Frontiers in Human Neuroscience最新文献

Aim: In this systematic review and meta-analysis, we evaluated the effectiveness of transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) or transcranial random noise stimulation (tRNS) combined with dual task training (DTT) on physical and cognitive functions in adults with mild cognitive impairment (MCI), Parkinson's disease (PD), and stroke disorders.

Method: We conducted a systematic search of the Web of Science, MEDLINE, Cochrane Library, PubMed, and CINAHL databases for English-language literature on randomized clinical trials (RCTs) investigating the effects of tDCS, tACS, or tRNS combined with DTT in adults with MCI, PD, and stroke. The search covered studies from the inception of each database up to November 21, 2025. The initial screening of selected articles was conducted independently by two researchers (YLQ and WLW).

Results: A total of twelve studies met the inclusion criteria, comprising individuals with stroke (n = 4), MCI (n = 3), and PD (n = 5). Meta-analysis revealed that active tDCS+DTT yielded no significant overall improvement in global cognition (Montreal Cognitive Assessment (MoCA): SMD = 0.09, 95% CI [-0.49, 0.66], p = 0.77, I² = 72%). A large, highly homogeneous benefit was observed for executive function (TMT-B: SMD = -1.33, 95% CI [-2.39, -0.27], p = 0.01), driven exclusively by the MCI subgroup (SMD = -2.35, 95% CI [-3.20, -1.51], I² = 0%). Timed Up and Go cognitive-motor dual-task (TUG CMDT) cadence improved overall (SMD = 0.58, 95% CI [0.09, 1.08], p = 0.02, I² = 39%) in both MCI and stroke subgroups. TUG motor dual task (MDT) speed improved modestly (SMD = 0.42, 95% CI [0.02, 0.83], p = 0.04, I² = 34%), and CMDT speed showed a strong trend (SMD = -0.49, p = 0.09), only significant in stroke (SMD = -1.42, p = 0.002). However, this generalized finding must be nuanced by specific efficacy observed in individual PD studies, which reported significant gains in force-tremor decoupling, postural stability, and CMDT accuracy.

Conclusion: The meta-analysis suggests that the effects of tDCS combined with DTT are remarkable in certain populations and for specific outcomes. While substantial improvements are confirmed for executive function and dual-task gait in MCI and stroke, the overall limited efficacy in PD highlights the critical influence of heterogeneity and intervention specificity. Future research should prioritize disease-specific electrode montages and the integration of tACS or tRNS to optimize outcomes across diverse neurological populations.

Individuals with ALS and other severe motor impairments often rely on caregivers for daily tasks, which limits their independence and sense of control. Brain-robot interfaces (BRIs) have the potential to restore autonomy, but many existing systems are task-specific and highly automated, which reduces the users' sense of empowerment and limits opportunities to exercise autonomy. In particular, shared autonomy approaches hold promise for overcoming current BRI limitations, by balancing user control with increased robot capabilities. In this work, we introduce a collaborative BRI that integrates non-invasive EEG, EMG, and eye tracking to enable multi-user, multi-robot interaction in a shared kitchen environment with mobile manipulators. Our system modulates assistance through three levels of autonomy-Assisted Teleoperation, Shared Autonomy, and Full Automation-allowing users to retain meaningful control over task execution while reducing effort for routine operations. We conducted a controlled user study comparing autonomy conditions, evaluating performance, workload, ease of use, and agency. Our results show that, while Full Automation was generally preferred by users due to lower workload and higher usability, Shared Autonomy provided higher reliability and preserved user agency, especially in the presence of noisy EEG decoding. Although there was significant individual variability in EEG decoding performance, our post-hoc analysis revealed the potential benefits of customizing pipelines for each user. Finally, we note that our findings are specific to the multi-modal configuration tested and should not be interpreted as a universal claim about the superiority of any autonomy level, and, furthermore, our user study was limited by the use of healthy adults rather than target population (e.g., individuals with ALS), gender imbalance, and a relatively small sample size, which may affect generalizability. Project website: https://coopopen.github.io/.

Introduction: This study sought to identify early risk factors and develop a predictive model for progression from self-limited epilepsy with centrotemporal spikes (SeLECTS) accompanied by spike-and-wave activation in sleep (SWAS) to epileptic encephalopathy with SWAS (EE-SWAS), aiming to facilitate early clinical intervention.

Methods: From a pediatric cohort with spike-and-wave index >50%, we analyzed 77 SeLECTS patients (33 progressed to EE-SWAS, 36 remained stable over ≥2 years of follow-up). Baseline clinical and EEG features were comprehensively evaluated. Multivariate logistic regression identified independent predictors of cognitive regression, which were incorporated into a nomogram-based predictive model. Model performance was assessed using the C-index in both derivation and external validation cohorts.

Results: Prolonged spike-and-wave clusters, high-amplitude spikes with secondary generalization, and younger age at first seizure emerged as independent predictors of EE-SWAS progression. The nomogram model demonstrated high discriminative ability, with a C-index of 0.932 in the derivation cohort and 0.934 in external validation.

Conclusion: This study provides the first validated tool for early risk stratification in SWAS-associated SeLECTS, enabling clinicians to anticipate EE-SWAS progression and optimize therapeutic strategies. The model's robustness supports its potential utility in clinical decision-making to mitigate cognitive decline.

Introduction: Sleep disorders represent the most prevalent psychiatric complication following stroke, seriously impacting patients' neurological recovery, functional prognosis, and quality of life. Music therapy, as a safe, cost-effective, and non-invasive intervention, is widely employed to ameliorate post-stroke sleep disorders. However, the precise mechanisms underlying music therapy's effects on post-stroke sleep disorders require further elucidation. This review aims to systematically examine the efficacy of music therapy for post-stroke sleep disorders and to elucidate the underlying physiological mechanisms through which music may improve sleep outcomes in this population.

Methods: We conducted a systematic search across the Cochrane Library, PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, and VIP, with a search time frame ending in August 2025. Quality assessment was performed using the Version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2).

Results: A total of 1,363 subjects from 14 original articles met the criteria for inclusion in the systematic review. Each study has shown that music intervention can effectively improve the sleep status in patients with post-stroke sleep disorders.

Introduction: Brain-computer interfaces (BCIs) provide a movement-free means of communication and control, typically based on motor imagery (MI) tasks of hand, foot, or tongue movements. Most BCI studies focus on classifying up to four such tasks, which limits the number of available commands and restricts overall system functionality. Expanding the range of reliable mental tasks would directly increase the number of possible commands and thereby enhance the practical utility of BCIs. Singing imagery (SI) may offer an intuitive alternative or additional task to complement conventional MI paradigms.

Methods: EEG data were recorded from 14 participants performing right-hand, left-hand, foot, and tongue MI, SI, and rest. Features were extracted using filter bank common spatial patterns (FBCSP), and tasks were classified with a random forest algorithm across 2-, 4-, 5-, and 6-class scenarios. Subjective data regarding participants' perceived task difficulty and general task preferences was also collected.

Results: Classification accuracies with SI included were comparable to subsets of conventional MI tasks in 2-, 4-, and 5-class scenarios. In the 6-class scenario, average accuracy was approximately 60%, with six participants exceeding 70%, the level often cited as being necessary for effective BCI control. It is reasonable to expect performance to improve further with more advanced analysis methods and participant training.

Conclusion: These promising results suggest that singing imagery can serve as both an additional and an alternative task in MI-BCIs. In lower-class systems, SI may provide a valuable option for generating commands, particularly for users who may find some conventional MI tasks less intuitive. When combined with the established MI tasks, SI could increase the number of possible commands, thereby extending the functional capacity of BCI systems. Overall, this work demonstrates the potential of SI to broaden the repertoire of mental tasks available for BCI control and to advance the development of more flexible, powerful, and user-centered BCI applications.

The evolutionary adaptation of the left inferior frontal gyrus is considered a crucial neural specialization supporting the emergence of human language. As a central node in the language network, it is linked to the temporoparietal cortex via both the ventral and dorsal pathways. These connections enable humans to combine a limited set of vocal elements into infinitely diverse, hierarchically structured sequences. Although homologous brain structures are also present in non-human primates, language remains a uniquely human faculty. This review synthesizes anatomical, functional, and connectivity evidence across species to trace the evolution of the left inferior frontal gyrus in support of language. We argue that language did not emerge from novel cortical areas, but through the gradual repurposing, expansion, and optimization of pre-existing fronto-temporal circuits. Human-specific innovations include vocal neuron specialization, volumetric expansion, strengthened connectivity of the arcuate fasciculus, and a functional shift within the left inferior frontal gyrus from motor control to syntactic processing. Finally, we discuss how lesion studies contribute to our understanding of the brain's potential for language acquisition and its neurobiological constraints.

Background: Despite growing recognition of painful long COVID syndrome as a chronic neurological condition marked by pain and autonomic symptoms, the precise contribution of autonomic small fiber involvement is still not well characterized and understood. In this retrospective study, we aimed to identify autonomic small fiber involvement in patients with painful long COVID syndrome by analyzing skin biopsy data. We used nerve fiber density in the piloerector muscles (PMNFD) and sweat glands (SGNFD) as the primary histological outcomes of autonomic innervation.

Methods: We reviewed skin biopsy samples from 50 patients with painful long COVID syndrome and included 31 patients with available PMNFD and SGNFD data for analysis. PMNFD and SGNFD were compared with an age- and sex-matched healthy control group (n = 42). To evaluate whether autonomic involvement was independent of somatic nerve fiber reduction, a subgroup analysis was performed in patients with normal intraepidermal nerve fiber density (IENFD) (n = 23). Correlations between histological findings and autonomic symptoms, assessed with the COMPASS-31 questionnaire, were also analyzed.

Results: Piloerector muscle nerve fiber density and SGNFD were significantly reduced in patients with long COVID compared with controls, both in the full sample (p = 0.0135; p < 0.0001) and in the subgroup with normal IENFD (p = 0.0003; p = 0.0005). Neither PMNFD nor SGNFD correlated with COMPASS-31 scores (p = 0.27; p = 0.46) and no association with disease onset, duration and COVID-19 severity was found.

Conclusion: These findings provide histological evidence that autonomic small fiber damage is a prominent and measurable feature of painful long COVID syndrome. Importantly, this pathology was also observed in patients with preserved IENFD, indicating that autonomic involvement may occur independently of somatic small fiber loss.

Background: Gambling disorder (GD) is a behavioral addiction sharing neurobiological features with substance use disorders, yet objective biomarkers remain limited. This study examined resting-state EEG power and applied machine learning to identify potential electrophysiological markers of GD.

Methods: Resting eyes-closed Electroencephalography (EEG) was recorded from 47 individuals with GD and 32 healthy controls. Absolute and relative power across delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) bands were quantified over eight cortical regions. Group differences and correlations with the South Oaks Gambling Screen (SOGS) were analyzed. Multiple comparisons were controlled using the Benjamini-Hochberg False Discovery Rate (FDR) correction. A Linear Discriminant Analysis (LDA) classifier was trained to differentiate GD from controls based on EEG features.

Results: Group differences in EEG power were subtle, with GD showing significantly higher delta power in the left temporal region (p = 0.032, d = 0.43). Within the GD group, greater gambling severity was associated with higher absolute beta power across frontal, parietal, temporal, and occipital regions (r ≈ 0.40-0.50, p < 0.01), and these associations remained significant after FDR correction (pFDR < 0.05). The LDA model using absolute power achieved 73.7% classification accuracy (AUC = 0.74), whereas relative power yielded near-chance accuracy (57.9%).

Conclusions: GD is characterized by subtle but meaningful EEG alterations, particularly increased beta activity linked to gambling severity. Multivariate EEG patterns can distinguish GD from controls, supporting the potential of resting-state EEG as a biomarker for clinical assessment and severity monitoring in behavioral addiction.

Purpose: This study examined story retelling in individuals with aphasia who scored at or above the 93.8 cutoff on the Aphasia Quotient (AQ) of the Western Aphasia Battery-Revised (WAB-R). The performance of these participants deemed "not aphasic by WAB" (NABW) was compared with the performance of non-aphasic participants and individuals with anomic aphasia.

Method: Most participants were from a test development dataset for the Brief Assessment of Transactional Success in communication in aphasia (BATS), including four groups of 16 individuals: (1) a group who tested NABW; (2) a group with anomic aphasia matched on gender, age, education, and time post-onset; (3) a group with mild anomic aphasia who scored just below the NABW cutoff; and (4) a group of non-aphasic individuals matched on gender, age, and education with the NABW group. Groups were compared on main concepts of the BATS story retelling. Groups with aphasia were also compared on the main concepts of stories retold by non-aphasic conversation partners following co-construction of stories and on self-reported scores of the impact of aphasia on everyday communication.

Results: The results showed significant differences in the retelling of the story's main concepts between the non-aphasic control and conversation partner groups, with non-monotonic decreases in performance in comparisons of groups with and without aphasia: from non-aphasic to NABW to mildly anomic to anomic. Individuals deemed NABW (and their conversation partners) did not perform significantly better than individuals with mild anomic aphasia (and their conversation partners) on story retell main concepts. There were significant differences in the production of AphasiaBank discourse main concepts between the group with anomia and both the non-aphasic and NABW groups, but not between the non-aphasic and NABW or those with mild aphasia.

Conclusion: Individuals with aphasia who scored "non-aphasic" on the WAB demonstrated impairments in story retelling that align with their self-report of diminished everyday communicative functioning. This finding adds to growing support for the addition of a new measure of functional communication to the core outcome set of measures utilized in aphasia research. We propose the BATS, a measure that is sensitive across the spectrum of aphasia severity, including cases of mild and subclinical aphasia.