Brain Sciences最新文献

Background/Objectives: Non-motor symptoms (NMS) in Parkinson's disease (PD), particularly neuropsychiatric disturbances such as anxiety, significantly impact quality of life. The Holistic Care Clinic for Parkinson's disease at St George's Hospital offers multidisciplinary assessments and personalized care to address both motor and non-motor symptoms, aiming to improve patient well-being and empower patients to manage their health and enhance their quality of life. This study evaluated the effectiveness of a holistic management approach for PD patients with prominent non-motor symptoms, particularly neuropsychiatric issues, by analyzing clinical outcomes and patient feedback. Methods: A retrospective analysis was conducted on patients referred to the clinic between June 2022 and June 2023 for non-motor symptoms. Patients received comprehensive assessments, including clinical exams and interviews focused on neuropsychiatric symptoms, followed by individualized care plans. Interventions for anxiety included online psychoeducation and cardiac biofeedback. Outcomes were assessed using the Clinical Global Impression (CGI) scale and patient feedback on interventions. Results: Thirty patients (mean age 65.7 years, mean disease duration 7.8 years) were included. Anxiety was the primary referral reason (66%). CGI scores indicated that 62% of patients experienced improvement. Medications were adjusted in 14 patients and 65% improved. For anxiety, 13 patients attended the psychoeducation session, with 91% rating it "very likely"/"likely" to recommend. Ten patients completed cardiac biofeedback training, showing a significant reduction in Parkinson's Anxiety Scale scores (p = 0.03), and 90% recommending it. Conclusions: The holistic care approach of PD patients resulted in significant improvements in clinical outcomes. Patient feedback indicates high satisfaction with the interventions, supporting their acceptability and overall satisfaction with the interventions.

Introduction: This study focuses on the adaptation and validation of the Achievement Emotions Questionnaire-Short (AEQ-S) to the Spanish sports context. Emotions play a crucial role in athletes' decision making, making it essential to have reliable assessment tools tailored to this field.

Method: The AEQ-S was administered to 998 professional athletes (mean age: 26.83 years). The adaptation followed the Hambleton method and involved the support of sports psychologists. Exploratory (EFA) and confirmatory factor analyses (CFAs) were conducted, along with tests for reliability and criterion validity.

Results: The analyses confirmed that the factor structure of the AEQ-S in sports aligns with the original version, identifying eight key emotions: enjoyment, hope, pride, anxiety, anger, shame, hopelessness, and boredom. Furthermore, positive emotions were positively associated with resilience, while negative emotions showed an inverse relationship.

Conclusions: The adapted AEQ-S proved to be a valid and reliable tool for assessing emotions in athletes. Its applications extend to both research and professional practice in the sports domain.

Background: The purpose of the study was to assess the level of physical activity (PA) and identify barriers to PA for adults with intellectual disabilities attending occupational therapy workshops (OTW). Method: Forty-three people participated in the study. PA level (step count) was evaluated using the Garmin Vivofit 4. Barriers were identified using the Barriers to Being Active Quiz. Results: The mean weekly steps were 10,581 ± 3981. Respondents were significantly more active on weekdays compared to weekends (p < 0.0002). During their stay at OTW, the participants took an average of 4257 steps, which was 40% of the mean step count on weekdays. Among the identified barriers to undertaking PA, lack of willpower and lack of skills were most frequently cited among the respondents. Conclusions: The level of PA was relatively high and showed great individual variation. The high level of activity during the participants' stays in OTW indicates important role of these workshops in increasing PA in adults with intellectual disability.

Background/Objectives: Speech and motor control share overlapping neural mechanisms, yet their quantitative relationships in Parkinson's disease (PD) remain underexplored. This study investigated bidirectional associations between acoustic voice features and objective motor metrics to better understand how vocal and motor systems relate in PD. Methods: Cross-sectional baseline data from participants in a randomized neuromodulation trial were analyzed (n = 13). Motor performance was captured using an Integrated Motion Analysis Suite (IMAS), which enabled quantitative, objective characterization of motor performance during balance, gait, and upper- and lower-limb tasks. Acoustic analyses included harmonic-to-noise ratio (HNR), smoothed cepstral peak prominence (CPPS), jitter, shimmer, median fundamental frequency (F0), F0 standard deviation (SD F0), and voice intensity. Univariate linear regressions were conducted in both directions (voice ↔ motor), as well as partial correlations controlling for PD motor symptom severity. Results: When modeling voice outcomes, faster motor performance and shorter movement durations were associated with acoustically clearer voice features (e.g., higher elbow flexion-extension peak speed with higher voice HNR, β = 8.5, R² = 0.56, p = 0.01). Similarly, when modeling motor outcomes, clearer voice measures were linked with faster movement speed and shorter movement durations (e.g., higher voice HNR with higher peak movement speed in elbow flexion/extension, β = 0.07, R² = 0.56, p = 0.01). Conclusions: Voice and motor measures in PD showed significant bidirectional associations, suggesting shared sensorimotor control. These exploratory findings, while limited by sample size, support the feasibility of integrated multimodal assessment for future longitudinal studies.

Background/Objectives: Identifying pathological distinctions among mild cognitive impairment (MCI) subtypes is important for differentiating dementia. The purpose of this study is to investigate subtype-specific structural alterations in amnestic MCI (aMCI) and non-amnestic MCI (naMCI) and evaluate their potential as imaging biomarkers for subtype classification. Methods: T1 and DTI MRI data from two independent cohorts were analyzed, including a discovery dataset (58 aMCI, 35 naMCI, and 95 NC) and a replication dataset (61 aMCI, 39 naMCI, and 67 NC). Surface-based morphometry and automated fiber quantification (AFQ) were used to examine cortical thickness and white matter microstructure. Mediation models were used to explore the links between brain structure and cognitive outcomes. A logistic regression model was applied to evaluate classification performance. Results: The aMCI exhibited right hippocampal atrophy. In the naMCI, reduced cortical thickness was observed in the right anterior cingulate cortex (rACC) and opercular inferior frontal gyrus, along with increased fractional anisotropy (FA) in the right inferior fronto-occipital fasciculus (IFOF). These alterations were linked to domain-specific cognitive deficits. Moreover, partial mediation effects of IFOF FA values were observed in the link between rACC thickness and cognitive outcomes. Furthermore, these structural alterations effectively distinguished between aMCI and naMCI, showing stable performance across independent datasets (Accuracy = 0.821, AUC = 0.904). Conclusions: Our findings reveal distinct structural alterations across MCI subtypes, providing deeper insight into the heterogeneous mechanisms of dementia and supporting the potential of imaging markers for the diagnosis of MCI subtypes.

Background: Polyneuropathies impair sensory, motor, and autonomic functions, affecting functional status, cognition, and quality of life. This pilot study investigated the effects of exergame with biofeedback training (Riablo system) versus standard rehabilitation on these outcomes in outpatients with mixed-etiology polyneuropathies. Methods: Seventeen outpatients were assigned to standard rehabilitation (Group 1, n = 9) or combined standard plus Riablo training (Group 2, n = 8) over three weeks. Functional status, pain, cognition, quality of life, and psychological well-being were assessed pre- and post-intervention, with a 6-month follow-up. Outcome measures included the Morse Fall Scale, Visual Analogue Scales for pain and autonomy, Montreal Cognitive Assessment (MoCA), Trail Making Test (TMT), Stroop Test, Frontal Assessment Battery (FAB), Verbal fluency test, the Short-Form Health Survey-12 (SF-12), and the Patient Health Questionnaire-4 (PHQ-4). Longitudinal changes and between-group differences were analyzed using nonparametric statistics. Results: Both groups showed significant improvements in functional status and global cognition at post-intervention. Group 2 demonstrated greater improvements in executive functions and attention, with significant reductions in pain and fall risk. At 6-month follow-up, Group 2 maintained post-intervention gains in QoL and psychological outcomes, while Group 1 showed a significant decline. Technology evaluation revealed high usability and positive psychosocial impact in Group 2, with strong correlations between executive function improvements and device usability. Conclusions: Integrating exergames with biofeedback into standard rehabilitation may provide broader and longer-lasting benefits for polyneuropathy patients. These findings support further large-scale trials to confirm efficacy and optimize technology-assisted rehabilitation protocols.

Background/Objectives: Executive functions (EFs) and Theory of Mind (ToM) are often compromised in children with Specific Learning Disorders (SLD). Although evidence highlights the malleability of EF, studies have yet to investigate whether school-based interventions can enhance both cool and hot EF domains and support ToM development in this population. This study evaluated the effectiveness of a structured, classroom-based EF training program in improving cool EF, hot EF, and ToM in children with SLD. Methods: Forty students with SLD (aged 8-10 years) were allocated to an intervention group (n = 24) or a passive control group (n = 16). The program was delivered in small groups during regular school hours over 6-9 weeks (18 sessions). Pre- and post-intervention assessments measured cool EFs (working memory, planning, cognitive flexibility, inhibition), hot EFs (affective decision-making, delay of gratification), and ToM (false belief understanding, mental state/emotion recognition). Results: The intervention group showed significant within-group improvements in working memory, planning, and cognitive flexibility, whereas the control group showed no significant changes. Between-group comparisons revealed significant effects for working memory, planning, and ToM mental state/emotion recognition, with medium-to-large effect sizes. No significant group differences were found for hot EFs or ToM false belief understanding. Conclusions: These findings suggest that participation in a structured, school-based EF program is associated with selective improvements in specific cool EF components and one aspect of ToM in children with SLD, supporting the potential value of classroom-based interventions for cognitive and socio-cognitive development.

Affective Computing and emotion recognition hold significant importance in healthcare, identity verification, human-computer interaction, and related fields. Accurate identification of emotion is crucial for applications in medicine, education, psychology, and military domains. Electroencephalographic (EEG) signals have gained widespread application in emotion recognition due to their inherent characteristics of being non-concealable and directly reflecting brain activity. In recent years, with the establishment of open datasets and advancements in deep learning, an increasing number of researchers have integrated EEG with deep learning methods for emotion recognition studies. This review summarizes commonly used deep learning models in EEG-based emotion recognition along with their applications in this field, including the design of different network architectures, optimization strategies, and model designs based on EEG signal features. We also discuss limitations from the perspectives of commonality-individuality (C-I) and suggest improvements. The review outlines future research directions and provided a minimal C-I framework to assess models. Through this review, we aim to provide researchers in this field with a comprehensive reference and approach to balance universality and personalization to promote the development of deep learning-based EEG emotion recognition methods.

Background: Cognitive and physical functions share certain age-related patterns of change, including slowed processing speed and movement. Both functions are multifaceted, and the association between them can be affected by the type of measurement considered. This study examined one-to-one relationships between cognitive and physical functions, using data from the Compostela Aging Study. Methods: A total of 267 middle-aged and older individuals without cognitive impairment were included in the study (mean age 65.57, 75.7% women). The relationship between cognitive and physical performance was examined using Spearman's rho, adjusted for age and sex. Results: Standing up, sitting down and total times in the Timed-Up and Go test were significantly correlated with performance on the Trail-Making and phonological fluency tests. Turning time in the Timed-Up and Go test and self-reported physical activity were correlated with performance on the Spanish version of the California Verbal Learning Test. Grip strength was correlated with performance on the Counting Span task. Conclusions: This study adds evidence to the one-to-one relationship between cognitive and physical function in a subclinical cohort of middle-aged and older adults.