correlation r = 0.5; sensitivity analyses used r = 0.7 and r = 0.9. Multi-arm trials were combined to avoid double counting. Results: four randomized, sham-controlled trials (n = 297) contributed end-of-treatment change in FMA-UE. The pooled effect favored navigated rTMS but was not statistically significant (MD 3.65, 95% CI -1.84 to 9.13; I² = 73%). Sensitivity analyses with higher r produced directionally consistent estimates. A subgroup of 2-week (10-session) protocols (k = 3) showed a significant benefit (MD 7.09, 95% CI 4.14 to 10.05; I² = 0%). Most risk-of-bias domains were low risk. Conclusions: Navigated rTMS did not show a consistent short-term advantage over sham on FMA-UE across heterogeneous protocols. A positive signal in standardized 2-week courses supports further adequately powered multicenter randomized controlled trials (RCTs) with harmonized protocols and complete variance reporting.

Music is a near-universal anthropological and sensory phenomenon that engages distributed brain networks and peripheral physiological systems to shape emotion, cognition, sociality, and bodily regulation. Evidence from electrophysiology, neuroimaging, endocrinology, randomized controlled trials, and longitudinal training studies indicates that both receptive and active musical experiences produce experience-dependent neural and systemic adaptations. These include entrainment of neural oscillations, modulation of predictive and reward signaling, autonomic and neuroendocrine changes, and long-term structural connectivity alterations that support affect regulation, cognition, social functioning, motor control, sleep, and resilience to neuropsychiatric illness. This narrative review integrates mechanistic domains with clinical outcomes across major conditions, such as depression, anxiety, schizophrenia, dementia, and selected neurodevelopmental disorders, by mapping acoustic and procedural parameters onto plausible biological pathways. We summarize how tempo, beat regularity, timbre and spectral content, predictability, active versus passive engagement, social context, dose, and timing influence neural entrainment, synaptic and network plasticity, reward and prediction-error dynamics, autonomic balance, and immune/endocrine mediators. For each condition, we synthesize randomized and observational findings and explicitly link observed improvements to mechanistic pathways. We identify methodological limitations, including heterogeneous interventions, small and biased samples, sparse longitudinal imaging and standardized physiological endpoints, and inconsistent acoustic reporting, and translate these into recommendations for translational trials: harmonized acoustic reporting, pre-specified mechanistic endpoints (neuroimaging, autonomic, neuroendocrine, immune markers), adequately powered randomized designs with active controls, and long-term follow-up. Contextual moderators including music education, socioeconomic and cultural factors, sport, sleep, and ritual practices are emphasized as critical determinants of implementation and effectiveness.

The journal retracts the article titled "Neutrophil-Lymphocyte Ratio as a Predictor of Cerebral Small Vessel Disease in a Geriatric Community: The I-Lan Longitudinal Aging Study" [...].

Background/Objectives: Distraction is a form of impaired selective attention that becomes more pronounced with normal aging and in pathological conditions such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). Event-related potentials (ERPs) provide sensitive, time-resolved measures of neural mechanisms underlying distractibility. This study aimed to identify age- and disease-related ERP signatures of auditory-visual distraction as potential functional biomarkers for cognitive decline. Methods: Forty-six participants were enrolled, including young controls (Y), healthy older controls (O), individuals with MCI, and individuals with AD. Participants performed cross-modal interference tasks in which irrelevant auditory distracting sounds were paired with a relevant visual discriminating task. The distraction potential was quantified as the difference between ERP responses to novel distractors and standard stimuli, focusing on three core components: N1-enhancement, P3a, and reorienting negativity (RON). Behavioral measures (accuracy, reaction time, miss responses) were also assessed. Results: Compared to Y, O showed increased N1-enhancement and reduced P3a and RON amplitudes, consistent with age-related susceptibility to distraction. Patients with MCI and AD exhibited further abnormalities, including diminished P3a and altered RON responses, suggesting impaired orientation and reorientation of attention. Behavioral distraction effect was observed in all groups, with no significant difference between groups. ERP-cognition correlations indicated that reduced P3a amplitude and delayed RON were associated with executive dysfunction and memory deficits. Conclusions: ERP signatures of distraction, particularly altered P3a and RON components, differentiate normal aging from pathological decline and may serve as functional biomarkers for early detection of MCI and AD. These findings highlight the translational potential of distraction paradigms in clinical assessment of aging-related cognitive impairment.

Background: Although modifiers and function words are critical in cognitive linguistic assessments and cognitive training has proven to promote synaptic neural activity, they often receive limited attention, particularly in computational data-scarce settings. This study addresses communication difficulties associated with cognitive impairments using engineering data, a design to improve the evaluation of language attributes, applied specifically to these elements. A framework was developed to analyze potential language alterations resulting from traumatic brain injury (tbi), using narrative samples, primary data, and unconventional methods to overcome the limitations of existing resources. Methods: The core technique involves pairing language attributes based on defined relationships and assessing responses using standard statistical learning methods. Direct and normalized evaluations of variables, calculated using the Northwestern Narrative Language Analysis (nnla) profile from the original data, serve as benchmarks. The Area Under the Curve (auc) metric with the corresponding statistical support are reported. Results: The results indicate that the proposed method revealed informative patterns involving modifiers and function words that remained hidden in the baseline approaches. Although some exceptions were observed, results showed a substantially consistent behavior, and the responses achieved promote their use in a clinical setting. Conclusions: The findings can provide valuable directions for theoretical and applied research in language assessment. Identifying specific points of breakdown within language structures can improve the accuracy of rehabilitation plans and better leverage the neuroplastic response of the brain for recovery.

Background/Objectives: Amnestic mild cognitive impairment (aMCI) represents a transitional stage between normal aging and dementia, constituting a critical intervention window for Alzheimer's disease (AD). As a non-invasive intervention, neurofeedback training (NFT) has demonstrated potential in ameliorating cognitive deficits and clinical symptoms in aMCI patients; however, its mechanistic effects on functional brain connectivity remain inadequately elucidated. Methods: This study employed low- and high-order functional analytical approaches to comprehensively investigate the effects of NFT on dynamic brain functional networks in aMCI. Results: Our findings revealed that following NFT, aMCI patients exhibited enhanced connectivity strength, global efficiency, and nodal characteristics within the delta band, whereas connectivity was generally attenuated in the theta, alpha, and beta bands. Dynamic network analysis indicated increased entropy in short-time windows. Cognitive assessments showed a significant short-term improvement in MoCA scores among 92.9% of participants. Conclusions: These results suggest that NFT effectively remodels brain network activity patterns in aMCI patients, thereby facilitating cognitive improvement. These findings provide preliminary insights into the brain network mechanisms underlying NFT-mediated cognitive enhancement in aMCI.

Background: Germany provides a worldwide almost unique legal framework for offenders with substance use disorders through § 64 of the German Criminal Code, mandating a two-year multimodal therapy including an in-house clinical treatment period followed by a reintegration phase with gradually reduced supervision. During this phase, lapses are often concealed, with synthetic cannabinoids (SCs) serving as a potential tool due to limited detection in routine screenings and heterogeneous monitoring practices across forensic psychiatric clinics.

Methods: This study compared two forensic hospitals, Guenzburg and Kaufbeuren, over a ten-year period, from 2014 to 2024, to evaluate monitoring strategies. While Kaufbeuren applied a case-dependent testing approach, including unannounced urine screenings, Guenzburg introduced a stricter regime in 2019, combining mandatory hair analysis three months into reintegration with unannounced broad-spectrum screenings including SCs.

Results: Among the 527 patients included in this study, significantly more tests were conducted in Guenzburg after 2022. The different approach between hair vs. urine analysis produced a seven-fold higher detection rate of SC use compared to Kaufbeuren. Across both clinics, however, SC-positive patients shared similar features. They were younger at first conviction, more frequently under substitution treatment, and more likely to have committed violent offenses. A history of violence quadrupled SC-positive odds, while time since leave as such increased odds by 0.1% per day.

Conclusions: In conclusion, these results underscore the effectiveness of standardized long-term SC monitoring using hair analysis and the predictive role of a history of violence in the context of SC-relapse.