@article {pmid42783134,
year = {2026},
author = {Pan, B and Ding, S and Geng, Y and Liang, J and Li, F and Wang, G and Li, X and Dong, Y and Li, R},
title = {Systematic Benchmarking of a Dry Electrode EEG Prototype Against Wet Electrode EEG Systems in Electrophysiological/Cognitive Scenarios.},
journal = {Biosensors},
volume = {16},
number = {9},
pages = {},
pmid = {42783134},
issn = {2079-6374},
support = {82301743//National Natural Science Foundation of China/ ; 0016/2024/RIB1//Science and Technology Development Fund/ ; 2025A1515010539//Guangdong Provincial Natural Science Foundation/ ; MYRG-GRG2024-00296-ICI//University of Macau/ ; MYRG-CRG2024-00022-ICI//University of Macau/ ; GZY-KJS-SD-2023-067//the Joint TCM Science & Technology Projects of National Demonstration Zones for Comprehensive TCM Reform/ ; },
mesh = {Humans ; *Electroencephalography ; Electrodes ; *Cognition ; Brain-Computer Interfaces ; Female ; Evoked Potentials, Visual ; Male ; Adult ; Benchmarking ; Signal-To-Noise Ratio ; Young Adult ; },
abstract = {OBJECTIVE: Recent advances in dry electrode EEG have enabled rapid setup and recording in unconventional scenarios. However, past developments were primarily driven by brain-computer interfaces (BCI), leaving their comparability to wet electrodes in clinical and daily life applications an open question. Here, we developed a new dry EEG system and systematically benchmarked its performance against a commercial wet EEG system across various tasks.

METHODS: Participants (n = 19) underwent simultaneous recording using both devices. We first collected resting-state EEG under both eyes-closed and eyes-open conditions, followed by a steady-state visual evoked potential (SSVEP) task at different flicker frequencies and a motor imagery (MI) task. System performance was evaluated using power spectral density (PSD), signal to noise ratio (SNR), event-related spectral perturbation (ERSP), and single-trial classification accuracy.

RESULTS: The two systems performed similarly across different tasks. During the resting state, no statistically significant differences were observed between the two systems in the PSD of the five frequency bands (p > 0.05 in all cases). Similarly, SNR in the SSVEP task showed no significant differences at 8 Hz, 10 Hz, and 12 Hz after correction. For cognitive tasks, classification accuracies were comparable (SSVEP: dry 80.08% ± 7.1% vs. wet 81.10% ± 6.5%; MI: dry 72.46% ± 3.89% vs. wet 70.7% ± 2.37%).

CONCLUSIONS: The developed dry EEG system can effectively record electrophysiological measurements commonly employed in research and clinical settings, with quality comparable to that of traditional wet EEG systems.},
}

Humans
*Electroencephalography
Electrodes
*Cognition
Brain-Computer Interfaces
Female
Evoked Potentials, Visual
Male
Adult
Benchmarking
Signal-To-Noise Ratio
Young Adult

@article {pmid42783373,
year = {2026},
author = {Sanft, TB and Siuliukina, N and O'Neal, B and Khojandi, N and Jankowitz, RC and Pegram, MD and Diab, S and Zhang, Y and Anderson, AKL and Treuner, K and O'Shaughnessy, JA},
title = {Breast Cancer Index and Recommendations for Extended Endocrine Therapy.},
journal = {JAMA network open},
volume = {9},
number = {9},
pages = {e2634974},
pmid = {42783373},
issn = {2574-3805},
mesh = {Aged ; Female ; Humans ; Middle Aged ; *Antineoplastic Agents, Hormonal/therapeutic use ; *Breast Neoplasms/drug therapy/genetics/pathology/diagnosis ; Cohort Studies ; Prognosis ; Prospective Studies ; Registries ; Risk Assessment/methods ; },
abstract = {IMPORTANCE: The Breast Cancer Index (BCI) is an established genomic assay that provides individualized risks of overall and late distant recurrence and predicts the likelihood of extended endocrine therapy (EET) benefit in patients with early-stage, hormone receptor-positive (HR+) breast cancer. Previous findings from the first 1000 patients in the prospective BCI Registry showed that physicians changed their EET recommendation in more than 40% of patients.

OBJECTIVE: To investigate the use of the BCI in the full registry cohort and how physicians integrate prognostic and predictive results in real care settings.

The BCI Registry study is a US multicenter evaluation of long-term clinical outcome, decision impact, and medication adherence among patients enrolled from April 2021 to January 2024. Participants included women diagnosed with early-stage, HR+ breast cancer. Physician and patient questionnaires about recommendations or preferences for EET and confidence or comfort with these decisions were collected. For this cohort study, data were analyzed from January 2025 to March 2026.

EXPOSURE: Patients received BCI testing and endocrine therapy. The BCI prognostic model calculated a risk score to classify patients as having low or high risk of late distant recurrence, while the BCI predictive component used the BCI HOXB13/IL17BR (H/I) ratio to classify patients as having low or high likelihood of EET benefit.

MAIN OUTCOMES AND MEASURES: Change in physicians' and patients' recommendations or preferences for EET, and their confidence or comfort with these decisions. Pre-BCI and post-BCI results were analyzed using the McNemar test. Fisher exact test was used to determine the association between BCI categories and clinical variables.

RESULTS: The final analysis included 2900 women with completed physician and patient questionnaires (mean [SD] age, 65.2 [10.3] years). Among these patients, 2570 (88.6%) were postmenopausal, 2245 (77.4%) were N0, and 2501 (86.2%) were HER2-negative. After BCI testing, 1209 physicians (41.7%) changed their EET recommendation (P < .001), and 1479 patients (51.0%) changed their preference for EET (P < .001). Among 1100 patients classified as BCI (H/I)-High, EET recommendations increased from 671 pre-BCI (61.0%) to 1014 post-BCI (92.2%). Among 1800 patients classified as BCI (H/I)-Low, the number of physicians not recommending EET increased from 856 (47.6%) to 1576 (87.6%). Physician confidence in their recommendation increased for 1269 patients (43.8%; P < .001), and 1260 patients (43.4%) were more comfortable with the EET decision (P < .001).

CONCLUSIONS AND RELEVANCE: This cohort study of patients from the BCI Registry highlights the important treatment guidance provided by the BCI to reduce EET undertreatment or overtreatment and further substantiates its clinical utility to individualize patient care.},
}

Aged
Female
Humans
Middle Aged
*Antineoplastic Agents, Hormonal/therapeutic use
*Breast Neoplasms/drug therapy/genetics/pathology/diagnosis
Cohort Studies
Prognosis
Prospective Studies
Registries
Risk Assessment/methods

@article {pmid42785279,
year = {2026},
author = {Du, X and Xu, X and Zeng, H and Zhang, H and Yu, J and Deng, H and Song, A and Zhang, W and Chen, D},
title = {OrthoTSS: A Zero-Calibration Framework for Cross-Subject P300 Decoding Via Orthogonality-Guided Task-Subject Separation.},
journal = {IEEE transactions on bio-medical engineering},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TBME.2026.3735299},
pmid = {42785279},
issn = {1558-2531},
abstract = {OBJECTIVE: Cross-subject P300 decoding remains challenging for zero-calibration brain-computer interfaces (BCIs), as inter-subject variability must be reduced while preserving weak task-relevant neural information.

METHODS: We propose Orthogonality-guided Task-Subject Separation (OrthoTSS), integrating a multi-scale spatio-temporal frontend, dual bidirectional Mamba streams, and orthogonality regularization. The task stream performs target/non-target decoding, while an auxiliary domain stream models subject-related variability during training. The regularization reduces linear cross-stream coupling and promotes functional differentiation without assuming complete disentanglement.

RESULTS: Under leave-one-subject-out (LOSO) evaluation, OrthoTSS achieved 76.35% balanced accuracy on PhysioNet ERP and 86.75% on Naturalistic Search FRP. It showed favorable performance against representative architectural, recent cross-subject, and domain-generalization baselines. Ablation and representation analyses further indicated reduced cross-stream similarity and relative branch specialization while preserving task-discriminative structure.

CONCLUSION: OrthoTSS improves cross-subject P300 decoding by promoting functional differentiation between task-related and subject-related representations while retaining discriminative neural information.

SIGNIFICANCE: This task-preservation-oriented framework provides offline evidence toward practical zero-calibration P300 BCI decoding.},
}

@article {pmid42785492,
year = {2026},
author = {Liu, C and Zhang, D and Wang, Y and Fan, X and Fang, F},
title = {Dynamic reorganization of brain network information during emotion and identity recognition.},
journal = {NeuroImage},
volume = {341},
number = {},
pages = {122259},
doi = {10.1016/j.neuroimage.2026.122259},
pmid = {42785492},
issn = {1095-9572},
abstract = {Facial expression recognition jointly encodes identity and emotion within large scale brain networks, yet how identity and emotion information are represented and dynamically propagated remains unknown. To address this, we employed a dual-task paradigm integrating emotion and identity recognition with dynamic facial expressions, and recorded MEG signals to track millisecond-level neural dynamics. Using a network-based decoding framework, we identified discriminative spatiotemporal patterns supporting emotion and identity processing. We further applied Partial Information Decomposition (PID) to reveal how redundancy and synergy jointly govern information flow across large scale brain networks. The decoding results revealed distinct spatiotemporal organizations for emotion and identity processing. Emotion decoding exhibited a two-stage temporal processing pattern, with peaks at 180 to 360 ms and 580 to 660 ms, engaging early sensory and later frontoparietal, sensorimotor, and occipitotemporal networks, whereas identity decoding showed a single peak within a stable, bilaterally distributed network spanning temporal, sensorimotor, and frontoparietal regions. Information-theoretic analyses uncovered that rapid processing of facial expressions was dominated by redundant information, whereas integrated information emerged progressively within frontoparietal networks. Together, these findings provide a comprehensive computational account of how the brain dynamically encodes and coordinates emotional and identity information, revealing core principles of facial expression perception.},
}

@article {pmid42787344,
year = {2026},
author = {Naumov, AV and Soghoyan, GA and Makarova, AV and Syrov, NV and Skripnikov, AA and Kustov, YV and Sufianov, AA and Lebedev, MA},
title = {A stereoencephalography study of internal speech.},
journal = {Cognitive neurodynamics},
volume = {20},
number = {1},
pages = {183},
pmid = {42787344},
issn = {1871-4080},
abstract = {UNLABELLED: With advances in intracranial recording techniques, converting speech-related brain activity into commands for brain-computer interfaces (BCIs) is becoming increasingly feasible. In this study, we explored the utility of stereoencephalography (sEEG) for decoding covert and overt speech in humans. sEEG data were collected from 11 epilepsy patients undergoing presurgical monitoring, while they performed a set of speech tasks-overt speech, articulated speech, and imagined (inner) speech, as well as a handwriting task. Time- and frequency-domain analyses revealed that each speech condition elicited distinct spectral modulations, particularly in the alpha (8-12 Hz) and gamma (50-80 Hz) bands across temporal and frontal regions. Inner speech exhibited reduced and delayed activation in key motor and language-related areas, distinguishing it from both overt and articulated speech. In contrast, handwriting evoked a different activity pattern, marked by gamma desynchronization and more sustained alpha increases. A machine learning classifier achieved an average accuracy of 72% in distinguishing the three speech conditions based on their neural spectral profiles. These findings show that imagined speech is neurally the most distinct compared to the other speech tasks and demonstrate that sEEG can reliably detect the transitions between internal and overt forms of speech. This work contributes to the development of multimodal BCIs capable of decoding covert language representations, with implications for restoring communication in individuals with severe motor or speech impairments.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s11571-026-10554-9.},
}

@article {pmid42787353,
year = {2026},
author = {Cai, J and Gao, M and Li, G and Zhao, X and Xu, C and Chen, L and Xu, F and Hu, F},
title = {A dynamic multi-branch EEG decoding network for motor imagery classification with preliminary clinical validation.},
journal = {Frontiers in neuroscience},
volume = {20},
number = {},
pages = {1918072},
pmid = {42787353},
issn = {1662-4548},
abstract = {Motor imagery electroencephalography (MI-EEG) decoding remains challenging because of the low signal-to-noise ratio, non-stationarity, and inter-subject variability of EEG signals. This study proposes a dynamic multi-branch EEG decoding network (DMB-EDN) that jointly models temporal dynamics, learnable time-frequency patterns, and rhythm-specific spectral information. DMB-EDN combines a learnable Gabor-based time-frequency representation with physiologically guided rhythm modeling and employs trial-conditioned dynamic fusion to estimate the contribution of each branch separately for each EEG trial. This design enables adaptive coordination of complementary data-driven and physiology-guided representations. The proposed method was evaluated on the BCI Competition IV 2a dataset, the High Gamma Dataset, and a self-collected spinal cord injury (SCI) dataset. Under subject-specific evaluation, DMB-EDN achieved an average accuracy of 96.41% and a kappa of 0.952 on BCI Competition IV 2a. On the High Gamma Dataset, it achieved performance comparable to the strongest baseline under near-saturated conditions. Under leave-one-subject-out evaluation on the SCI dataset, DMB-EDN obtained an accuracy of 85.00% and a kappa of 0.700, providing preliminary evidence of improved offline cross-subject decoding. Ablation experiments confirmed the complementary contributions of the three representation branches and trial-conditioned fusion, while fusion-weight analysis revealed systematic class- and oscillation-related variations. These results demonstrate the effectiveness of DMB-EDN for EEG decoding, although validation on larger multicenter cohorts and prospective online BCI systems remains necessary.},
}

@article {pmid42787417,
year = {2026},
author = {Li, X and Zhong, J and Fan, SS and Yin, JY and Gao, X and Li, W},
title = {The construction and psychometric evaluation of the self-structure scale: a bidimensional model of self-structure.},
journal = {Frontiers in psychiatry},
volume = {17},
number = {},
pages = {1942305},
pmid = {42787417},
issn = {1664-0640},
abstract = {BACKGROUND: Although psychoanalytic and personality theories have consistently highlighted the central role of self-structure, existing psychometric tools predominantly measure isolated personality traits or narcissistic subtypes, with scarce instruments dedicated to evaluating the organizational mechanisms governing self-related functioning. This study puts forward a bidimensional theoretical framework of self-structure and constructs the Scale of Self-Structure (SOSS), aiming to empirically verify the measurable manifestation of the proposed theoretical dimensions.

METHODS: Two sequential empirical studies were performed to construct and psychometrically validate the SOSS. Study 1 covered item pool development, exploratory factor analysis (EFA), internal consistency testing, and test-retest reliability verification. A total of 1,954 participants were recruited for initial scale refinement, and an independent subsample of 128 respondents completed retest assessments to evaluate temporal stability. Study 2 recruited 3,805 participants split across two separate cohorts: Sample 3 (n = 2,570) and Sample 4 (n = 1,235). This sample was used for cross-sample structural validation and comprehensive psychometric examinations, including confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), internal reliability evaluation, multi-group measurement invariance tests, discriminant validity estimation, and person-centered latent profile clustering. Supplementary narcissism measurement data collected from Sample 4 further supported analyses of convergent and nomological validity.

RESULTS: EFA yielded a 28-item SOSS encompassing four correlated first-order factors: Positive Self, Self-Center, Idealized Identification, and Vulnerable Self. In Study 2, competing measurement models were compared. The four-factor exploratory structural equation modeling (ESEM) solution exhibited the best fit to the data, implying that self-structural processes consist of interrelated yet partially overlapping components, rather than following a strictly hierarchical structure. The SOSS showed acceptable internal consistency and temporal stability, supported measurement invariance across gender, and displayed adequate discriminant validity together with theoretically consistent correlations with grandiose and vulnerable narcissism. Subsequent person-centered analyses tentatively revealed four distinct profile configurations within the two-dimensional structural space defined by the SOSS.

CONCLUSIONS: This study provides preliminary empirical evidence supporting the SOSS as a multidimensional instrument for assessing individual differences in self-structural organization. Established based on psychodynamic self-organization theories and validated through systematic psychometric examinations, the SOSS may serve as a tentative framework for understanding self-investment, relational functioning, and self-cohesion beyond traditional trait-based indicators. Given the nonclinical and culturally homogeneous sample of the present study, future investigations incorporating longitudinal designs, demographically diverse cohorts, clinical populations, and cross-cultural validation are required to further elucidate the developmental implications, generalizability, and clinical applicability of the self-structural dimensions captured by the SOSS.},
}

@article {pmid42787461,
year = {2026},
author = {Singh, K and Yuvaraj, R and Sharma, G and Joshi, A},
title = {Editorial: Modern applications of EEG in neurological and cognitive research.},
journal = {Frontiers in computational neuroscience},
volume = {20},
number = {},
pages = {1969406},
doi = {10.3389/fncom.2026.1969406},
pmid = {42787461},
issn = {1662-5188},
}

@article {pmid42789169,
year = {2026},
author = {Wu, Y and Zhang, R and Wu, F and Liu, M and Wang, Y and Sun, W and Cai, W},
title = {Comparative efficacy of brain-computer interface-coupled robotic rehabilitation, robot-assisted therapy, and motor imagery for upper-limb motor recovery after stroke: a systematic review and network meta-analysis.},
journal = {Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology},
volume = {47},
number = {10},
pages = {},
pmid = {42789169},
issn = {1590-3478},
support = {2026JD06//Capital Health Management and Policy Research Base/ ; ZHKY202526//Chinese Nursing Association/ ; },
mesh = {Humans ; *Stroke Rehabilitation/methods ; *Robotics/methods ; *Brain-Computer Interfaces ; *Recovery of Function/physiology ; *Upper Extremity/physiopathology ; *Stroke/therapy/physiopathology/complications ; *Imagery, Psychotherapy/methods ; Treatment Outcome ; },
abstract = {OBJECTIVE: To compare and rank the efficacy of brain-computer interface-coupled robotic rehabilitation (BCI-robot), robot-assisted therapy, motor imagery (MI), and conventional rehabilitation for upper-limb recovery after stroke, and to explore whether treatment effects differed according to key clinical and intervention-related characteristics.

METHODS: A systematic search was conducted in 11 databases from inception to March 31, 2026. Randomized controlled trials enrolling adults with post-stroke upper-limb motor impairment were included. The primary outcome was the Fugl-Meyer Assessment of Upper Extremity (FMA-UE). Secondary outcomes included the Action Research Arm Test (ARAT), Wolf Motor Function Test (WMFT), and Modified Barthel Index (MBI). Direct pairwise meta-analyses were performed using mean differences (MDs) with 95% confidence intervals (CIs), and a frequentist network meta-analysis was conducted to synthesize direct and indirect evidence and rank interventions using P-scores.

RESULTS: Twenty-three reports representing 22 independent study cohorts were included, comprising 727 participants. Network meta-analysis showed no significant inconsistency, and the consistency model was adopted. BCI-robot ranked highest for improving FMA-UE according to the P-score analysis (P-score = 0.992), followed by robot-assisted therapy (0.641), MI (0.240), and conventional rehabilitation (0.127). In direct comparisons, BCI-robot produced a statistically significant improvement in FMA-UE versus conventional rehabilitation (MD = 6.80, 95% CI 4.29 to 9.30). The point estimate exceeded the 5.25-point (minimal clinically important difference) MCID, although the lower confidence limit did not. Compared with robot-assisted therapy, BCI-robot showed a statistically significant but small improvement (MD = 2.04, 95% CI 0.29 to 3.78), with both the point estimate and the entire 95% CI remaining below the MCID. Follow-up-duration subgroup analyses suggested that BCI-robot remained favorable over conventional rehabilitation in both < 3-month and ≥ 3-month subgroups, whereas no significant follow-up advantage over robot-assisted therapy was observed. For secondary outcomes, BCI-robot significantly improved WMFT versus conventional rehabilitation (MD = 8.94, 95% CI 5.22 to 12.65) and MBI versus conventional rehabilitation (MD = 3.37, 95% CI 0.10 to 6.63). A significant benefit for MBI versus robot was also observed (MD = 8.61, 95% CI 1.76 to 15.46), although this result was not robust in sensitivity analysis. No significant advantage was found for ARAT. Exploratory subgroup analyses suggested that, compared with robot-assisted therapy, the additional benefit of BCI-robot was more apparent in studies delivering more than four sessions per week.

CONCLUSIONS: BCI-robot ranked highest for improving FMA-UE and may provide a clinically important benefit over conventional rehabilitation, although the magnitude remains uncertain. Its additional benefit over robot-assisted therapy was small and unlikely to be clinically important. Evidence for longer-term effects and for activity-level and daily-function outcomes remains limited, and the findings should be interpreted cautiously.},
}

Humans
*Stroke Rehabilitation/methods
*Robotics/methods
*Brain-Computer Interfaces
*Recovery of Function/physiology
*Upper Extremity/physiopathology
*Stroke/therapy/physiopathology/complications
*Imagery, Psychotherapy/methods
Treatment Outcome

@article {pmid42790484,
year = {2026},
author = {Mulder, MQ and Valdenegro-Toro, M and Sburlea, AI and de Jong, IP},
title = {The challenge of out-of-distribution detection in motor imagery BCIs.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/aeac87},
pmid = {42790484},
issn = {1741-2552},
abstract = {Objective Machine Learning classifiers used in Brain-Computer Interfaces make classifications based on the distribution of examples on which they were trained. When exposed to EEG from unfamiliar classes they can only make blind guesses. Instead of allowing such guesses, these Out-of-Distribution (OOD) samples should be detected and rejected to improve the robustness of BCIs against unfamiliar cognitive states. Approach We study OOD detection in Motor Imagery BCIs by training a model on some classes and observing whether an unfamiliar movement class can be detected based on increased uncertainty. We tested seven different OOD detection methods and one more method that has been claimed to boost the quality of OOD detection. Main results For many BCI users, the uncertainty for the familiar in-distribution classes can still be higher than for the out-of-distribution classes, due to the high intrinsic variability inherent in EEG signals. As a result, many OOD detection methods that have shown good performance in other machine learning domains prove to be ineffective at identifying unfamiliar motor imagery patterns in BCIs. However, we also found that OOD detection performance is correlated with on-task performance, and that Deep Ensemble models and MC-Dropout models were able to achieve on-task AUROC > 0.9, and OOD detection ability up to 0.7. This shows that for models and subjects where task performance is high, rejecting unfamiliar cognitive states becomes feasible. Significance Our research demonstrates a Leave-One-Class-Out OOD detection setup as an experimental paradigm for studying whether models are robust against unfamiliar motor imagery actions that were not seen in the training data. This is the first benchmark in Motor Imagery BCI that evaluates this type of OOD data. Our results demonstrate how to improve the overall safety and reliability of BCIs by preventing erroneous actions.},
}

@article {pmid42791544,
year = {2026},
author = {Darshana, N and Thuvarahan, I and Vancuylenberg, A and Perera, J},
title = {Validation and psychometric evaluation of the Diabetes Quality-of-Life Brief Clinical Inventory: Tamil version (DQoL-BCI-T).},
journal = {BMC health services research},
volume = {26},
number = {1},
pages = {},
pmid = {42791544},
issn = {1472-6963},
support = {Nil//Research and Development Centre, Link Natural products (Pvt) Limited, Sri Lanka/ ; },
mesh = {Humans ; Psychometrics ; *Quality of Life/psychology ; Female ; *Diabetes Mellitus, Type 2/psychology ; Cross-Sectional Studies ; Middle Aged ; Male ; Reproducibility of Results ; Sri Lanka ; Adult ; Surveys and Questionnaires/standards ; Aged ; Translations ; },
abstract = {BACKGROUND: Diabetes mellitus (DM) significantly impairs quality of life (QoL) through its chronic course, treatment burden, and complications. Disease-specific QoL tools provide more clinically relevant assessment than generic instruments. Although the Diabetes Quality of Life-Brief Clinical Inventory (DQOL-BCI) has been widely validated internationally, no validated Tamil version exists despite large Tamil-speaking populations affected by type 2 diabetes mellitus (T2DM). This study aimed to translate, culturally adapt, and validate a Tamil version of the DQOL-BCI (DQOL-BCI-T) among Tamil-speaking adults with T2DM in Sri Lanka.

METHODS: A cross-sectional validation study of DQOL-BCI-T was conducted among 165 native Tamil-speaking adults with T2DM attending an urban outpatient clinic in Colombo from May to October 2025). Translation followed a standardized forward-backward procedure with expert panel review and cognitive debriefing. Reliability was assessed using Cronbach's alpha. Construct validity was evaluated through convergent validity with the Tamil WHOQOL-BREF and discriminant validity across clinical variables. Factor structure was examined using principal component analysis with oblimin rotation.

RESULTS: The DQOL-BCI-T demonstrated acceptable internal consistency (Cronbach's α = 0.682) and stability over two weeks. Significant moderate negative correlations with WHOQOL-BREF total (r = - 0.559, p < 0.001) and domain scores supported convergent validity. Discriminant validity was demonstrated by significantly lower QoL among patients with microvascular complications (p = 0.040). Factor analysis showed satisfactory sampling adequacy (KMO = 0.729) and acceptable item loadings, explaining 72% of total variance.

CONCLUSIONS: The DQOL-BCI-T demonstrates satisfactory validity, reliability, and cultural appropriateness for measuring diabetes-specific quality of life among Tamil-speaking adults with T2DM. Its concise format and strong psychometric performance make it a practical tool for routine clinical assessment and research, supporting patient-centred diabetes care. Further validation across diverse clinical populations, socio-cultural contexts, and treatment regimens is warranted to confirm its broader applicability and generalisability.},
}

Humans
Psychometrics
*Quality of Life/psychology
Female
*Diabetes Mellitus, Type 2/psychology
Cross-Sectional Studies
Middle Aged
Male
Reproducibility of Results
Sri Lanka
Adult
Surveys and Questionnaires/standards
Aged
Translations

@article {pmid42779633,
year = {2026},
author = {Thurston, MJ and Bjånes, D and Wandelt, S and Pejsa, K and Lee, B and Liu, C and Andersen, RA},
title = {Neural encoding of grasp and object properties in the posterior parietal and motor cortices of the cortical grasping network in tetraplegic humans.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
doi = {10.64898/2026.09.10.750758},
pmid = {42779633},
issn = {2692-8205},
abstract = {The cortical grasping network (CGN) is responsible for the ability to physically interact with the world around us using our hands. For patients with motor impairments due to neurogenerative disease or traumatic injury, brain-machine interfaces (BMIs) offer a potential pathway towards restoration of dexterous hand control via recording neural activity throughout the CGN. However, grasping objects with robotic BMI devices has proved challenging, when utilizing neural signals from only motor cortex (MC, a subregion of the CGN). It is currently unclear how the presence of an object might compromise BMI performance; thus this work explores the interactive neural representation of grasp and objects throughout the CGN. Three tetraplegic human participants performed grasp motor imagery during imagined object manipulation while we recorded neural activity from the supramarginal gyrus (SMG), anterior intraparietal cortex (AIP), motor cortex (MC), and primary somatosensory cortex (S1). All regions within the CGN represented whole hand configuration of imagined grasps during motor planning and imaged execution. Additionally, grasp-related neural activity in each region was modulated by context (motor planning vs. imagined execution and object present vs. not present). SMG and AIP represented object shape during motor planning. PPC encoded both grasp and object properties simultaneously from mostly unique subpopulations of neurons. This separability in higher cortical regions could be a critical for stable BMI grasp performance.},
}

@article {pmid42780484,
year = {2026},
author = {Pang, R and Hu, Z and Luo, C and Liu, Z and Zhang, S},
title = {Comparative efficacy of virtual reality, robotics, and brain-computer interface interventions for upper limb rehabilitation after stroke: a systematic review and network meta-analysis.},
journal = {Frontiers in neurology},
volume = {17},
number = {},
pages = {1882841},
pmid = {42780484},
issn = {1664-2295},
mesh = {Humans ; *Stroke Rehabilitation/methods ; *Upper Extremity/physiopathology ; *Robotics ; *Brain-Computer Interfaces ; *Stroke/therapy ; *Virtual Reality ; },
abstract = {BACKGROUND: Stroke often leads to persistent upper-limb motor impairment, which significantly impairs quality of life. Conventional physical therapy (CPT) has limitations, including insufficient intensity, limited patient engagement, and inadequate feedback. Emerging technologies such as virtual reality (VR), robotics (ROT), and brain-computer interfaces (BCI) have shown promise; however, direct comparisons among these approaches are lacking, and their relative effectiveness remains unclear.

OBJECTIVE: This study aimed to systematically evaluate and compare the relative effectiveness of VR, robotics, and BCI on upper limb motor function, motor performance, and activities of daily living in stroke survivors using network meta-analysis.

METHODS: PRISMA-NMA guidelines were followed. PubMed, Web of Science, Cochrane Library, and Embase were searched from inception to October 2025 for RCTs. Two reviewers independently screened studies, extracted data, and assessed risk of bias using RoB 2.0. A Bayesian random-effects network meta-analysis (R package gemtc) was performed to estimate relative treatment effects and calculate SUCRA values, along with sensitivity and subgroup analyses.

RESULTS: 25 RCTs (1,145 stroke survivors) were included. The network evidence geometry was star-shaped, with conventional physical therapy (CPT) as the common comparator. For FMA-UE, ROT-RFE achieved the highest SUCRA ranking, although this estimate was based on a single study. ROT-CPT and ROT, supported by two and three studies respectively, provided more consistent evidence. For secondary outcomes, ROT-CPT ranked highest for MBI (SUCRA = 0.89), whereas VR-CPT ranked highest for WMFT (SUCRA = 0.59). Sensitivity analyses generally supported robustness, and subgroup analyses suggested patient characteristics may influence treatment effects.

CONCLUSION: For improving upper-limb motor function after stroke, robotics-based interventions were supported by stronger evidence than other modalities. Specifically, ROT (SUCRA = 0.71, 3 studies) and ROT-CPT (SUCRA = 0.70, 2 studies) demonstrated consistent and clinically meaningful improvements, representing more reliable options for clinical practice. While a single robotics variant (ROT-RFE, SUCRA = 0.91) achieved a numerically higher ranking, this estimate was based on one trial and should not be interpreted as definitive evidence of superiority. VR-based interventions showed modest benefits, whereas BCI-based interventions were supported by only one eligible study with extractable data and no reliable conclusions can be drawn.

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420251180631, identifier: CRD420251180631.},
}

Humans
*Stroke Rehabilitation/methods
*Upper Extremity/physiopathology
*Robotics
*Brain-Computer Interfaces
*Stroke/therapy
*Virtual Reality

@article {pmid42780863,
year = {2026},
author = {Zhang, W and Catherine Chan, KL and Zeng, H and Xu, B and Hu, H and Miao, M and Song, A and Shen, Y},
title = {Vibrotactile stimulation for upper-limb neurorehabilitation and sensorimotor training: a systematic review of clinical and mechanistic evidence.},
journal = {Frontiers in bioengineering and biotechnology},
volume = {14},
number = {},
pages = {1892452},
pmid = {42780863},
issn = {2296-4185},
abstract = {BACKGROUND: Vibrotactile stimulation (VTS) has emerged as a potential sensory-based adjunct to upper limb rehabilitation by providing additional afferent feedback and supporting sensorimotor rehabilitation. This systematic review aimed to synthesize clinical evidence on VTS for post-stroke upper-limb rehabilitation and complementary mechanistic and technological evidence from healthy participants, with emphasis on intervention characteristics, stimulation parameters, clinical outcomes, neurophysiological effects, usability and safety.

METHODS: This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and was retrospectively registered with the Open Science Framework. PubMed, PEDro, Web of Science and Google Scholar were searched for English-language full-text studies published between January 2015 and January 2026. Search terms included combinations of stroke, VTS, vibration, tactile, somatosensory, haptic, upper limb and hand.

RESULTS: A total of 35 studies were included. Fourteen studies used direct upper-limb stimulation, six integrated VTS with robotic systems, two with virtual reality (VR), two with mirror visual feedback (MVF), seven with brain-computer interface (BCI) paradigms, and four with multimodal systems. Stimulation sites included the wrist, hand, fingers, fingertips, forearm, and upper arm, whereas reported frequencies, intensities, timing, and doses varied widely. Clinical studies suggested potential improvements in upper-limb motor function, sensory and proprioceptive function, spasticity, and affected-limb use, particularly when VTS accompanied active or task-oriented training. Mechanistic studies indicated that VTS may modulate sensorimotor rhythms, cortical activation, functional connectivity, and motor-imagery (MI)-related brain responses.

CONCLUSION: Current evidence suggests that VTS may support upper-limb functional recovery after stroke. However, confidence in the evidence remains limited by small samples, heterogeneous protocols, and the frequent use of multimodal interventions that do not isolate the contribution of vibration. Further adequately powered randomized controlled trials are needed to determine clinical efficacy and to identify the stimulation parameters and feedback architectures most likely to benefit people after stroke.},
}

@article {pmid42780871,
year = {2026},
author = {Saha, T and Giri, P and Nag, R and Ganguly, D and Patel, N and Roy, A and Chaudhuri, S and Verma, K and Pal, A and Rina, K and Sarkar, S and Basu, A},
title = {fNIRS-based neurofeedback targeting the right dorsolateral prefrontal cortex (dlPFC) in children at familial risk for substance use disorder and/or severe mental illness: a proof-of-concept study from eastern India.},
journal = {Frontiers in human neuroscience},
volume = {20},
number = {},
pages = {1936277},
pmid = {42780871},
issn = {1662-5161},
abstract = {BACKGROUND: Children who have first-degree relatives diagnosed with substance use disorders and/or severe mental illnesses show altered prefrontal cortical development and an elevated risk of executive function impairment. fNIRS-based neurofeedback (NF) is a portable, child-tolerant technique for the modulation of cortical hemodynamics, with preliminary evidence of dlPFC-dependent cognitive benefits in adult populations. However, evidence evaluating its efficacy in pediatric at-risk cohorts from the Indian subcontinent is currently lacking.

METHODS: This single-arm, uncontrolled proof-of-concept study evaluated the feasibility and tolerability of an eight-session, fNIRS-based NF protocol targeting two right dlPFC channels (Ch10, Ch15) in 11 children (aged 6-12 years), recruited from an inpatient psychiatric unit and an addiction treatment facility. Real-time oxygenated hemoglobin (HbO) feedback was provided via Turbo-Satori BCI. Session-wise HbO amplitude and Ch10↔Ch15 functional connectivity (FC) were extracted for all 11 children. Participants completed pre- and postintervention assessments of executive function. Exploratory Spearman correlations examined the associations between dlPFC HbO modulation and pre-post behavioral changes.

RESULTS: All 11 children completed the protocol without adverse events. The ROI-averaged right dlPFC HbO amplitude showed a positive session-wise increase that did not reach conventional significance (β = 0.00003, t(950) = 1.90, p = 0.058). Individual channel slopes were positive but non-significant after FDR correction. Inter-channel FC increased from session 1 (r = 0.21) to session 4 (r = 0.41) before declining by session 8 (r = 0.18), with no significant linear trend. Behavioral measures showed numerically higher accuracy across tasks, and both the Raven's CPM and the Stroop task showed shorter reaction times postintervention, but none of the comparisons survived Bonferroni correction. A moderate-to-strong correlation was observed between right dlPFC HbO change and Stroop incongruent accuracy improvement, but it was non-significant (ρ = 0.679, p = 0.094), with no significant associations for the N-back or CPM outcomes.

CONCLUSION: This eight-session right dlPFC fNIRS-NF protocol in children with elevated familial risk was feasible and well tolerated. It showed a positive, but not statistically significant, increase in HbO amplitude. The connectivity between targeted channels and behavioral scores showed a positive correlation, but it was not statistically significant. A strong-to-medium correlation was observed between right dlPFC HbO change and Stroop incongruent accuracy scores. These findings provide preliminary effect-size estimates to inform the design of future sham-controlled trials in this underrepresented pediatric population.},
}

@article {pmid42780902,
year = {2026},
author = {Young, MJ and Sandbrink, JD and Cabrera, LY and Kampasi, K and Kennedy, P and Masood, M and Rubin, DB and Brielmaier, L and Ford, P},
title = {Unifying Consent Standards for Implantable Brain-Computer Interfaces.},
journal = {Device},
volume = {},
number = {},
pages = {},
pmid = {42780902},
issn = {2666-9986},
support = {F32 MH123001/MH/NIMH NIH HHS/United States ; K23 NS140495/NS/NINDS NIH HHS/United States ; },
abstract = {Implantable brain-computer interfaces (iBCIs) are approaching clinical deployment and can transform care for people with speech and motor impairment by restoring their ability in communication, movement, and aspects of agency. As a means of neurological intervention, iBCIs are not ethically or clinically analogous to current clinically established procedures or devices. They combine invasive neurosurgery, continuous neural data capture, adaptive machine-learning-based decoding, software dependence, and functionality that can change over time. These features create distinctive ethical, legal, clinical, and practical challenges that conventional informed consent frameworks do not adequately address. In this review and analysis, we present a framework and checklist to help guide more consistent and comprehensive informed consent for iBCIs to strengthen respect for autonomy, align stakeholder expectations, reduce fragmentation across sites, and support ethically robust translation of iBCIs into clinical practice.},
}

@article {pmid42781884,
year = {2026},
author = {Lian, M and Gao, X and Liang, K and Ji, Y},
title = {Nanoparticle Reinforcement of Poly(diol citrate)-Based Coacervate Adhesives.},
journal = {ACS applied bio materials},
volume = {},
number = {},
pages = {},
doi = {10.1021/acsabm.6c01521},
pmid = {42781884},
issn = {2576-6422},
abstract = {Tannic acid (TA)-based coacervate adhesives rely primarily on hydrogen-bonding interactions to maintain cohesion. However, these relatively weak hydrogen-bonds easily trigger cohesive failure in practical bonding applications, particularly under wet conditions. To address this limitation, a nanoparticle reinforcement strategy was employed in this study. A poly(diol citrate)-based coacervate adhesive (PN) was first synthesized via one-pot melt polycondensation of citric acid (CA), 1,8-octanediol (OD), and polyethylene glycol (PEG), followed by coupling with N-hydroxysuccinimide (NHS). Subsequently, TA-modified silica (TA-SiO2) and TA-modified chitin nanocrystals (TA-ChNC) were separately blended with PN and TA in aqueous solution to fabricate two types of nanocomposite coacervate adhesives, denoted as PNTS and PNTC, respectively. The results demonstrated that the cohesive strength, represented by peak stress, was significantly enhanced from 762.4 ± 94.1 kPa (pristine PNT) to 1266.1 ± 63.0 kPa (PNTS-3) and 2201.5 ± 187.6 kPa (PNTC-5), accompanied by a pronounced improvement in lap-shear adhesion strength: for the gel-type adhesives, from 36.6 ± 9.4 kPa (pristine PNT) to 56.4 ± 4.5 kPa (PNTS-3) and 74.4 ± 13.4 kPa (PNTC-3); for powder-type adhesives, from 27.1 ± 5.2 kPa (pristine PNT) to 36.3 ± 7.5 kPa (PNTS-3) and 73.3 ± 8.0 kPa (PNTC-3). Notably, TA-ChNC showed superior reinforcing effects in both gel and powder forms. Furthermore, the nanocomposite adhesives exhibited favorable cytocompatibility and antibacterial activity. Specifically, the PNTC adhesive achieved a hemolysis rate below 5%, together with shortened blood coagulation time and a low blood clotting index (BCI). In summary, the nanoparticle composite strategy effectively improved the overall performance of the coacervate adhesives.},
}

@article {pmid42782640,
year = {2026},
author = {Luo, J and Yu, J and Cao, H and Tan, Q and Chen, J and Xiao, J},
title = {A Few-Channel Brain-Computer Interface System Based on a Heuristic Algorithm.},
journal = {Biomimetics (Basel, Switzerland)},
volume = {11},
number = {9},
pages = {},
pmid = {42782640},
issn = {2313-7673},
abstract = {Traditional P300 brain-computer interface (BCI) systems rely on multi-channel EEG acquisition, causing cumbersome setup, lengthy preparation, and high user workloads, which limits their real-world application. To enhance practicality, this paper proposes a fixed few-channel selection framework based on a heuristic algorithm to balance decoding performance and user experience. We integrated a genetic algorithm (GA) with Bayesian linear discriminant analysis (BLDA) to identify a strongly generalizable few-channel combination from a traditional eight-channel system, avoiding costly subject-specific recalibration. Validating this method, 48 healthy subjects completed rigorous offline and online virtual reality (VR) experiments. Results showed that the proposed three-channel system maintained highly comparable accuracy and information transfer rates to the eight-channel system, showing no significant performance degradation. Crucially, the few-channel scheme reduced equipment preparation time by 90% (from 30 to 3 min). Furthermore, NASA-TLX workload evaluations confirmed a significant reduction in users' psychological and physical burdens (p < 0.05). Ultimately, while preserving core interaction performance, this few-channel strategy vastly improves user experience and system practicality, offering key theoretical and practical support for implementing lightweight, user-friendly BCI systems.},
}

@article {pmid42599846,
year = {2026},
author = {Chen, D and Gomzyakova, E and Gu, Y and Zhang, Y and Hofmann, SG and Liu, X},
title = {Effectiveness and Cost-Effectiveness of a Digital Mindfulness-Based Intervention for Psychological Distress Delivered by Trainee Instructors: A Randomized Controlled Trial.},
journal = {Psychotherapy and psychosomatics},
volume = {},
number = {},
pages = {1-19},
doi = {10.1159/000553463},
pmid = {42599846},
issn = {1423-0348},
abstract = {INTRODUCTION: The high prevalence of psychological distress and shortage of mental health professionals create a service gap for highly symptomatic populations exceeding routine care capacity. We evaluated a hybrid digital mindfulness intervention (MIED) delivered via a train-the-trainer (TTT) model for reducing psychological distress and providing economic value.

METHODS: In this randomized controlled trial in China, adults with significant psychological distress (Kessler-10 score ≥22) were assigned (1:1) to 8-week MIED plus services as usual (SAU), or SAU alone. The primary outcome was the 8-week trajectory of psychological distress. Secondary outcomes included mental health indicators and short-term cost-utility. Intention-to-treat analyses used generalized estimating equations (GEEs).

RESULTS: Between November 1 and 8, 2024, 1,281 participants were assigned (MIED: n = 641; SAU: n = 640). GEE revealed a significant Group × Time interaction for distress (χ2 (4) = 143.611, p < 0.001), with the intervention group demonstrating greater reductions than SAU (Cohen's d = -0.526 at Week 8). Secondary indicators also improved (p < 0.001). From a societal perspective, MIED incurred lower mean costs (993 CNY [∼USD 140] vs. 1,326 CNY [∼USD 186]; p < 0.001) with 95% probability of cost-effectiveness at 9,246 CNY [∼USD 1,299] per quality-adjusted life-year. Adherence was high (mean, 6.04 of 8 sessions). No severe adverse events were identified, and self-reported meditation-related adverse experiences declined over time within the intervention group.

CONCLUSIONS: Compared with SAU, TTT-delivered MIED is a safe, effective, and potentially cost-saving adjunct strategy for scaling MIED delivery in resource-constrained systems. Future research should evaluate long-term sustainability beyond 8 weeks.},
}

@article {pmid42773469,
year = {2026},
author = {Richter, F},
title = {The foundational role of autonomy for brain-computer interfaces.},
journal = {Philosophy, ethics, and humanities in medicine : PEHM},
volume = {21},
number = {1},
pages = {},
pmid = {42773469},
issn = {1747-5341},
mesh = {*Brain-Computer Interfaces/ethics ; Humans ; *Personal Autonomy ; Sense of Agency ; },
abstract = {Invasive brain-computer interfaces (BCIs) pose a challenge for describing human-system interactions because they involve a depth of engagement that is difficult to disentangle. This is particularly problematic when clear authorship of decisions is needed. This presupposes that such devices might also decide autonomously in certain situations. Although the use and implementation of such devices are highly disputed in practical ethics, they seem to offer at least therapeutic benefits for persons with, e.g., Parkinson's disease. That is why it is indispensable to develop a conceptual framework that allows a description of the system's interactions with the human agent. The effects of brain-computer interfaces on patients are assessed empirically in studies and hypothesized on a more speculative level via thought experiments. A model to operationalize dimensions of agency, such as responsibility and privacy, has been proposed. Nevertheless, this model is inchoate if it is not related to autonomy, because it is widely assumed that autonomy is not only a characteristic of the human agent but also of the technological system (at least to a certain degree). Consequently, a more complete model is needed that classifies autonomy at different levels (operational, strategic, and moral). Technological systems can only operate on the first two levels because their behavior is based on dispositions within the scope of alethic modality, whilst human agency is based on deontic structures that are expressed via normative attitudes and statuses that cannot be reduced to alethic modality. This crucial difference can be used to develop methods for evaluating the ethical side of BCIs.},
}

*Brain-Computer Interfaces/ethics
Humans
*Personal Autonomy
Sense of Agency

@article {pmid42773498,
year = {2026},
author = {Huang, Y and Li, M and Shang, Z and Yang, L},
title = {Duration-aware unsupervised segmentation reveals collective movement modes in homing flights of pigeon flocks.},
journal = {Movement ecology},
volume = {14},
number = {1},
pages = {},
pmid = {42773498},
issn = {2051-3933},
abstract = {BACKGROUND: Homing flights of pigeon flocks require rapid adjustments in individual behaviour while maintaining group cohesion. However, how heading adjustments and coordinated movement changes are temporally organised during continuous flight, and whether they form repeatable collective movement modes, remain poorly characterised.

METHODS: During homing flights of domestic pigeon (Columba livia) flocks, we synchronously recorded individual GPS trajectories and inertial measurement data. After standardised preprocessing, candidate flock-level kinematic features were constructed to characterise flock movement changes across six aspects: flock-level turning intensity, acceleration intensity, turning consistency, acceleration consistency, turning directionality and acceleration directionality. After comparing candidate input schemes, four flock-level kinematic indicators were selected as model inputs. A hidden semi-Markov model with an explicit duration structure was then used to perform unsupervised segmentation of continuous homing flights.

RESULTS: We identified five collective movement modes that were comparable across flight trials. In addition to steady cruising, coordinated counterclockwise turning and coordinated clockwise turning, two modes were identified that were difficult to distinguish from flock trajectory geometry alone. The first was rapid collective reorientation, which showed the highest flock-level turning intensity, acceleration intensity and turning consistency, but whose turning directionality was not fixed to a single clockwise or counterclockwise direction. The second was a transition mode that connected different movement modes during mode switching. All five modes recurred during homing flights, with overall occupancies of 10.5%-26.7%, median durations of 0.60-1.03 s, and approximately 90% of mode segments ending within 2 s. Transitions among modes were concentrated in a small number of source-mode-specific high-probability pathways, indicating a non-uniform transition structure during homing flights.

CONCLUSIONS: Homing flights of pigeon flocks contain a recurrent set of second-scale collective movement modes rather than a simple "straight flight-turning" dichotomy. An unsupervised segmentation framework based on flock-level kinematic indicators and explicit duration modelling can identify these short-timescale modes at the level of flock kinematics and characterise their transition structure, providing a comparable temporal reference for future analyses of spatial organisation, information transfer and leader-follower relationships across different modes.},
}

@article {pmid42774502,
year = {2026},
author = {Yan, T and Zhang, A and Yang, Z and Su, H and Ma, Y and Wu, Y and Yan, L and Wang, Y and Guo, F and Cao, J},
title = {A novel motor imagery brain-computer interface classification framework based on augmented covariance matrix: deep Riemannian geometry learning with self-attention mechanism.},
journal = {Cognitive neurodynamics},
volume = {20},
number = {1},
pages = {180},
pmid = {42774502},
issn = {1871-4080},
abstract = {The rapid development of motor imagery brain-computer interface (MI-BCI) technology has introduced a novel mode of human-machine interaction, drawing significant interest. However, due to the nonlinearity and nonstationarity of motor imagery signals, this communication method faces challenges such as low recognition accuracy and poor stability, which severely hinder the practical application of MI-BCIs. Riemannian geometry techniques, leveraging their non-Euclidean properties, have shown promise in addressing motor imagery signal pattern recognition. Traditional Riemannian geometry methods, however, still suffer from limitations, such as requiring manual feature extraction and resulting in suboptimal classification performance. This paper proposes Aug-SPD-AttentionNet, a deep Riemannian geometry learning framework for MI-BCI classification that combines lagged augmented covariance representations, a learnable high-dimensional embedding layer, and self-attention operations defined on the SPD manifold. The proposed framework employs multiple deep Riemannian learning blocks to extract manifold-aware features and uses a Riemannian self-attention mechanism to capture long-range dependencies among different SPD representations. Aug-SPD-AttentionNet was evaluated on BCI Competition III Dataset IVa, BCI Competition IV Dataset I, and BCI Competition IV Dataset 2a, achieving mean classification accuracies of [Formula: see text], [Formula: see text], and [Formula: see text], respectively. Ablation experiments further demonstrate that the proposed components collectively improve classification performance, increasing the mean accuracy across the three evaluated subjects from 70.60 to 82.62%, corresponding to a 12.03-percentage-point improvement over the baseline SPDNet.},
}

@article {pmid42775222,
year = {2026},
author = {Wang, L and Zhou, Y and Wang, P and Ma, X and Zhou, S},
title = {Cross-variability decoding for motor imagery EEG signals: a comprehensive review.},
journal = {Frontiers in neuroscience},
volume = {20},
number = {},
pages = {1899645},
pmid = {42775222},
issn = {1662-4548},
abstract = {Motor Imagery-based (MI) Electroencephalography (EEG) has emerged as a leading solution in non-invasive Brain-Computer Interface (BCI) systems, leveraging its strong motor intention correlation to enable reliable neural decoding. However, practical implementation of MI confronts three persistent challenges: low signal-to-noise ratio, substantial variability across subjects or over time, and inherent signal nonstationarity. These fundamental limitations continue to hinder the widespread adoption and operational reliability of MI BCI systems. Despite advances in cross-variability decoding methods, there is a lack of systematic syntheses to guide technological evolution in MI BCI. To address these challenges, this review presents a comprehensive taxonomy of MI EEG cross-variability decoding studies from 2020 to 2025, systematically organizing advances in deep learning and transfer learning. We critically evaluate core algorithmic approaches, including Convolutional Neural Networks (CNN), transformers, feature alignment, domain adaptation, and meta-learning. We then explore the underlying mechanisms of these methods and assess their efficacy across key variability paradigms (mainly cross-subject and cross-session scenarios). Finally, we summarize key findings, highlight unresolved challenges, and outline promising future research directions. These advancements hold significant potential to bridge the gap between laboratory-based MI and real-world clinical and consumer applications.},
}

@article {pmid42776881,
year = {2026},
author = {Li, A and Wang, Z and Liu, H and Xu, T and Zhou, T and Van Hulle, MM and Hu, H},
title = {A Co-adaptive Few-shot Calibration Method for Improving Motor Imagery BCI Performance.},
journal = {IEEE journal of biomedical and health informatics},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/JBHI.2026.3735157},
pmid = {42776881},
issn = {2168-2208},
abstract = {Motor Imagery Brain-computer Interfaces connect the human brain with external devices by imagining muscular activity, serving as one of the promising solutions for human-computer interaction. It has been successfully applied by paralyzed individuals to control assistive devices, prosthetics and exoskeletons, and several dedicated applications. However, about half of potential users exhibit MI illiteracy, which hinders its adoption in real-world settings. Calibration has been demonstrated as an effective approach to enhancing MI capabilities. Nevertheless, existing calibration methods face two critical challenges: 1) the lack of systematic protocols to guide subjects in refining their MI skills based on the outcome of the intended actions, and 2) the use of fixed, cross-subject classifiers that do not address inter-subject MI variability. This study proposes the Co-adaptive Few-shot calibration (CFC) approach. It particularly addresses the above two challenges: 1) it introduces MI pattern selection to provide a subject-specific assessment protocol, and 2) it incorporates meta-learning in the calibration stage to address inter-subject and inter-pattern variability and reduce calibration time. We carried out an experiment on 30 subjects to verify the effectiveness of CFC. The results show that after a short calibration, the subject's MI capabilities were significantly improved, with the average binary motor imagery accuracy improved from 69.50% to 77.47% (+ 7.97%) on the experiment group with 10 naive subjects. The CFC approach can help subjects find the optimal MI pattern to enhance their MI ability in a short time. This method broadens the practical usability of MI-BCI systems, making them accessible to a wider population of users.},
}

@article {pmid42777027,
year = {2026},
author = {Lin, X and Liu, H and Lin, K and Chen, J and Huang, Y and Song, J},
title = {Fine-grained multi-level gesture recognition based on a stretchable multichannel ultrasonic device.},
journal = {Science advances},
volume = {12},
number = {39},
pages = {eaef1101},
pmid = {42777027},
issn = {2375-2548},
mesh = {*Gestures ; Humans ; *Pattern Recognition, Automated/methods ; Convolutional Neural Networks ; },
abstract = {Discrete gesture recognition provides a direct output form for command-based human-machine interaction, while fine-grained multi-level recognition can expand command capacity by mapping subtle graded finger movements to distinct commands or different levels of the same command, thereby reducing the need for large or repetitive hand gestures. However, reliably distinguishing fine-grained multi-level gestures remains challenging. Here, we present a stretchable multichannel ultrasonic device comprising four functional sites and sixteen piezoelectric modules. Its fan-shaped substrate stretches up to 30%, enabling conformal forearm attachment and alignment with target muscle regions. Experimental characterization demonstrated sub-millimeter spatial resolution and excellent signal quality. Integrated with a one-dimensional convolutional neural network, the system achieved up to 98.75% accuracy in recognizing metacarpophalangeal joint-angle changes below 5°. The multichannel configuration yields high classification accuracy, improved class-wise recognition balance, more effective learning from multi-subject data and enhanced calibration-assisted adaptation to shifted device positions and new users, providing a reliable strategy for low-burden, fine-grained multi-level gesture command control.},
}

*Gestures
Humans
*Pattern Recognition, Automated/methods
Convolutional Neural Networks

@article {pmid42777772,
year = {2026},
author = {Carrillo, D and Fortich, M and Serrano, JI and Del Castillo-Sobrino, MD},
title = {The effect of different observation modalities in motor imagery: Immersive virtual reality produces stronger desynchronization than video and real-world presentations.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/aeabf4},
pmid = {42777772},
issn = {1741-2552},
abstract = {OBJECTIVE: The combination of action observation and motor imagery (AO+MI) has emerged as a promising neurorehabilitation strategy to promote sensorimotor plasticity without real movement, making it particularly valuable for individuals whose motor capacity is limited or absent. Improving AO+MI protocols requires understanding whether different observation stimuli engage the sensorimotor system to varying degrees, as the quality of cortical activation during each training trial may directly influence cumulative neuroplastic outcomes. The present study aimed to determine how the observation modality influences the activation of the sensorimotor cortex during synchronous AO+MI.

APPROACH: Here, we investigated the effects of three observation modalities: immersive virtual reality (iVR), two-dimensional video and real-world observation of a robotic agent, on sensorimotor cortical engagement, using Event-Related Desynchronization (ERD) as a neurophysiological marker. Electroencephalographic (EEG) signals were recorded from fifteen healthy participants across three sessions, one per modality, while they observed a humanoid robot performing arm elevation movements and simultaneously engaged in motor imagery of the same movements. ERD was computed for alpha and beta frequency bands over eight electrodes covering frontocentral, central, and centroparietal regions.

MAIN RESULTS: Statistical analyses revealed significant modality-dependent differences in sensorimotor cortical engagement across multiple frequency bands, electrode locations, and movement types. Immersive virtual reality consistently elicited the strongest desynchronization, with robust effects in the beta band over frontocentral and right centroparietal regions, and in the alpha band over the right central motor cortex.

SIGNIFICANCE: These results demonstrate that the modality of action observation significantly shapes sensorimotor cortical engagement during AO+MI. Our findings also support the integration of immersive virtual reality as a neurophysiological grounded tool for optimizing AO+MI-based neurorehabilitation protocols and brain-computer interface applications.},
}

@article {pmid42777778,
year = {2026},
author = {Du, K and Chang, W and Kong, W and Huang, H and Yan, G and Sadiq, MT},
title = {A hierarchical graph learning framework for VR-based motor imagery decoding driven by MVMD and feature optimization.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/aeabf5},
pmid = {42777778},
issn = {1741-2552},
abstract = {OBJECTIVE: While virtual reality (VR) combined with action observation (AO) provides enriched visual guidance for motor imagery (MI), the decoding stability of MI Brain-Computer Interface (BCI) remains a challenge due to the inherent non-stationarity and low signal-to-noise ratio of Electroencephalography (EEG) signals in dynamic environments. Enhancing decoding accuracy and understanding neural representations in VR-based AO+MI tasks remain important challenges in neural engineering.

APPROACH: This study proposes a hierarchical graph learning framework tailored for VR-based MI decoding, leveraging multivariate variational mode decomposition (MVMD) to decouple complex EEG signals into rhythmic components for enhanced multi-domain feature analysis, hybrid feature selection for compact representation, and functional brain network modeling based on phase locking value. Each EEG trial is represented as a sparsified graph, and a hierarchical graph convolutional network is designed to capture multi-scale spatial dependencies and high-order interactions for classification.

MAIN RESULTS: Experimental evaluations on a lab-acquired VR-MI dataset demonstrate that the proposed framework achieves competitive three-class decoding accuracy. This performance surpasses baseline models such as EEGNet, as observed under VR-based motor imagery conditions. In addition to enhanced decoding performance, the study enables neurophysiological interpretation by characterizing VR-induced modulations in brain network organization.

SIGNIFICANCE: VR-based AO+MI paradigm is found to enhance sensorimotor connectivity and promote large-scale network integration, indicating more coordinated neural dynamics during MI tasks. These findings suggest that the proposed framework effectively improves VR-based AO+MI decoding while providing interpretable insights into neural mechanisms, supporting its potential for advanced BCI applications.},
}

@article {pmid42777852,
year = {2026},
author = {Zhang, C and Xu, S},
title = {Dissociable prefrontal dynamics and evidence accumulation in experiential versus material value-based decisions: insights from fNIRS and computational modeling.},
journal = {NeuroImage},
volume = {},
number = {},
pages = {122256},
doi = {10.1016/j.neuroimage.2026.122256},
pmid = {42777852},
issn = {1095-9572},
abstract = {Value-based decisions often require the integration of information that is not directly observable but internally constructed from memory, simulation, and affective processes. Although previous research has extensively examined valuation for options with explicit attributes, less is known about how such internally generated information influences the dynamics of evidence accumulation and its neural implementation. In this study, we integrated functional near-infrared spectroscopy (fNIRS) with Hierarchical Drift Diffusion Modeling (HDDM) to examine decision processes in experiential versus material contexts, which differ in their reliance on internally constructed versus externally specified value information. Behaviorally, experiential choices were associated with higher willingness to upgrade and reduced sensitivity to price. Computationally, HDDM revealed that this preference was driven by a drift bias toward upgrading, while decision thresholds remained stable. At the neural level, fNIRS showed increased activation in a prefrontal network including the frontopolar cortex (FPC), inferior frontal gyrus (IFG), and dorsolateral prefrontal cortex (dlPFC) during experiential evaluation. Dynamic causal modeling (DCM) further indicated condition-dependent modulation of intrinsic connectivity within dorsolateral prefrontal cortex, characterized by reduced self-inhibitory coupling. Together, these findings suggest that differences in value construction are associated with systematic variation in the efficiency of evidence accumulation and with corresponding changes in prefrontal functional dynamics. The observed links between drift rate, prefrontal dynamics, and individual differences in subjective effort and evaluation strategies provide a coherent bridge between computational mechanisms and their neural substrates, offering a network-level account of how internally generated information is integrated during value-based decision-making.},
}

@article {pmid42778036,
year = {2026},
author = {Sun, X and Fang, T and Wang, H and Liu, C and Wang, X and Wang, G and Chen, Y and Fan, Q and Xia, S and Chai, C},
title = {Multiscale signatures of cortical hierarchical alterations and dialysis-associated preservation in end-stage renal disease.},
journal = {Progress in neuro-psychopharmacology & biological psychiatry},
volume = {},
number = {},
pages = {111945},
doi = {10.1016/j.pnpbp.2026.111945},
pmid = {42778036},
issn = {1878-4216},
abstract = {End-stage renal disease (ESRD) is a chronic condition associated with prominent cognitive deficits, potentially arising from disruptions in the brain's hierarchical organization. However, the underlying neurobiological mechanisms, as well as the extent to which hemodialysis-an effective treatment for ESRD-is associated with cognitive outcomes, remain unclear. In this study, we collected resting-state functional MRI data from 51 healthy controls, 54 hemodialysis-dependent ESRD patients (HD-ESRD), and 25 non-hemodialysis ESRD patients (NHD-ESRD). Functional connectivity gradients were derived and compared across groups to characterize cortical reorganization. We further integrated spatial transcriptomic data to identify molecular correlates of gradient alterations and conducted gene enrichment, neurotransmitter receptor density, and NeuroSynth-based cognitive mapping analyses to investigate multiscale mechanisms associated with ESRD-related functional reorganization. We found that ESRD patients exhibited a marked compression of cortical hierarchy, particularly within the default mode and sensorimotor networks. Compared with non-hemodialysis ESRD patients, the hemodialysis-dependent ESRD group demonstrated relative preservation of gradient organization, with longer dialysis duration and better cognitive performance associated with improved secondary gradient expression in the default mode network. Transcriptomic analyses revealed enrichment of genes related to synaptic signaling, calcium ion transport, and neuronal projection processes, predominantly expressed in excitatory, inhibitory, and astrocytic cells. Neurotransmitter and NeuroSynth decoding linked gradient alterations to distribution of serotonergic, noradrenergic, and opioid systems, aligning with cognitive domains spanning sensory processing, attention, and higher-order cognition. These findings suggest that ESRD-related alterations in cortical hierarchy are associated with molecular, neurochemical, and cognitive signatures, while the relative preservation observed in HD-ESRD patients may reflect dialysis-associated sparing.},
}

@article {pmid42778046,
year = {2026},
author = {Fu, B and Gu, W and Li, F and Fang, X and Li, J},
title = {NPD-RSVP: A novel BCI paradigm and decoding method for target recognition.},
journal = {Neuroscience},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.neuroscience.2026.09.009},
pmid = {42778046},
issn = {1873-7544},
abstract = {Rapid serial visual presentation (RSVP) based brain-computer interfaces (BCIs) can detect and recognize target and non-target objects. In this study, we proposed a novel dual-RSVP paradigm known as negative photographic dual-RSVP (NPD), in which one sequence contains the original target images and the other comprises the corresponding negative photographic images. Compared to the conventional RSVP, the proposed method can provide complementary information about target-related brain signals and efficiently avoid repetition blindness (RB). Based on this paradigm, we further proposed a novel electroencephalography (EEG) decoding method, known as cross-frequency decoupling model (CFDM). To model the periodic temporal changes, we first transformed the one-dimensional data vector of each EEG channel into a two-dimensional data matrix by adopting a period corresponding to the dominant neural oscillation components. To extract more discriminative features, we input two target feature maps into different channels and extracted the spatio-temporal dynamics of different brain regions using depth-wise spatio-temporal convolution kernels of different scales. Experiments were conducted on an expanded dataset of 20 subjects using a rigorous 8:2 train-test split to evaluate the performance of the proposed paradigm. The experimental results show that the proposed method achieved a mean classification accuracy of 94.24% and a True Positive Rate (TPR) of 90.62%. These results jointly demonstrate the effectiveness and advantages of the proposed NPD paradigm and the CFDM model for solving the dual-RSVP recognition problem.},
}

@article {pmid42779390,
year = {2026},
author = {Han, J and Jiang, H},
title = {[Historical development, frontiers of exploration, and disciplinary horizons of acupuncture research].},
journal = {Zhen ci yan jiu = Acupuncture research},
volume = {51},
number = {9},
pages = {1113-1118},
doi = {10.13702/j.1000-0607.20260816},
pmid = {42779390},
issn = {1000-0607},
mesh = {Humans ; *Acupuncture Therapy/history/trends ; History, 20th Century ; History, 21st Century ; *Acupuncture/history/trends ; China ; *Biomedical Research/history/trends ; },
abstract = {On the occasion of the 50[th] anniversary of the founding of Acupuncture Research, this paper systematically reviews the milestone value of the journal in promoting the scientification, standardization, and internationalization of acupuncture-moxibustion medicine. Integrating the core research achievements of the authors' team over the past sixty-odd years-particularly the classic literature published in Acupuncture Research over the last half-century-this article deeply analyzes the development characteristics of modern acupuncture research in its transition from "empirical verification" to "mechanism-driven" science. Furthermore, it elucidates four core pathways for the high-quality development of the acupuncture research field： first, emphasizing the neurochemical principles of acupuncture analgesia to drive theoretical and technological innovation through heritage preservation； second, harnessing translational medicine as a developmental catalyst to integrate basic medicine and clinical medicine； third, spearheading the evolution of the "Clinical+X" paradigm via brain-computer interfaces； and fourth, prioritizing the standardization and internationalization of acupuncture research, while strengthening the building of multidisciplinary talent teams to enhance China's voice and leadership in the field of global acupuncture governance. Ultimately, this work provides a robust theoretical foundation and forward-looking horizons for constructing a modern acupuncture medical system with Chinese characteristics and advancing the cause of global health.},
}

Humans
*Acupuncture Therapy/history/trends
History, 20th Century
History, 21st Century
*Acupuncture/history/trends
China
*Biomedical Research/history/trends

@article {pmid42764074,
year = {2026},
author = {Qin, Y and Zhang, L and Liu, Y and Yu, J and Li, Y and Yuan, Y},
title = {A Neural Network with Multi-Type Attention for Enhancing Motor Imagery EEG Decoding.},
journal = {Behavioural brain research},
volume = {},
number = {},
pages = {116482},
doi = {10.1016/j.bbr.2026.116482},
pmid = {42764074},
issn = {1872-7549},
abstract = {Despite the widespread adoption of deep learning techniques in motor imagery (MI) electroencephalogram (EEG) decoding, the limited decoding performance persists due to the low signal-to-noise ratio of EEG signals and insufficient exploration of MI-related information from temporal, frequency and spatial domains. Therefore, this paper proposed a novel end-to-end neural network with multi-type attention (MTANet) to extract the spatiotemporal-frequency coupling features in MI EEG and enhance MI EEG decoding. In MTANet, the EEG inception attention module was established to efficiently extract and weight temporal-frequency-spatial features inherent in EEG signals and the parallel temporal sequence attention module was introduced to enhance feature representation through parallel temporal convolutional networks, each processing weighted segments of different feature sequences. The proposed MTANet model achieved average accuracies of 83.39% (±0.09), 89.47% (±0.08) and 77.06% (±0.12) on the BCI Competition IV datasets IIa and IIb, and the BCI Competition III dataset IIIa, respectively, outperforming seven state-of-art models. The experimental results demonstrated that the MTANet model, empowered by the EEG inception attention and parallel temporal sequence attention modules, effectively improved the accuracy and stability of MI decoding.},
}

@article {pmid42765286,
year = {2026},
author = {Brizio, MV and Duran, F and Cabezas-Cartes, F and Avila, LJ and Boretto, JM},
title = {Do anthropogenic disturbances affect the stress physiology and immunity of Liolaemus cuyumhue? The case of an endangered lizard from the Monte Desert of Patagonia.},
journal = {Biology open},
volume = {},
number = {},
pages = {},
doi = {10.1242/bio.062777},
pmid = {42765286},
issn = {2046-6390},
support = {38373-2//Rufford Foundation/ ; 220520673//Mohammed bin Zayed Species Conservation Fund/ ; PICT2020-03395//Fondo para la Investigacion Cientifica y Tecnologica/ ; 04/B234//Universidad Nacional del Comahue/ ; 04/B285//Universidad Nacional del Comahue/ ; },
abstract = {In arid environments, hydrocarbon exploitation causes habitat alterations, affecting the availability of microhabitats for thermoregulation, predator evasion, and foraging opportunities. This is the first study to evaluate the effects of this anthropogenic disturbance on stress and immunological parameters in a liolaemid lizard, Liolaemus cuyumhue, an endemic and Critically Endangered species (Monte Desert, Patagonia, Argentina). During the spring-summer seasons, we compared the leucocyte profiles, heterophil-to-lymphocyte ratio (H/L), capture body temperatures (Tb), serum corticosterone concentrations (CORT), and body condition index (BCI) of adults from a site disturbed by hydrocarbon exploitation and an undisturbed site. We found that lymphocyte percentages were higher in lizards from the disturbed site, whereas heterophils, basophils, and monocytes were more abundant at the undisturbed site. The H/L differed significantly between sites and seasons, being higher at the undisturbed site and during spring. A significant negative association between H/L ratio and Tb was observed only at the disturbed site. CORT measured in adult males varied seasonally, being higher in summer, but showed no differences between sites. Our results suggest that individuals that survived and persisted in the disturbed site have been able to cope with environmental conditions, which at present do not appear to induce chronic physiological stress.},
}

@article {pmid42766735,
year = {2026},
author = {Gusman, JT and Beckman, ZC and Singer-Clark, TS and Paulk, AC and Kapitonava, A and Hosman, T and Allcroft, S and Acosta, AJ and Nicolas, C and Rubin, DB and Donoghue, JP and Vargas-Irwin, CE and Hochberg, LR},
title = {Observation-related activity in the human motor cortex increases with effector anthropomorphicity.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {123},
number = {39},
pages = {e2537457123},
doi = {10.1073/pnas.2537457123},
pmid = {42766735},
issn = {1091-6490},
support = {19CSLOI34780000//American Heart Association (AHA)/ ; N2864C A2295R A4820R//VA | Office of Research and Development (ORD)/ ; UH2NS095548//HHS | NIH | National Institute of Neurological Disorders and Stroke (NINDS)/ ; U01DC017844//HHS | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; N/A//Movement Disorder Foundation/ ; N/A//ALS Association (ALSA)/ ; N/A//Cerebral Palsy Alliance Research Foundation (CPA)/ ; },
mesh = {Humans ; *Motor Cortex/physiology ; Brain-Computer Interfaces ; Female ; Male ; Adult ; Movement/physiology ; Hand/physiology ; Neurons/physiology ; Hand Strength/physiology ; },
abstract = {Neurons in the motor cortex can be engaged not only in motor execution but also during observation of movements performed by other anthropomorphic agents (i.e., humans or monkeys). However, it is unknown how motor cortical neurons respond during observation of the range of assistive or prosthetic devices controlled by people using intracortical brain-computer interfaces (iBCIs). We recorded single-unit activity in the precentral gyrus while iBCI users viewed grasp-like movements performed by a spectrum of virtual effectors that included human, robotic, and hand-like dot stimuli. We found a relationship between neural modulation and effector anthropomorphicity (i.e., human-likeness) that existed on an ensemble-wide and individual-neuron level, suggesting that human motor cortex activity incrementally increases in response to the visually observed agent's human-likeness. Both solicited and spontaneous feedback from the participant indicated a relationship between neural activity and subjective assessments of anthropomorphicity, revealing a powerful contribution of context on observation-induced activity in the motor cortex. The activity of the motor cortex remained similar during attempted hand movements while different effectors were being observed, suggesting that intuitive external device control via iBCIs may not be overtly affected by the anthropomorphicity of the effector.},
}

Humans
*Motor Cortex/physiology
Brain-Computer Interfaces
Female
Male
Adult
Movement/physiology
Hand/physiology
Neurons/physiology
Hand Strength/physiology

@article {pmid42768143,
year = {2026},
author = {Li, N and Chen, S and Wang, J and Li, T},
title = {Exploring the shared genetic architecture and causal relationship between childhood maltreatment and psychiatric disorders.},
journal = {Molecular psychiatry},
volume = {},
number = {},
pages = {},
pmid = {42768143},
issn = {1476-5578},
support = {20241203A14//Hangzhou Science and Technology Bureau/ ; },
abstract = {Childhood maltreatment (CM) is a major risk factor for psychiatric disorders, yet the shared genetic etiology, potential causal effects, and mediating pathways underlying these associations remain incompletely understood. We investigated the shared genetic architecture, potential causal relationships, and candidate mediating pathways linking genetically proxied reported CM with major psychiatric disorders. Summary statistics were obtained from large-scale genome-wide association studies of CM and 10 psychiatric disorders. Genetic correlations were estimated using linkage disequilibrium score regression and genetic covariance analysis. Shared loci were identified using pleiotropy analysis under the composite null hypothesis. Causal effects and mediation pathways were evaluated using two-sample and two-step Mendelian randomization analyses. CM showed significant positive genetic correlations with 10 psychiatric disorders, with the strongest association observed for post-traumatic stress disorder (rg = 0.71). Mendelian randomization supported potential effects of CM on increased risk for major depressive disorder (OR = 1.61), bipolar disorder (OR = 1.70), schizophrenia (OR = 2.33), attention-deficit/hyperactivity disorder (OR = 2.40), obsessive-compulsive disorder (OR = 1.76), and post-traumatic stress disorder (OR = 1.24). Pleiotropy analysis identified 4113 shared single nucleotide polymorphisms mapped to 167 unique genes. Multi-omics integration prioritized 12 pleiotropic genes enriched in neurodevelopmental, immune, and neuronal signaling pathways. Several candidate mediators were implicated, including lifestyle and behavioral factors (e.g., number of sexual partners, smoking, religious involvement, and leisure screen time), psychosocial traits (loneliness and neuroticism), and physical health indicators. These shared loci and mediation findings should be interpreted as hypothesis-generating candidates for future mechanistic and intervention studies rather than as direct clinical targets.},
}

@article {pmid42768974,
year = {2026},
author = {Romero-Báez, Ó and Zepeda, V and Vázquez-Domínguez, E},
title = {Genotype-Phenotype-Environment Associations and Potential Local Adaptation Signals in the Mesquite Lizard Along the Eastern Trans-Mexican Volcanic Belt.},
journal = {Molecular ecology},
volume = {35},
number = {18},
pages = {e70561},
pmid = {42768974},
issn = {1365-294X},
support = {286794//Consejo Nacional de Humanidades, Ciencias y Tecnologías CONAHCyT - SRE/ ; },
mesh = {Animals ; *Lizards/genetics ; Phenotype ; Polymorphism, Single Nucleotide ; *Adaptation, Physiological/genetics ; Genotype ; Mexico ; Gene Flow ; *Gene-Environment Interaction ; Ecosystem ; Genetic Association Studies ; Genetics, Population ; Environment ; },
abstract = {Anthropogenic activities modify the composition and configuration of landscapes and fragment habitats, generating environmental gradients and dispersal barriers that alter gene flow and generate selective pressures. Identifying local adaptation, which depends on the balance between selection and gene flow, requires integrative approaches that combine multiple sources of evidence. Notably, signals of local adaptation have been poorly evaluated in Neotropical lizards. By integrating phenotypic, genomic, environmental, and landscape data, we assessed whether the mesquite lizard Sceloporus grammicus exhibits morphological changes associated with landscape variables, and also potential signals of local adaptation along a natural-anthropogenic gradient across the eastern Trans-Mexican Volcanic Belt. Phenotypic results showed traits that varied with landscape variables, including a negative effect of elevation on snout-vent length (SVL) and a positive effect of distance to forested areas (Dfz) on body condition index (BCI). Using genotype-environment and genotype-phenotype associations, we detected 72 candidate single nucleotide polymorphisms (SNPs) with adaptive signals, based on which we identified four adaptive units across the study area. Functional enrichment highlighted four genes (ADCY10, LMOD3, NINJ1, STX16) with overrepresented molecular functions. The frequency of the alternative allele in SNPs annotated to ADCY10, LMOD3, and NINJ1 increased with elevation and in individuals with smaller SVL, while it increased with Dfz and BCI for STX16. Overall, our results support spatially structured, landscape-linked candidate adaptive variation consistent with previously inferred functional connectivity patterns for the mesquite lizard. They also suggest mechanisms for exploring physiological and metabolic responses under environmental heterogeneity and anthropisation that could favor local adaptation.},
}

Animals
*Lizards/genetics
Phenotype
Polymorphism, Single Nucleotide
*Adaptation, Physiological/genetics
Genotype
Mexico
Gene Flow
*Gene-Environment Interaction
Ecosystem
Genetic Association Studies
Genetics, Population
Environment

@article {pmid42769683,
year = {2026},
author = {Zhou, Z and Xiao, X and Du, L and Zhu, J and Du, Z and Zheng, Y and Si, K and Gong, W},
title = {Accelerated immunostaining of thick biological tissues using bidirectional electric fields with reversible deformation.},
journal = {Biomedical optics express},
volume = {17},
number = {9},
pages = {4901-4915},
pmid = {42769683},
issn = {2156-7085},
abstract = {Immunostaining of thick biological tissues is often limited by slow antibody transport, resulting in long processing times and depth-dependent labeling. We describe an automated immunostaining approach based on an alternating bidirectional electric field, termed ARDEI, that improves labeling performance in millimeter-scale tissues. Under the applied electric-field conditions, tissue samples undergo reversible cyclic deformation, which may contribute to antibody redistribution by transiently altering tissue geometry. Using ARDEI, 1000 μm-thick mouse brain sections were labeled within 2.5 h, with improved signal penetration and spatial uniformity compared with passive diffusion and unidirectional electric-field staining under time-matched conditions. The system operates at 40 V under temperature-controlled conditions, minimizing thermal and structural perturbation. ARDEI supports three-dimensional imaging of neuronal and glial structures and can be applied to SHANEL-pretreated human brain tissue, where improved labeling uniformity was observed in 1000 μm-thick sections within 4 h. Under the tested conditions, repeated deformation cycles did not produce detectable structural distortion or signal degradation. These results show that ARDEI improves thick-tissue immunostaining performance and are consistent with a contribution from coupled electric-field-assisted transport and reversible tissue deformation. ARDEI provides a practical approach that can be integrated with existing optical imaging workflows for volumetric tissue analysis.},
}

@article {pmid42770209,
year = {2026},
author = {Thomas, S and Rajendran, AR and Radha, G and Subramanian, B},
title = {Sponge-Like Nanofibrous Hydroxyapatite/Zinc Oxide-Integrated Scaffolds for Rapid Hemostasis and Antibacterial Defense in Irregular Wound Management.},
journal = {ACS applied bio materials},
volume = {},
number = {},
pages = {},
doi = {10.1021/acsabm.6c00670},
pmid = {42770209},
issn = {2576-6422},
abstract = {Effective management of bleeding in irregular or noncompressible wounds continues to demand advanced hemostatic strategies beyond conventional dressings. In this study, a sponge-like fibrous scaffold was developed using electrospinning and gas-foaming techniques, incorporating polycaprolactone (PCL), Pluronic F127, biogenic hydroxyapatite (BHAP), and zinc oxide nanoparticles (nZnO). The primary objective of this nanostructured composite was to provide speedy hemostasis along with additional antibacterial properties. Structural and morphological characterization by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and field emission scanning electron microscopy (FESEM), that are evidently confirms successful integration of the active components and the formation of a highly porous, ECM-mimicking nanofibrous architecture. As compared to standard gauze and the commercial Hemosponge, the fibrous scaffold exhibited superior fluid handling, with water and blood absorption capacities of 4070 ± 203.5% and 2315.3 ± 115.7%, respectively. It also demonstrated enhanced hemo-compatibility (1.3% hemolysis), high porosity (73.3 ± 3%), and strong red blood cell and platelet adhesion, promoting clot formation. Whole blood clotting assays revealed a significantly lower blood clotting index (BCI: 14.59 ± 0.72%) than controls, confirming accelerated coagulation. The scaffold also exhibited broad-spectrum antibacterial activity against Escherichia coli and Staphylococcus aureus, attributed to ZnO-mediated high-surface-area contact-killing mechanism of the fibrous sponge. In vivo studies using rat tail and liver injury models showed rapid bleeding cessation (1.1 ± 0.05 min and 2.7 ± 0.13 min, respectively), with no histopathological abnormalities in major organs, confirming its systemic biocompatibility. Overall, this fibrous sponge filled with BHAP and ZnO offers a potential multipurpose foundation for sophisticated hemorrhage control.},
}

@article {pmid42771991,
year = {2026},
author = {Chen, L and Zheng, J and Xu, M and Zhu, P and Fu, Y and Shen, M and Chen, H},
title = {The objecthood of visual working memory representations influences their interaction with attention.},
journal = {Cognition},
volume = {278},
number = {},
pages = {106727},
doi = {10.1016/j.cognition.2026.106727},
pmid = {42771991},
issn = {1873-7838},
abstract = {Visual working memory (VWM) guides attentional selection toward memory-matching information in the environment. However, in the classical VWM-driven attentional capture paradigm, this effect is substantially reduced when multiple representations are simultaneously maintained. Although this capacity limitation has been attributed to a limited number of active VWM representations, it remains unclear what constitutes the functional unit underlying this limitation. Here, we examined whether objecthood enables multiple features to function as a single unit for attentional guidance. Across five experiments, participants memorized multiple features that either belonged to the same object or to separate objects before performing a visual search task containing memory-matching distractors. Replicating previous findings, multiple features failed to produce VWM-driven attentional capture when they belonged to separate objects. Critically, when the same features were integrated into a single object, they reliably guided attention. This objecthood effect generalized from two to three colors, extended to features from different dimensions (color and orientation) and different modalities (visual and verbal color representations), and could not be explained by differences in memory fidelity. These findings suggest that the capacity limitation in VWM-driven attentional capture operates over integrated representational units rather than individual features, with objecthood serving as an effective organizational principle that integrates multiple features into a single unit for attentional guidance.},
}

@article {pmid42772284,
year = {2026},
author = {Chen, Z and Wang, M and Xue, J and Li, Z and Chen, Y and Zhou, D and Tu, H and Zhuang, H and Du, H and Chen, Y and Ni, X and Wang, J and Li, T and Yang, H and Zhao, Z and Shen, WL},
title = {Anterior zona incerta to ventral tegmental area circuit controls compulsive eating in a binge-eating-disorder mouse model.},
journal = {Neuron},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.neuron.2026.08.014},
pmid = {42772284},
issn = {1097-4199},
abstract = {Compulsion is a defining feature of binge eating disorder (BED), yet the circuit basis sustaining compulsive binge eating remains unclear. Here, we identify tyrosine hydroxylase (TH)-BAC-Cre-labeled γ-aminobutyric acid (GABAergic) neurons in the anterior zona incerta (aZI[T] neurons) as a key population driving compulsive binge eating. In a mouse BED model, intermittent high-fat-diet training increases aZI[T] neuronal excitability, which is required for the development of compulsive intake. These neurons project to the ventral tegmental area (VTA), where they promote aversion-resistant food seeking and consumption. Mechanistically, BED training reduces inhibitory control from aZI[T] neurons onto VTA dopamine neurons via both direct and indirect pathways, and this effect results in enhanced dopamine release in the nucleus accumbens. Single-cell RNA sequencing and behavioral profiling further identify neurensin 2 (Nrsn2) as a genetic marker for aZI binge neurons that functionally contribute to compulsive binge eating. Together, these findings define a cell-type-specific ZI-VTA circuit that engages mesolimbic dopamine signaling to drive compulsive binge eating.},
}

@article {pmid42772331,
year = {2026},
author = {Jamil, M and Aziz, MZ and Huang, B and Yu, X},
title = {Diff-ADN: A diffusion-guided artifact denoising network with deterministic residual refinement for EEG.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/aeab36},
pmid = {42772331},
issn = {1741-2552},
abstract = {Physiological artifacts degrade electroencephalographic (EEG) recordings and can affect downstream brain-computer interface (BCI) analysis. This study develops a compact single-channel framework for ocular, muscular, cardiac, and mixed-artifact removal. Approach: The Diffusion-Guided Artifact Denoising Network (Diff-ADN) employs a two-stage framework comprising severity-conditioned Stage-I reconstruction followed by diffusion-guided Stage-II residual refinement. During training, forward noising and velocity prediction supervise the Stage-II encoder, whereas inference requires only a single deterministic residual correction, without iterative reverse-diffusion sampling. The framework was evaluated under contamination levels ranging from -7 to +2 dB, using independently recorded artifact sources and motor-imagery decoding across four public EEG datasets. Main results: Diff-ADN achieved mean Pearson correlations of 0.936, 0.839, 0.886, and 0.844 for EOG, EMG, ECG, and mixed EOG+EMG artifacts, respectively. When tested with independently recorded artifact sources, performance varied by artifact type: larger reductions were observed for EOG and EMG, while PTB and INCART ECG differed from the MIT-BIH reference by 0.026 and 0.014, respectively. Across the four motor-imagery datasets, ECG denoising recovered 4.88-5.59 percentage points (pp) in decoding accuracy compared with artifact-corrupted EEG. The largest recovery was 21.90 pp for PTB ECG artifacts on BCI IV-2a at -6 dB. Significance: The proposed framework combines artifact-aware EEG reconstruction with efficient deterministic inference, processing 2-s segments in 12.52-17.08 ms on the tested CPU. Results across independent artifact sources and multiple motor-imagery datasets further show that improvements in waveform reconstruction do not necessarily translate into uniform recovery of BCI decoding accuracy.},
}

@article {pmid42759576,
year = {2026},
author = {Cai, Y and Guo, Q and Lin, X},
title = {TopoAdapter: a plug-and-play multi-hop topology adapter for MI-EEG decoding.},
journal = {Journal of neuroscience methods},
volume = {},
number = {},
pages = {110909},
doi = {10.1016/j.jneumeth.2026.110909},
pmid = {42759576},
issn = {1872-678X},
abstract = {BACKGROUND: Motor imagery electroencephalography (MI-EEG) decoding is limited by low signal-to-noise ratio, non-stationarity, inter-subject variability, and small calibration sets. Lightweight decoders are attractive for online BCI but often learn channel relations only from limited training data.

NEW METHOD: We introduce TopoAdapter, a plug-and-play input module that injects a fixed electrode-layout prior into existing EEG backbones. It builds a physical electrode graph from the montage, computes cumulative multi-hop channel-to-neighborhood contrasts, and adds a learnable low-amplitude residual while preserving input shape.

RESULTS: Under an aligned 500-epoch, five-seed ATCNet protocol, mean accuracy changes were +1.17 and +0.13 percentage points on the BCI Competition IV-2a and Zhou2016 motor-imagery datasets, respectively, and +0.36 points on the High-Gamma executed-movement dataset. All three dataset-level means were positive; the BCI IV-2a and High-Gamma bootstrap intervals excluded zero, although no paired test remained significant after three-dataset Holm correction. In a separate BCI IV-2a compatibility study, all seven selected backbones improved on average and three retained Holm-adjusted Wilcoxon evidence.

Unlike graph neural decoders that redesign the backbone, TopoAdapter keeps downstream components unchanged. In a matched comparison with the open-source Adaptive Channel Mixing Layer (ACML), TopoAdapter attained 60.52% versus 60.42% accuracy with 70 versus 506 added parameters; the direct paired difference was unresolved.

CONCLUSIONS: TopoAdapter provides an explicit, ultra-lightweight spatial prior for motor EEG decoding. Positive mean changes on two motor-imagery datasets, one executed-movement dataset, and seven heterogeneous BCI IV-2a backbones support portability and a favorable cost-benefit profile, while effect magnitude remains dataset- and subject-dependent.},
}

@article {pmid42761268,
year = {2026},
author = {Deedklin, A and Suwanprateeb, J and Pisek, A and Pawaputanon Na Mahasarakham, C and Pisek, P},
title = {Influence of carboxymethyl cellulose and calcium-crosslinked CMC coating of 3D-Printed hydroxyapatite scaffolds on the early hemostatic performance and osteoblastic compatibility.},
journal = {Frontiers in bioengineering and biotechnology},
volume = {14},
number = {},
pages = {1866258},
pmid = {42761268},
issn = {2296-4185},
abstract = {INTRODUCTION: Successfully managing bl eeding bone defects relies on biomaterials capable of promoting early hemostasis alongside osteogenesis. While 3D-printed hydroxyapatite (3DP-HA) scaffolds possess osteoconductivity, their clinical utility can be limited by poor blood stability and inadequate initial hemostatic properties. To address these challenges, this preliminary study investigates the surface modification of 3DP-HA scaffolds using carboxymethyl cellulose (CMC) and its calcium-crosslinked derivative (CMC-Ca).

MATERIALS AND METHODS: Scaffolds were coated with either 1% or 2% CMC, or a CMC-Ca complex at varying formulations (1:1, 1:2, and 2:1). Total porosity and mean pore diameter were evaluated via micro-computed tomography (micro-CT). Surface morphology and elemental properties were characterized via scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). Early in vitro hemostatic tendencies were evaluated through blood absorption and whole-blood clotting index (BCI) assays. Preliminary cytocompatibility and early osteogenic response were assessed by observing cell attachment via SEM and measuring alkaline phosphatase (ALP) activity at Day 7 using a human fetal osteoblast cell line (hFOB 1.19).

RESULTS: All modified formulations maintained total porosity ranging from 54.08% to 61.85%. Blood absorption capacity was comparable among all groups without statistically significant differences. For the in vitro clotting assay, the 2:1 CMC-Ca formulation exhibited a lower blood clotting index value than the other scaffold groups, suggesting a favorable initial coagulation response under the tested conditions. In vitro biological assays provided early descriptive evidence that the coatings permitted cell attachment and spreading by Day 7. Furthermore, ALP activity remained comparable across all groups, indicating that the surface modifications did not inherently suppress early-stage osteogenic signaling at the investigated time point.

CONCLUSION: This preliminary study demonstrates that surface-modified 3DP-HA scaffolds maintained macro-porosity while the addition of CMC and CMC-Ca coatings provided early indications of in vitro hemostatic potential and early osteogenic compatibility. In particular, the 2:1 CMC-Ca formulation showed a positive initial blood clotting tendency without descriptive impairment of osteoblastic function. While further comprehensive, higher-powered quantification and mechanistic assays are required, these initial results offer a potential baseline strategy for developing surface-modified bone grafts.},
}

@article {pmid42762093,
year = {2026},
author = {Wang, PS and Zou, SM and Wei, Q and Wu, ZY and Li, HF},
title = {Weak association of pathogenic ERBB4 variants with amyotrophic lateral sclerosis.},
journal = {Neurodegenerative disease management},
volume = {},
number = {},
pages = {1-9},
doi = {10.1080/17582024.2026.2736021},
pmid = {42762093},
issn = {1758-2032},
abstract = {INTRODUCTION: ERBB4 variants were reported to cause amyotrophic lateral sclerosis (ALS). However, gene burden analyses did not find an enrichment of rare variants in patients, leaving the pathogenic role of ERBB4 in ALS unclear. Therefore, this study aimed to reassess the association of ERBB4 variants with ALS.

METHODS: Next-generation sequencing was performed in 250 ALS and 714 non-ALS patients. Low-frequency, deleterious non-synonymous ERBB4 variants were filtered, and their allele frequencies were compared between groups.

RESULTS: In total, 42 low-frequency and deleterious ERBB4 variants were identified in patients and normal controls, with three variants in all groups. There was no significant difference in allele frequencies between ALS and non-ALS groups. Additionally, four reported pathogenic variants (c.158A > G, c.284G > A, c.965T > A, and c.1624G > A) were observed in patients with neuromuscular disease or leukoencephalopathy, as well as normal controls. Based on the evidence from this study, c.284G > A was reclassified as a likely benign variant, while the others were reclassified as uncertain significance according to the American College of Medical Genetics and Genomics Guidelines.

DISCUSSION: These results suggest a modest association between ERBB4 variants and ALS, underscoring the need for clinicians to conduct more careful molecular diagnosis and genetic consultations for ALS patients with ERBB4 variants.},
}

@article {pmid42763341,
year = {2026},
author = {Wang, D and Xu, J and Wang, Z and Liu, Z and He, Z and Xu, T and Mei, B and Zhang, J and Liu, H and Yang, Z and Ren, X and Ni, J and Li, Y and Gong, W and Qiu, G and Liu, X},
title = {A circuit dissection of perception-action decoupling in S-ketamine-induced hallucination-like states.},
journal = {Molecular psychiatry},
volume = {},
number = {},
pages = {},
pmid = {42763341},
issn = {1476-5578},
support = {82571450//National Natural Science Foundation of China (National Science Foundation of China)/ ; grant Nos. 82571450//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
abstract = {Hallucinations are a core feature of several psychiatric disorders, but the circuit mechanisms that separate perception from behavioral output remain poorly defined. Here, we combined an auditory discrimination task with AI-based pose analysis to quantify S-ketamine-induced false auditory threat responses and behavioral disorganization in mice. Control assays, including sucrose preference, loss of righting reflex, and prepulse inhibition, indicated that these effects were not explained by anhedonia, anesthesia, or basic auditory deficits. Using in vivo fiber photometry, single-cell miniscope calcium imaging, and pathway-specific chemogenetic and optogenetic manipulations, we identified dissociable circuit contributions within convergent striatal pathways. The basolateral amygdala to caudal striatum pathway (BLA→TS) supported salience-weighted perceptual decisions and, when aberrantly recruited by S-ketamine, promoted auditory false alarms. In contrast, the medial prefrontal cortex to caudal striatum pathway (mPFC→TS) primarily shaped behavioral expression and, when dysregulated, generated disorganized action patterns. At the network level, S-ketamine shifted TS activity from a sparse, high-contrast state to a high-frequency, low-amplitude, diffusely coupled state, consistent with reduced integrative precision. Auditory cortex to TS inputs were not broadly suppressed, supporting pathway specificity. Bidirectional chemogenetic manipulation of BLA→TS and mPFC→TS pathways in drug-naive mice further supported the TS as an integrative node linking perceptual evaluation to behavioral output. Dexmedetomidine co-administration restored pathway-level temporal dynamics and reorganized TS network coupling without simply suppressing activity. Together, these findings define a circuit framework for NMDAR-antagonist-induced hallucination-like states and provide a mechanistic rationale for dexmedetomidine-mediated mitigation of S-ketamine-associated perceptual and behavioral disruption.},
}

@article {pmid42763501,
year = {2026},
author = {Huang, X and Li, L and Gao, X and Chen, S and Feng, C and Zhong, Z and Zhang, Z and Huang, J},
title = {Exploiting frontotemporal asymmetry in low-channel EEG emotion recognition via spectral fusion network.},
journal = {Cognitive neurodynamics},
volume = {20},
number = {1},
pages = {177},
pmid = {42763501},
issn = {1871-4080},
abstract = {Portable EEG devices hold promise for pervasive affective computing, yet sparse channel counts limit the resolution for capturing global cortical dynamics of emotional processing. To address this, we propose the Spatiotemporal Spectral Asymmetric Fusion Network (STSANet), a neurophysiologically grounded framework designed to decode emotional states from low-density recordings. Unlike traditional methods limited by spatial resolution, we introduce a dual-branch architecture prioritizing Frequency and Spatial Asymmetry Modeling. Instead of merely extracting features, the model explicitly quantifies non-linear hemispheric lateralization-a core mechanism of valence regulation. By modeling differential activation between homologous frontotemporal electrodes (e.g., prefrontal asymmetry), STSANet captures critical lateralized neurodynamics without high-density coverage. A cross-modal attention mechanism then adaptively fuses these lateralized signatures with spectral oscillations. Validating ecological feasibility, we confirm consistent spectral energy distributions between portable Xmuse and professional-grade Enobio devices. Experiments on SEED and a self-collected dataset demonstrate STSANet's superior performance, achieving accuracies of 86.80% and 87.43%, respectively. Crucially, the model maintains high robustness even under rigorous trial-level cross-validation, confirming its generalization capability against temporal distribution shifts. Ablation studies reveal success hinges on explicit spatial asymmetry modeling. Thus, capturing lateralized neurodynamics serves as a resource-efficient strategy for accurate, neurophysiologically interpretable pervasive BCI applications.},
}

@article {pmid42763839,
year = {2026},
author = {Carvalho, R and Azevedo, E and Marques, P and Dias, N and Cerqueira, JJ},
title = {Neurofeedback-Guided Motor Imagery in Chronic Stroke: A Case Series on Upper-Limb Recovery, Cortical Activation, and Brain Symmetry.},
journal = {Applied psychophysiology and biofeedback},
volume = {},
number = {},
pages = {},
pmid = {42763839},
issn = {1573-3270},
abstract = {BACKGROUND: Brain-computer interface (BCI) systems combined with motor imagery (MI) have emerged as promising tools in neurorehabilitation. Real-time neurofeedback may further enhance motor recovery by promoting use-dependent neuroplasticity; however, evidence in chronic stroke remains limited, particularly from controlled pilot studies.

OBJECTIVE: This case series explored the feasibility and preliminary effects of EEG-based BCI neurofeedback combined with MI and physiotherapy on upper-limb motor function and brain activation patterns in individuals with chronic stroke.

METHODS: In a double-blind, controlled protocol, seven individuals with chronic stroke were allocated to either an experimental group receiving MI with real-time EEG-based BCI neurofeedback or a control group receiving MI with sham feedback. All participants completed a standardized four-week physiotherapy program. Motor outcomes were assessed with the Action Research Arm Test, Fugl-Meyer Assessment, Motor Assessment Scale, and grip strength, with functional changes interpreted against minimal clinically important difference (MCID) thresholds. Neuroplastic changes were explored using EEG-derived symmetry measures and task-related functional MRI.

RESULTS: Participants receiving real neurofeedback exhibited consistent improvements exceeding MCID thresholds in at least one functional outcome, most notably grip strength. This group also demonstrated more symmetrical EEG activity and more consistent sensorimotor and cerebellar activation patterns on fMRI. In contrast, responses in the sham group were more variable and appeared influenced by a single high responder.

CONCLUSIONS: These findings support the feasibility of integrating EEG-based BCI neurofeedback with MI and physiotherapy in chronic stroke rehabilitation. The observed functional gains and associated neurophysiological changes suggest a preliminary, exploratory role for this intervention in promoting upper-limb recovery in this small sample.},
}

@article {pmid42763980,
year = {2026},
author = {Luo, TJ and Cai, Z and Cao, X},
title = {Comprehensive deep representation-based Wasserstein domain discriminator for cross-subject motor imagery EEG classification.},
journal = {Artificial intelligence in medicine},
volume = {182},
number = {},
pages = {103537},
doi = {10.1016/j.artmed.2026.103537},
pmid = {42763980},
issn = {1873-2860},
abstract = {Motor imagery electroencephalogram (MI-EEG) signals have attracted great attention for assistant rehabilitation in biomedical engineering. However, due to recording environment, device, and subject variabilities, original deep neural network models are suffered from data distribution discrepancies across subjects. Although recently deep domain adaptation models endeavored to solve the distribution discrepancies, they suffer from the simple feature representation and gradient vanish during domain-invariant feature learning. To this end, we propose a novel deep domain adaptation model, referred to as Comprehensive Deep Representation based Wasserstein Domain Discriminator (CDR-WDD), to simultaneously represent comprehensive deep features and adversarial learned based on the domain discriminator with stable learning gradient. Specifically, our CDR-WDD model involves a jointly optimization that weighted the loss of feature representing and adversarial learning, which improves the performance of cross-subject MI-EEG classification. Empirical studies on four benchmark MI-EEG datasets have revealed the superiority performance of the proposed model compared with state-of-the-art deep domain adaptation models, which achieves average accuracies and Cohen's kappa value of 84.34, 89.59, 73.32, 87.75 and 0.790, 0.802, 0.466, 0.755 for BCIIV-2a, BCIIV-2b, OpenBMI, and WCCI datasets, respectively. Ablation studies have been conducted to show the effectiveness of CDR and WDD modules. Our CDR-WDD model provides a novel option to build brain-computer interfaces.},
}

@article {pmid42758840,
year = {2026},
author = {Dong, K and Song, H and Zhao, Q and Song, Z and Lv, F and Wan, S and Zheng, T and Fan, Y and Liu, WC and Zhang, S and Wu, Y and Huang, Y and Song, J and Gong, Z and Zheng, N and Nan, K},
title = {Real-time, cross-modal genotype mapping of free-moving Drosophila larvae via simultaneous mechano-electrophysiological recording.},
journal = {Science advances},
volume = {12},
number = {38},
pages = {eaef7492},
pmid = {42758840},
issn = {2375-2548},
mesh = {Animals ; *Larva/genetics/physiology ; Genotype ; *Electrophysiological Phenomena ; *Drosophila/genetics/physiology ; *Drosophila melanogaster/genetics/physiology ; Phenotype ; Locomotion ; },
abstract = {Drosophila larvae provide a powerful model for interrogating genes associated with human muscle and neurological disorders; however, existing genotyping and phenotyping approaches remain low-throughput and often rely on destructive, invasive, or toxic procedures. Here, we present a scalable bioelectronic platform that enables real-time, simultaneous mechano-electrophysiological recording from freely moving Drosophila larvae in an open three-dimensional (3D) space, allowing high-throughput cross-modal genotype mapping (CMGM). The system integrates conductive and piezoelectric microneedle electrodes into a flexible sensory array that achieves stable, long-term signal acquisition during unrestricted and complex 3D locomotion. By coupling dual-modal signal acquisition with machine-learning-assisted classification, we directly identify muscle defects in unlabeled RNAi-knockdown larvae within 30 minutes, without invasive manipulation or time-consuming sample preparation. Incorporation of both electrophysiological and mechanical waveform features improves overall classification accuracy to 96%, outperforming single-modality approaches. This non-destructive, high-throughput CMGM strategy establishes a generalizable framework for bridging genotype and phenotype in intact, freely behaving organisms, with broad implications for functional genetics and disease modeling.},
}

Animals
*Larva/genetics/physiology
Genotype
*Electrophysiological Phenomena
*Drosophila/genetics/physiology
*Drosophila melanogaster/genetics/physiology
Phenotype
Locomotion

@article {pmid42759058,
year = {2026},
author = {Fang, S and Yang, C and Tang, Y and Chen, L and Zhao, W and Ma, C and Li, G and Wu, X and Li, J},
title = {Association between choroid plexus susceptibility features and motor outcomes following deep brain stimulation in Parkinson's disease.},
journal = {Journal of neurosurgery},
volume = {},
number = {},
pages = {1-10},
doi = {10.3171/2026.4.JNS252510},
pmid = {42759058},
issn = {1933-0693},
abstract = {OBJECTIVE: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy for advanced Parkinson's disease (PD), but postoperative motor outcomes show substantial interindividual variability. Recent evidence suggests choroid plexus (ChP) dysfunction in PD pathophysiology. This study aimed to investigate the association between preoperative ChP MRI characteristics and postoperative motor outcomes following STN-DBS in PD patients.

METHODS: Forty-one PD patients who underwent bilateral STN-DBS were included for final analysis. Motor outcomes were assessed using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale part III scores at baseline and 6 months after surgery. ChP dysfunction was evaluated by quantifying volume from T1-weighted imaging and extracting susceptibility histogram features from quantitative susceptibility mapping (QSM). Correlation and receiver operating characteristic (ROC) analyses were performed to evaluate the predictive value of ChP imaging metrics.

RESULTS: Preoperative total motor scores were positively associated with maximum ChP susceptibility (r = 0.410, p = 0.008), while tremor and rigidity subscores correlated with kurtosis (r = 0.395, p = 0.011) and the 90th percentile (r = 0.356, p = 0.023), respectively, of the ChP susceptibility values. Postoperative total motor improvement showed significant positive correlations with the 10th percentile (r = 0.406, p = 0.009), mean (r = 0.325, p = 0.038), minimum (r = 0.322, p = 0.040), and skewness (r = 0.344, p = 0.028) of ChP susceptibility histogram features. For specific motor symptoms, bradykinesia improvement was positively associated with the 10th percentile (r = 0.394, p = 0.011), minimum (r = 0.335, p = 0.033), and skewness (r = 0.319, p = 0.042) of the ChP susceptibility values. Gait stability improvement correlated positively with the 10th percentile (r = 0.376, p = 0.016), mean (r = 0.379, p = 0.015), and median (r = 0.349, p = 0.026) values of ChP susceptibility. Combining ChP susceptibility histogram features with clinical characteristics achieved an area under the curve of 0.85 for differentiating superior from moderate responders to STN-DBS in terms of total motor outcomes.

CONCLUSIONS: This exploratory study suggests that ChP microvascular damage and iron dysregulation are linked to preoperative motor severity in PD, while ChP calcification is significantly associated with motor responsiveness to STN-DBS. Combining the susceptibility histogram features of ChP calcification with clinical characteristics may offer additional value for improving patient-specific prognostication.},
}

@article {pmid42759510,
year = {2026},
author = {Qu, J and Yang, J and Li, W and Zeng, X and He, X and Guo, H and Lu, J and Jiang, X and Zhuang, X and Qian, C and Liu, Z and Huang, J and Wang, H and Xu, H and Li, H and Gao, Z and Kang, L and Hu, H and Ma, H},
title = {A miR-10a-5p-γCaMKII axis links periphery-to-brain signaling to cognitive vulnerability during female midlife.},
journal = {Neuron},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.neuron.2026.08.022},
pmid = {42759510},
issn = {1097-4199},
abstract = {Although women live longer, they paradoxically face heightened susceptibility to cognitive and systemic decline emerging in midlife-an underexplored transition from resilience to vulnerability. Here, we investigate biological processes associated with this female-biased vulnerability and their molecular regulation. Senescence-associated features were preferentially elevated in middle-aged females in human brain and spleen tissues, with similar changes in mice. In female mice, epigenetic upregulation of the X-linked RNA-binding protein RBMX promoted midlife increases in splenic miR-10a-5p, while complementary in vivo approaches supported a peripheral contribution to cerebral miR-10a-5p abundance. miR-10a-5p repressed calcium/calmodulin-responsive kinase γCaMKII, and modulation of this axis influenced mitochondrial function, cellular senescence, and memory in mice. In neurons derived from Alzheimer's disease patients and in model mice, miR-10a-5p inhibition attenuated disease-associated phenotypes, supporting relevance to pathological aging. Together, these findings link periphery-to-brain communication to emerging brain vulnerability during female midlife and indicate that this transition may remain amenable to intervention.},
}

@article {pmid42754029,
year = {2026},
author = {Fonseca, M and Roy, JP and Albaaj, A and Renaud, DL and Barkema, HW and de Lagarde, M and Arango-Sabogal, JC and Dufour, S},
title = {Estimating herd prevalence of major mastitis pathogens in Canadian dairy herds using Bayesian latent class models.},
journal = {Journal of dairy science},
volume = {},
number = {},
pages = {},
doi = {10.3168/jds.2026-28861},
pmid = {42754029},
issn = {1525-3198},
abstract = {Mastitis remains a major challenge for dairy production worldwide, and understanding pathogen prevalence is essential for guiding control strategies. This study aimed to estimate the prevalence of major mastitis pathogens in bulk tank milk (BTM) from Canadian dairy herds in Alberta, Ontario, and Québec. A total of 340 herds were included, with BTM samples analyzed by qPCR for Staphylococcus aureus, Streptococcus uberis, Streptococcus dysgalactiae, Streptococcus agalactiae, Mycoplasma spp., Mycoplasmopsis bovis, Prototheca spp., Klebsiella spp., and Escherichia coli. We used a 2-stage Bayesian latent class model (BLCM) to estimate the provincial herd-level prevalence of each pathogen, along with 95% credible intervals (95% BCI). Samples classified as 'suspect' by qPCR were excluded from the BLCM analysis. We also classified pathogens as having a very low prevalence when there was a > 95% probability that the provincial prevalence was below 1%. The estimated prevalence of S. aureus was 56.4% in Québec (95% BCI: 48.5-63.9), 32.6% in Ontario (95% BCI: 23.7-42.2), and 35.0% in Alberta (95% BCI: 22.4-48.8). Streptococcus uberis was the second most prevalent pathogen, with estimated prevalence of 41.2% (95% BCI: 34.2-48.4) in Québec, 34.1% (95% BCI: 25.7-43.2) in Ontario, and 33.7% (95% BCI: 22.6-45.8) in Alberta. Streptococcus dysgalactiae followed, with estimated prevalence of 13.7% (95% BCI: 9.3-19.1), 8.2% (95% BCI: 4.0-14.2), and 8.5% (95% BCI: 3.1-17.3) in Québec, Ontario, and Alberta, respectively. The estimated prevalence for S. agalactiae, Mycoplasma spp., M. bovis, Prototheca spp., Klebsiella spp., and E. coli ranged from 0.3 to 5.8%. Specifically, S. agalactiae prevalence was 0.6% (95% BCI: 0.1-4.4) in Alberta, 1.8% (95%BCI: 0.3-5.5) in Ontario, and 2.1% (95% BCI: 0.7-4.8) in Québec. Mycoplasma spp. prevalence was 0.6% (95% BCI: 0.1-4.4), 2.7% (95% BCI: 0.7-6.9), and 1.6% (95%BCI: 0.4-4.1) in Alberta, Ontario, and Québec, respectively, while M. bovis prevalence was 0.5% (95% BCI: 0.1-3.8), 0.9% (95% BCI: 0.1-3.7), and 0.3% (95% BCI: 0.1-1.4). Prototheca spp. prevalence ranged from 0.4% (95% BCI: 0.1-2.5) in Ontario to 3.1% (95% BCI: 1.3-6.3) in Québec, and Klebsiella spp. prevalence ranged from 0.6% (95%BCI: 0.1-4.2) in Alberta to 1.8% (95% BCI: 0.3-5.5) in Ontario. Finally, for E. coli, the estimated prevalence was 4.1% (95% BCI: 0.8-11.0), 5.8% (95% BCI: 2.4-11.1), and 3.9% (95%BCI: 1.7-7.3) in Alberta, Ontario, and Québec, respectively. Our analyses suggested that all 3 provinces could be considered as having low prevalence of M. bovis. For microorganisms that mainly causes clinical mastitis, the lower prevalence estimates likely reflect, at least in part, the limitations of a single BTM sampling rather than true limited circulation. Positive predictive values were low for most pathogens, except for S. aureus, highlighting the need to interpret positive results with caution, whereas negative predictive values were consistently high for most pathogens (>0.98), indicating reliable negative results. Overall, these findings emphasize the importance of continuous surveillance, regular diagnostic testing, and implementation of biosecurity measures to reduce the prevalence of mastitis pathogens.},
}

@article {pmid42755609,
year = {2026},
author = {Wang, K and Li, W and Ding, D and Wang, L and Sun, Y and Zhao, H and Gong, W},
title = {Hybrid EEG-EMG intention decoding for real-time triggering of a lower-limb exoskeleton.},
journal = {Frontiers in neurorobotics},
volume = {20},
number = {},
pages = {1914651},
pmid = {42755609},
issn = {1662-5218},
abstract = {BACKGROUND: Wearable lower-limb exoskeletons have the potential to support intention-driven control of lower-limb exoskeletons, but existing control strategies often rely on mechanical or manual triggers that fail to capture user intent.

METHOD: Subjects were recruited from 23/9/2024 to 10/2/2025. A BiLSTM detector was pretrained on a dataset collected from 50 healthy volunteers (45 for training, 5 for independent testing) using bilateral surface EMG recordings from six lower-limb muscles (12 EMG channels), 16-channel EEG, and hip-knee kinematics. Seven naive participants then completed ten 20-m outward-and-return walking trials (10 m outward and 10 m return) under each of three control modes (EMG, EEG, hybrid). Primary outcomes were triggering latency and classification accuracy. Triggering latency was defined as the time interval between the onset of the gait-transition event and the activation of the exoskeleton assistance command. This latency included the observation delay introduced by the sliding window, feature extraction time, BiLSTM inference time, and communication delay between the decoder and the exoskeleton controller. Usability was assessed with donning/doffing times and QUEST 2.0.

RESULTS: The hybrid BiLSTM detector achieved higher classification accuracy (left: 91.3%; right: 86.6%) and shorter mean per-step triggering latency (left: 0.29 s; right: 0.28 s) than either EMG-only (mean 0.33 s) or EEG-only approaches (mean 0.30 s). Hybrid EEG-EMG fusion therefore improved decoding performance while reducing triggering latency compared with unimodal decoding strategies. The latency reduction relative to EMG-only control corresponded to a large effect size (Cohen's d ≈ 0.88). Hybrid sessions also yielded shorter total session time (mean 32.1 min). Usability metrics demonstrated acceptable donning/doffing times and favorable QUEST 2.0 scores (mean 32.0/40).

CONCLUSION: These proof-of-concept results demonstrate that BiLSTM-based fusion of EEG and EMG improves responsiveness and classification reliability for exoskeleton assistance. These findings underscore the contribution of EEG-derived sensorimotor features and EMG information for intention-related gait transition detection within a multimodal real-time exoskeleton control framework. We discuss limitations related to sample size, artifact validation, and generalizability and identify next steps for patient studies and ergonomic optimization.},
}

@article {pmid42755662,
year = {2026},
author = {Wu, Y and Zhu, F and Dong, Q and Zhang, M},
title = {Brain-computer interface for post-stroke upper-limb recovery: a systematic review integrating clinical efficacy with neuroplasticity evidence.},
journal = {Frontiers in neurology},
volume = {17},
number = {},
pages = {1895484},
pmid = {42755662},
issn = {1664-2295},
mesh = {Humans ; *Stroke Rehabilitation/methods ; *Neuronal Plasticity/physiology ; *Brain-Computer Interfaces ; *Upper Extremity/physiopathology ; *Recovery of Function/physiology ; *Stroke/physiopathology/therapy ; Randomized Controlled Trials as Topic ; },
abstract = {OBJECTIVE: Over 20 systematic reviews have evaluated brain-computer interface (BCI) training for post-stroke upper-limb rehabilitation, but published syntheses have focused predominantly on clinical efficacy, and the neuroplasticity mechanisms remain comparatively underexplored. This review integrates pooled clinical efficacy with a structured synthesis of neuroplasticity evidence from the same trials.

METHODS: PubMed, Embase, CINAHL via EBSCO, Web of Science, Scopus, and Cochrane CENTRAL were searched from inception to May 2026. Randomized controlled trials (RCTs) of BCI-based training for post-stroke upper-limb recovery were eligible. Two parallel syntheses were conducted. A random-effects meta-analysis pooled mean differences for three upper-limb motor outcomes, RoB 2 risk-of-bias assessment, GRADE certainty-of-evidence grading, and publication-bias diagnostics. Neuroplasticity evidence was synthesized qualitatively following the Synthesis Without Meta-analysis (SWiM) guideline.

RESULTS: Thirty-five RCTs (n = 1,188) were included. BCI training improved Fugl-Meyer Assessment-Upper Extremity [FMA-UE; MD = 4.55, 95% CI (2.84, 6.25), P < 0.001], Action Research Arm Test [ARAT; MD = 3.90, 95% CI (1.31, 6.50), P = 0.003], and Wolf Motor Function Test [WMFT; MD = 8.53, 95% CI (3.01, 14.04), P = 0.002]. Comparator type significantly moderated the effect [Q-between(3) = 13.43, P < 0.01], ranging from MD = 6.70 against usual care to MD = 1.97 against sham-contingent controls; stroke stage, signal strategy, and feedback modality did not. Qualitative synthesis of 22 trials identified multi-level neuroplastic changes spanning corticospinal excitability, sensorimotor rhythm modulation, and network reorganization. A subset of studies reported correlations between neuroplastic changes and motor improvement.

CONCLUSION: This systematic review found that BCI-based multimodal rehabilitation improves post-stroke upper-limb motor function, with the estimated effect varying by comparator type. Neuroplasticity outcomes were examined across electrophysiological, hemodynamic, and structural modalities, but the current evidence is too heterogeneous and sparse to support a mechanistic account of recovery. Further research is needed to determine how training-associated neural changes relate to functional improvement.

https://www.crd.york.ac.uk/prospero/view/CRD420251053630, identifier: CRD420251053630.},
}

Humans
*Stroke Rehabilitation/methods
*Neuronal Plasticity/physiology
*Brain-Computer Interfaces
*Upper Extremity/physiopathology
*Recovery of Function/physiology
*Stroke/physiopathology/therapy
Randomized Controlled Trials as Topic

@article {pmid42756320,
year = {2026},
author = {Yin, C and Tu, J},
title = {Ultrasound Brain-Computer Interfaces for Transcranial Closed-Loop Neuromodulation.},
journal = {BME frontiers},
volume = {7},
number = {},
pages = {0312},
pmid = {42756320},
issn = {2765-8031},
abstract = {Noninvasive brain-computer interfaces (BCIs) have advanced communication, assistive control, and neurorehabilitation, but most remain readout-oriented systems with limited capacity for deep targeting, focal intervention, and response-guided modulation. Ultrasound offers a distinct route to brain interfacing: functional ultrasound imaging provides spatially localized hemodynamic readout, although current human task-related evidence relies on surgically enabled acoustic access; transcranial focused ultrasound enables noninvasive modulation of cortical and subcortical circuits. We define an ultrasound BCI as a system that converts measured brain activity into a functionally useful output, with ultrasound providing readout, state-contingent write-in, or both; in the closed-loop framework considered here, response assessment updates or constrains subsequent modulation. This Perspective argues that ultrasound BCI should be viewed not as a replacement for established BCIs, but as a transcranial closed-loop acoustic neuromodulation platform. We clarify its boundaries, compare current evidence maturity, and outline translational routes for neurorehabilitation, abnormal brain-state intervention, and deep-brain neurofeedback.},
}

@article {pmid42751858,
year = {2026},
author = {Peng, Y and Han, Y and Niu, X and Wang, Z and Zhang, X and Shi, L and Lu, S},
title = {An Avian-Inspired Computational Model Driven by Texture-Color Prioritization Strategies in Visual Processing.},
journal = {International journal of neural systems},
volume = {},
number = {},
pages = {2750023},
doi = {10.1142/S0129065727500237},
pmid = {42751858},
issn = {1793-6462},
abstract = {Birds have evolved distinctive visual processing strategies to adapt to complex natural environments. Pigeons can discriminate visual objects using multiple cues, including local texture, color, and shape. However, natural objects contain these cues simultaneously, and it remains unclear how the pigeon visual system balances these visual features when they co-occur. Whether such biological feature-prioritization principles can inform computational recognition models also remains unknown. Here, we combined behavioral delayed matching-to-sample tasks, in vivo electrophysiological recordings from the entopallium, and spectral-coherence-based network analysis to investigate multidimensional visual processing in pigeons. Behavioral and electrophysiological results revealed a stable feature-prioritization pattern dominated by color and texture, with shape playing a subordinate role. Functional connectivity further indicated that network organization became sparser under information-rich conditions, suggesting that pigeons selectively extract nonredundant cues rather than processing all dimensions equally. Guided by these biological findings, the present research developed the Avian-inspired Feature Gating Model (AFGM). By incorporating independent channel gating and sparse regularization, AFGM formalizes this biological feature-weighting strategy. The model achieved a modest performance advantage over the HVE baseline on fine-grained recognition tasks. Together, these results reveal a consistent texture-color prioritization pattern in pigeons and provide a biologically inspired framework for feature-weighted machine vision.},
}

@article {pmid42753558,
year = {2026},
author = {Wolpert, M and Chen, Y and Ding, N},
title = {Phrase-level speech timing preferences predict synchronization in joint reading.},
journal = {Cognition},
volume = {278},
number = {},
pages = {106713},
doi = {10.1016/j.cognition.2026.106713},
pmid = {42753558},
issn = {1873-7838},
abstract = {For rhythmic motor activities, such as tapping, walking, and playing music, individuals often show preferred timescales, and differences between individuals' timing preferences impact how well they can synchronize. Speech is only quasi-periodic, but previous studies have suggested that it also exhibits preferred timescales for linguistic units, e.g., syllables and intonational phrases. The present study provides a direct test of whether individual speech timing preferences at syllable and phrase boundaries constrain synchronization in joint speech. We recorded Mandarin speech while participants read aloud lists of short, regularly structured sentences in solo and joint reading tasks. Syllable-level timing was measured with inter-syllable onset interval, and phrase-level timing was indexed by phrase-final lengthening and inter-phrase pause. Participants (N = 88) completed an at-home solo reading task; a subset (N = 32) participated in an in-lab session with solo and paired joint reading. Results show that mean syllable duration is highly aligned in joint reading, regardless of individuals' preferred syllable duration during solo speech. In contrast, mismatches in individuals' phrase-level, but not syllable-level, timing preferences during solo speech significantly predicted syllable onset asynchrony during joint reading. These findings suggest that syllable timing is adaptable in speech synchronization, while final lengthening and pauses between intonational phrases show stronger individual preferences that impact synchronization performance.},
}

@article {pmid42748101,
year = {2026},
author = {Zhao, Q and Xu, J and Li, D and Wu, X and Zhang, K and Chu, C and Fan, L},
title = {Abstract Property-selective Clusters Link Continuous Property Representations to Discrete Category-selective Regions in Human Higher Visual Cortex.},
journal = {Journal of cognitive neuroscience},
volume = {},
number = {},
pages = {1-18},
doi = {10.1162/JOCN.a.2720},
pmid = {42748101},
issn = {1530-8898},
support = {2021ZD0200200//STI2030-Major Projects/ ; 82472061//Natural Science Foundation of China/ ; 7262231//Beijing Natural Science Foundation/ ; 2025GGXM005//Chongqing Science and Health Joint Medical Research Key Project/ ; //Yantai "Double Hundred Plan" Talent Grant/ ; },
abstract = {Object representations in the human higher visual cortex (HVC) support complex recognition behaviors early in development, yet the principles linking continuous dimensional representations and discrete category-selective areas in the HVC remain incompletely understood. Here, we propose a "property-cluster-category" organization that bridges object conceptual dimensions and discrete category areas in the HVC. Using a large-scale naturalistic stimulus data set and voxel-wise encoding methods, we analyzed the encoding patterns of a low-dimensional abstract property space and identified distinct brain clusters with shared cortical property profiles. These clusters broadly aligned with category-selective areas, suggesting that category regions can be understood as local peaks within a continuous property topology. We further tested whether this visual organization could emerge in a visual-only Topographic Deep Artificial Neural Network trained without semantic supervision. The model recapitulated property tuning for physical and biological dimensions but showed weaker affective tuning, suggesting that affective dimensions may require embodied or nonvisual experience. Finally, model-based lesion and stimulation analyses showed that Topographic Deep Artificial Neural Network units aligned with brain clusters contributed selectively to object classification. Together, these results provide a framework for understanding how the continuous property topology and discrete category selectivity are jointly organized in the human HVC, and suggest that abstract visual properties-which shape this topological organization-can be learned in part from statistical regularities in visual input.},
}

@article {pmid42749210,
year = {2026},
author = {Liu, X and Li, M and Hu, Z and Yang, J},
title = {Baseline cortisol level moderated the effect of stress on associative memory: Pre-encoding and pre-retrieval manipulations.},
journal = {Neurobiology of learning and memory},
volume = {},
number = {},
pages = {108219},
doi = {10.1016/j.nlm.2026.108219},
pmid = {42749210},
issn = {1095-9564},
abstract = {Stress has powerful effects on memory, but previous studies have yielded mixed findings regarding its impact on associative memory and the relationship between cortisol response and memory performance. Whether stress affects both encoding and retrieval of associative memory through a common mechanism remains unclear. In addition, an individual's baseline cortisol level should be considered to clarify the cortisol reactivity - memory relationship. In this study, we recruited 63 participants for Experiment 1 and 56 participants for Experiment 2 to learn unrelated word pairs with negative and neutral valence and complete an associative recognition task. They were exposed to a stress or control condition before either the encoding phase (Experiment 1) or the retrieval phase (Experiment 2). The results showed that pre-retrieval stress significantly impaired associative memory. For pre-encoding stress, the group difference was not significant, but stress significantly predicted the corrected recognition and FA rate in the regression analysis. Regardless of whether stress was induced at pre-encoding or pre-retrieval, cortisol reactivity positively predicted the false alarm (FA) rate, while baseline cortisol levels negatively predicted the FA rate. In addition, baseline cortisol levels moderated the effect of stress on memory performance. When the baseline cortisol levels were lower, a greater cortisol reactivity was associated with a higher FA rate in both experiments. These results suggest that stress impairs the ability to distinguish old memories from lures, which is a common mechanism across memory phases. They also highlight the role of baseline cortisol in moderating the relationship between cortisol reactivity and associative memory.},
}

@article {pmid42749481,
year = {2026},
author = {Jaikumar, V and Rifkin, LS and Wahlig, PM and Morioka, TPT and Goyal, AD and Rupp, J and Stockman, IG and Levy, L and Przepiorka, L and Monteiro, A and Lim, J and Vakharia, K and Lai, PMR and Davies, JM and Snyder, KV and Levy, EI and Siddiqui, AH},
title = {Atlas self-expandable stents versus low profile visualized intraluminal support stents for intracranial aneurysm coiling assistance: systematic review and meta-analysis.},
journal = {Journal of neurointerventional surgery},
volume = {},
number = {},
pages = {},
doi = {10.1136/jnis-2026-025664},
pmid = {42749481},
issn = {1759-8486},
abstract = {BACKGROUND: Neurointerventionalists performing stent assisted coil embolization for intracranial aneurysms use Neuroform Atlas stents (Stryker) for their low metal coverage, deployment ease, and lower thromboembolic risk, although low profile visualized intraluminal support (LVIS) and LVIS Jr stents (Terumo Neuro) offer better wall apposition and high metal coverage, potentially promoting flow diversion and endothelialization. The next generation LVIS Evolution (LVIS EVO; Terumo Neuro) adds enhanced visibility, improved resheathability, and even higher metal coverage to address earlier limitations of LVIS and LVIS Jr. We evaluated the performance and complications of these devices.

METHODS: PubMed and Embase were searched from 1 January 2017 to 31 July 2025 to identify studies comparing Atlas assisted coil embolization (AACE) versus LVIS/LVIS Jr assisted coil embolization (LACE), and single arm LVIS EVO assisted coil embolization (LeACE) studies. Meta-analyses were performed to compare baselines, procedural considerations, and occlusion rates.

RESULTS: We included five studies comparing 504 patients treated with AACE and 579 patients with LACE, and 12 studies evaluating LeACE (575 patients). Fewer aneurysms were ruptured at presentation in the AACE group than in the LACE (OR 0.09; P<0.01) and LeACE (0.7% vs 15.2%; P<0.01) groups. Comparable technical failure rates were found between AACE and LeACE (1.8% vs 5.4%; P=0.15), contrasting with the superiority of AACE over LACE (OR 0.14; P<0.01). AACE resulted in higher immediate adequate occlusion than LACE (OR 1.62; P=0.02), but comparable with LeACE (83% vs 90.8%; P=0.28). Follow-up complete occlusion rates were similar between AACE and LACE (OR 1.31; P=0.16) and between AACE and LeACE (82.4% vs 81.2%; P=0.86).

CONCLUSIONS: The superior outcomes of the Atlas over LVIS/LVIS Jr were matched by the LVIS EVO. Thromboembolic complications occurred more frequently with the LVIS EVO.},
}

@article {pmid42749849,
year = {2026},
author = {Li, D and Cui, G and Yang, K and Lu, C and Jiang, Y and Zhang, L and Wu, Q and Dixit, D and Zhu, Z and Gimple, RC and Gu, D and Gao, J and Lin, Q and Yu, H and Shi, Z and Chen, Y and Wang, Q and Jin, G and Lin, F and Shao, J and Zhou, Q and Liu, C and Li, C and You, Y and Zhang, N and Zhang, J and Qian, X and Zhang, Q and Rich, JN and Wang, X},
title = {Author Correction: Inhibiting macrophage-derived lactate transport restores cGAS-STING signalling and enhances antitumour immunity in glioblastoma.},
journal = {Nature cell biology},
volume = {},
number = {},
pages = {},
doi = {10.1038/s41556-026-02083-8},
pmid = {42749849},
issn = {1476-4679},
}

@article {pmid42750660,
year = {2026},
author = {Chetty, N and Bennett, J and Schone, HR and Fry, A and Yoo, PE and Lacomis, D and Oxley, TJ and Collinger, JL and Putrino, DF and Weber, DJ},
title = {Measuring motor intent for BCI control-A comparative analysis of signal quality of simultaneously recorded vECoG and scalp EEG.},
journal = {Journal of neural engineering},
volume = {23},
number = {5},
pages = {},
pmid = {42750660},
issn = {1741-2552},
mesh = {Humans ; *Brain-Computer Interfaces/standards ; *Electroencephalography/methods/standards/instrumentation ; *Scalp/physiology ; Male ; *Electrocorticography/methods/standards/instrumentation ; *Intention ; Female ; Movement/physiology ; },
abstract = {Objective.Stent-electrode arrays enable endovascular brain-computer interfaces (BCI) by recording cortical neural activity from within the superior sagittal sinus and have recently been evaluated in an early feasibility clinical trial in the United States (ClinicalTrials.gov: NCT05035823). For a BCI to be viable, the signals need to be high quality to enable accurate decoding of user intent. Compared to electrodes placed on the scalp for electroencephalography (EEG), stent-electrode arrays lie closer to the cortical surface and would presumably offer higher signal quality yet a direct comparison of intravascular and scalp-based neural recordings in humans has not yet been investigated.Approach.We directly compared the signal quality of vascular electrocorticography (vECoG) versus scalp EEG signals in one participant with severe upper limb paralysis due to ALS. During two experimental sessions, the participant underwent simultaneous recording with the stent-electrode array and a scalp EEG using a gel cap. The participant was visually cued to attempt motor tasks, such as repeated flexion and extension of the ankles. Signal quality was assessed by quantifying motor modulation strength, differentiation of movement effort, and spatial lateralization. Noise metrics evaluated the relative impact of artifacts including 60 Hz line noise, electrocardiogram contamination, eye blinks, jaw clenching, and vocalization.Main results.Both recording modalities exhibited significant modulation during attempted movement relative to rest, with vECoG generally demonstrating significantly stronger modulation per channel in some frequency bands and conditions. Motor modulation was significantly reduced during motor imagery compared to overt movement in both modalities. Spatial source localization between left and right ankle movement did not reach significance for either modality. Each modality was vulnerable to some artifacts while generally unaffected by others. Scalp EEG showed large susceptibility to ocular artifacts and cranial muscle activity due to its proximity to superficial physiological sources, whereas vECoG exhibited prominent cardiac activity.Significance.Within this participant, the large modulation during attempted movement recorded with vECoG, unaffected by the attenuating effects of the skull, coupled with fewer artifacts in the frequency bands of interest, provides preliminary evidence that the stent-electrode arrays can acquire high quality neural signals that could support BCI control.},
}

Humans
*Brain-Computer Interfaces/standards
*Electroencephalography/methods/standards/instrumentation
*Scalp/physiology
Male
*Electrocorticography/methods/standards/instrumentation
*Intention
Female
Movement/physiology

@article {pmid42751287,
year = {2025},
author = {ElSayed, Z and Westerkamp, G and Liu, JY and Pedapati, E},
title = {Brian Intensify: An Adaptive Machine Learning Framework for Auditory EEG Stimulation and Cognitive Enhancement in FXS.},
journal = {2025 3rd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)},
volume = {2025},
number = {},
pages = {},
doi = {10.1109/AIBThings66987.2025.11296220},
pmid = {42751287},
support = {R01 HD108222/HD/NICHD NIH HHS/United States ; },
abstract = {Neurodevelopmental disorders such as Fragile X Syndrome (FXS) and Autism Spectrum Disorder (ASD) are characterized by disrupted cortical oscillatory activity, particularly in the alpha and gamma frequency bands. These abnormalities are linked to deficits in attention, sensory processing, and cognitive function. In this work, we present an adaptive machine learning-based brain-computer interface (BCI) system designed to modulate neural oscillations through frequency-specific auditory stimulation to enhance cognitive readiness in individuals with FXS. EEG data were recorded from 38 participants using a 128-channel system under a stimulation paradigm consisting of a 30-second baseline (no stimulus) followed by 60-second auditory entrainment episodes at 7Hz, 9Hz, 11Hz, and 13Hz. A comprehensive analysis of power spectral features (Alpha, Gamma, Delta, Theta, Beta) and cross-frequency coupling metrics (Alpha-Gamma, Alpha-Beta, etc.) was conducted. The results identified Peak Alpha Power, Peak Gamma Power, and Alpha Power per second per channel as the most discriminative biomarkers. The 13Hz stimulation condition consistently elicited a significant increase in Alpha activity and suppression of Gamma activity, aligning with our optimization objective. A supervised machine learning framework was developed to predict EEG responses and dynamically adjust stimulation parameters, enabling real-time, subject-specific adaptation. This work establishes a novel EEG-driven optimization framework for cognitive neuromodulation, providing a foundational model for next-generation AI-integrated BCI systems aimed at personalized neurorehabilitation in FXS and related disorders.},
}

@article {pmid42751597,
year = {2026},
author = {Akhter, J and Nazeer, H and Naseer, N},
title = {fNIRS dataset of motor hand-gripping activity using the NIRSport2 system.},
journal = {Neurophotonics},
volume = {13},
number = {Suppl 3},
pages = {S32604},
pmid = {42751597},
issn = {2329-423X},
abstract = {SIGNIFICANCE: The functional near-infrared spectroscopy (fNIRS) dataset acquired with the NIRSport2 device provides noninvasive recordings. The analysis of the fNIRS dataset can be used to refine existing models or propose new models to understand the motor cortex during voluntary motor activities, such as neuroplasticity and task-specific neural activation patterns.

AIM: The hand-gripping dataset provides open-access fNIRS recordings of motor task-related brain activity to support the development and refinement of signal processing and machine learning models in brain-computer interface (BCI) research.

APPROACH: Twenty healthy right-handed participants' fNIRS data is acquired during a hand-gripping task from the motor cortex using an 8 × 8 optodes configuration (twenty channels) following the international 10 / 20 system. The NIRSport2 device (NIRx Medizintechnik GmbH, Germany) is used to record hemodynamic cortical activity with a sampling frequency of 10.1725 Hz in the form of light intensity. Signal processing software nirsLAB (version: v201904_64bit) is used for preprocessing and converting the light intensity into optical density, which is then converted into hemoglobin concentration changes (oxy- and deoxyhemoglobin) and finally filtered out for physiological artifacts, consistent with our previous work on this dataset.

RESULTS: This dataset is intended to explore patterns of brain activation during hand gripping, contributing to research on rehabilitation, motor learning, and neuroplasticity, and could be used to develop and validate classification algorithms, contributing to the field of BCI.

CONCLUSIONS: These results demonstrate that the dataset is reliable and suitable for motor task analysis, benchmarking, and fNIRS-based machine learning studies.},
}

@article {pmid42743863,
year = {2026},
author = {Güner Yılmaz, ÖZ and Duranlar, Ö and Yılmaz, A and Çetin, S and Torkay-Çay, G and Özdemir-Kumral, ZN and Bal-Öztürk, A and Açma, H and Yaman, S and Güner, FS},
title = {Injectable biochar-reinforced alginate hydrogels for hemostasis under wet and deformable conditions.},
journal = {Colloids and surfaces. B, Biointerfaces},
volume = {269},
number = {},
pages = {116172},
doi = {10.1016/j.colsurfb.2026.116172},
pmid = {42743863},
issn = {1873-4367},
abstract = {Uncontrolled bleeding under wet and deformable conditions remains a major challenge for conventional hemostatic materials, which often suffer from limited tissue adhesion and poor mechanical adaptability. Here, we developed an injectable sodium alginate hydrogel ionically cross-linked with Ca[2][+] and reinforced with hazelnut branch-derived biochar (HB) to improve structural stability and local hemostatic performance. The HB-containing hydrogel exhibited pronounced shear-thinning behavior, high injectability, enhanced wet tissue adhesion, and self-healing efficiency exceeding 80%, while achieving an adhesive strength of approximately 420 kPa. Physicochemical characterization indicated homogeneous HB incorporation and Ca[2][+] retention by HB, which may influence the local ionic environment of the hydrogel network. In vitro studies demonstrated good cytocompatibility and hemocompatibility. In hemostatic assays, 6A7C-HB exhibited a blood clotting index (BCI) of 4.45%, markedly lower than that of the commercial oxidized cellulose hemostat Surgicel® (26.98%), and shortened the clotting time to 4.4 min compared with 7.5 min for the untreated blood control and 7.2 min for Surgicel®. In vivo evaluation in rat tail transection and liver injury models showed effective hemorrhage control, reducing blood loss by approximately 45-55% compared with untreated controls, while subcutaneous implantation demonstrated acceptable biocompatibility without evidence of significant systemic toxicity or adverse histopathological responses. These findings demonstrate that HB reinforcement provides a simple and effective strategy for developing injectable alginate hydrogels with improved mechanical adaptability and localized hemostatic performance under wet and deformable conditions.},
}

@article {pmid42743888,
year = {2026},
author = {Denost, Q and Rouanet, P and Teruel, E and Borg, C and Lelong, B and Etienne, PL and Maingon, P and Rio, E and Tuech, JJ and Noiret, B and Nougaret, S and Pezzela, V and Gourgou, S and Conroy, T and , },
title = {Oncological impact of adjuvant chemotherapy after rectal cancer excision in the era of FOLFIRINOX-based TNT: A pooled post-hoc analysis of GRECCAR4-PRODIGE23.},
journal = {European journal of cancer (Oxford, England : 1990)},
volume = {247},
number = {},
pages = {117046},
doi = {10.1016/j.ejca.2026.117046},
pmid = {42743888},
issn = {1879-0852},
abstract = {BACKGROUND: The role of adjuvant chemotherapy (AC) after total neoadjuvant therapy (TNT) for locally advanced rectal cancer (LARC) remains controversial, mainly based on colon cancer protocols, with recent validation of the equivalence of the 3- and 6-month CT regimens. The aim of this study is to evaluate the oncological impact of AC in the era of TNT in patients with LARC.

METHODS: We conducted a post hoc analysis of ypN+ and ypN0/cN+ subgroups from two French multicentre randomized trials GRECCAR 4(NCT01333709) and PRODIGE 23(NCT01804790). Patients received either long-course chemoradiotherapy (CRT) or TNT with FOLFIRINOX 4-6 cycles followed by CRT.In each subgroup, outcomes of patients who received AC (AC+) were compared with those who did not(AC-).The primary outcome was 3-year Disease-free survival(DFS).Secondary endpoints included 3-year overall survival(OS),distant metastasis and local recurrence free-survival(3y-DMFS and 3y-LRFS). Survivals were adjusted on propensity score.

RESULTS: Among 489 patients were eligible, 152 AC- (25ypN+ and 127ypN0/cN+)vs 337 AC+ (119 ypN+ and 218 ypN0/cN+).Baseline tumor characteristics were similar. Median follow-up was 70 months. Overall 3y-DFS was 77% and was significantly improved in AC+ group for ypN+ after CRT (p < 0.001), but not after TNT. For ypN0/cN+, no statistically significant association was observed regarding the 3y-DFS whatever the neoadjuvant treatment,TNT (p = 0.33) or CRT (p = 0.45).Similarly, the AC+ group had a significantly better 3y-OS (p < 0.001), 3y-DMFS (p ≤ 0.001) and 3y-LRFS (p ≤ 0.001) for ypN+ after CRT, but not after TNT. For ypN0/cN+, there was no significant difference between the 2 groups regarding 3y-OS(p = 0.74), 3y-DMFS(p = 0.72) and 3y-LRFS(p = 0.71),whatever the neoadjuvant treatment.

CONCLUSIONS: Adjuvant chemotherapy was associated with significantly improved oncological outcomes in ypN+ patients after CRT, whereas no significant association was observed after TNT, irrespective of nodal status. These findings may support de-escalation of adjuvant therapy in the TNT era and inform a more individualised postoperative strategy.},
}

@article {pmid42744316,
year = {2026},
author = {Riveros-Matthey, CD and Connick, MJ and Lichtwark, GA and Carroll, T},
title = {Cycling cadence selections at different saddle heights minimize muscle activation rather than energy cost.},
journal = {Journal of the Royal Society, Interface},
volume = {23},
number = {242},
pages = {},
doi = {10.1098/rsif.2026.0006},
pmid = {42744316},
issn = {1742-5662},
support = {CHILE/2018-72190123//Chilean National Agency for Research and Development/ ; FT190100129//Australian Research Council Future Fellowship/ ; },
mesh = {*Energy Metabolism/physiology ; Humans ; *Muscle, Skeletal/physiology ; *Bicycling/physiology ; Male ; Oxygen Consumption/physiology ; Muscle Fatigue/physiology ; },
abstract = {Unlike walking and running, people do not consistently choose cadences that minimize energy consumption when cycling. This suggests either that the neural control system for locomotion relies on indirect sensorimotor cues to energetic cost that are approximately accurate during walking but not cycling, or that an alternative objective function applies that correlates with energy expenditure in walking but not cycling. This study compared how objective functions derived as proxies to (i) energy cost or (ii) an avoidance of muscle fatigue predicted self-selected cycling cadences (SSC) at different saddle heights. Saddle height systematically affected SSC, with lower saddles increasing SSC and higher saddles decreasing SSC (n = 12). Both fatigue-avoidance and energy-expenditure cost functions derived from muscle activation measurements showed minima that closely approximated the SSCs. By contrast, metabolic power derived from VO2 uptake was minimal at cadences well below the SSC across all saddle height variations. The mismatch between the cadence versus muscle activation and the cadence versus metabolic energy relations is probably owing to additional energy costs associated with performing mechanical work at higher cadences. The results suggest that the nervous system places greater emphasis on muscle activation than on energy consumption for action selections in cycling.},
}

*Energy Metabolism/physiology
Humans
*Muscle, Skeletal/physiology
*Bicycling/physiology
Male
Oxygen Consumption/physiology
Muscle Fatigue/physiology

@article {pmid42744781,
year = {2026},
author = {Depannemaecker, D and d'Hollande, A and Casagrande, G and Wu, J and Rozenberg, MJ},
title = {A minimal model of working memory in neural systems and neuromorphic circuits.},
journal = {Nature communications},
volume = {17},
number = {1},
pages = {},
pmid = {42744781},
issn = {2041-1723},
support = {SGA 101147319//EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)/ ; ANR-23-CE30-0040//Agence Nationale de la Recherche (French National Research Agency)/ ; AWARD # DE-SC0019273//US Department of Energy/ ; },
mesh = {*Models, Neurological ; *Neurons/physiology ; *Neural Networks, Computer ; *Memory, Short-Term/physiology ; *Nerve Net/physiology ; Action Potentials/physiology ; Animals ; Computer Simulation ; Humans ; },
abstract = {Phenomenological spiking neuron models such as Izhikevich, adaptive quadratic integrate-and-fire (aQIF), and Adaptive Exponential (AdEx) are widely used because of their simplicity and numerical efficiency. These models reproduce diverse neuronal dynamics through a slow self-inhibitory adaptation variable. Here we introduce their symmetric counterpart by replacing adaptation with slow self-excitation, motivated by intrinsic calcium-mediated membrane currents. This minimal modification enables robust persistent spiking and working-memory dynamics without compromising computational efficiency. These properties remain in excitatory spiking neural networks. We then derive and validate a mean-field neural mass model that remains stable while retaining working-memory functionality. Additionally, we implement the single-neuron model in a minimal memristor-based neuromorphic circuit and experimentally confirm its dynamics. These results provide scalable tools for large-scale brain simulations and neuromorphic applications in robotics, brain-machine interfaces, and edge AI devices.},
}

*Models, Neurological
*Neurons/physiology
*Neural Networks, Computer
*Memory, Short-Term/physiology
*Nerve Net/physiology
Action Potentials/physiology
Animals
Computer Simulation
Humans

@article {pmid42744792,
year = {2026},
author = {Rajeswaran, P and Payeur, A and Lajoie, G and Orsborn, AL},
title = {Assistive algorithms influence neural representations in motor brain-computer interfaces.},
journal = {Nature communications},
volume = {17},
number = {1},
pages = {},
pmid = {42744792},
issn = {2041-1723},
support = {898220//Simons Foundation/ ; 898220//Simons Foundation/ ; 898220//Simons Foundation/ ; 898220//Simons Foundation/ ; K12HD073945//U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)/ ; NS134634//U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)/ ; Accelnet INBIC fellowship//National Science Foundation (NSF)/ ; IVADO postdoctoral fellowship//Canada First Research Excellence Fund (Fonds d'excellence en recherche Apog&ée Canada)/ ; RGPIN-2018-04821//Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (NSERC Canadian Network for Research and Innovation in Machining Technology)/ ; R01 NS134634/NS/NINDS NIH HHS/United States ; },
mesh = {Animals ; *Brain-Computer Interfaces ; *Motor Cortex/physiology ; *Algorithms ; Macaca mulatta ; Neurons/physiology ; Neural Networks, Computer ; Learning/physiology ; Male ; Movement/physiology ; Models, Neurological ; },
abstract = {Task errors are used to learn and refine motor skills. We investigated how task assistance influences learned neural representations using Brain-Computer Interfaces (BCIs), which map neural activity into movement via a decoder. We analyzed motor cortex activity as monkeys practiced BCI with a decoder that adapted to improve or maintain performance over days. Over time, task-relevant information became concentrated in fewer neurons, unlike with fixed decoders. At the population level, task information also became largely confined to a few neural modes that accounted for a small fraction of the population variance. A neural network model suggests the adaptive decoders directly contribute to forming these more compact neural representations. Our findings suggest that assistive decoders manipulate error information used for long-term learning computations like credit assignment, which may explain the altered neural representations and inform real-world BCI design.},
}

Animals
*Brain-Computer Interfaces
*Motor Cortex/physiology
*Algorithms
Macaca mulatta
Neurons/physiology
Neural Networks, Computer
Learning/physiology
Male
Movement/physiology
Models, Neurological

@article {pmid42747931,
year = {2026},
author = {Shaikh, UQ and Kalra, AM and Lowe, A and Niazi, IK},
title = {SPAR-EEG: Selective Pass-Wise Artifact Reduction for Wearable Single-Channel EEG Denoising.},
journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TNSRE.2026.3734253},
pmid = {42747931},
issn = {1558-0210},
abstract = {Single-channel electroencephalography (EEG) is attractive for wearable neurotechnology and brain-computer interface (BCI) applications, including assistive interfaces and clinical monitoring, but artifact suppression is difficult when auxiliary channels, artifact labels, or user-selected clean baseline segments are unavailable. We introduce SPAR-EEG, a self-contained framework for Selective Pass-wise Artifact Reduction in single-channel EEG. The framework applies three artifactspecific attenuation passes to each EEG epoch: a variational mode decomposition (VMD)-based pass for high-frequency electromyo-graphic (EMG) bursts, a singular spectrum analysis (SSA)-based pass for blink-like electrooculographic (EOG) transients, and an SSA-based pass for slow motion-related drift. Rather than rejecting components globally, each pass estimates artifact-dominant regions and attenuation strength directly from the input channel. SPAR-EEG was evaluated using controlled EEGdenoiseNet and PhysioBank benchmarks, pass ablations, task-locked event-related potential (ERP) preservation, runtime diagnostics, dry-electrode exercise EEG, and a downstream rapid serial visual presentation (RSVP)/P300 speller task using only FP1 and FP2. Across 26 EEGdenoiseNet input signal-to-noise ratio (SNR) levels, it obtained the largest average artifact-region SNR improvement among the tested wavelet, empirical mode decomposition (EMD), and artifact-label-guided wavelet quantile normalization (WQN) baselines for EMG, EOG, and combined EOG+EMG contamination (9.05, 8.28, and 8.00 dB, respectively). In exercise EEG, denoising reduced high-amplitude artifact burden and increased alpha and steady-state visual evoked potential (SSVEP) spectral-prominence metrics. In the P300 validation, the full SPAR-EEG sequence increased repetition-curve area under the curve (AUC) by 0.048 (Holm-adjusted p = 0.0069) and improved final Letter@15 accuracy by 7.8 percentage points. These results suggest that artifact-specific selective attenuation can provide a practical self-contained alternative for single-channel EEG denoising in low-burden and movement-prone settings.},
}

@article {pmid42747938,
year = {2026},
author = {Han, Y and Ke, Y and Ming, D},
title = {Calibration-Efficient Dual-Frequency SSVEP-BCI for Head-Mounted AR-Based UAV Control.},
journal = {IEEE journal of biomedical and health informatics},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/JBHI.2026.3734494},
pmid = {42747938},
issn = {2168-2208},
abstract = {Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) integrated with head-mounted augmented reality (AR) enable wearable, intuitive interaction, yet two fundamental issues limit practical adoption: (i) the role of different dual-frequency stimulation paradigms in head-mounted optical see-through displays is not systematically understood, and (ii) calibration-efficient decoding under multi-target settings remains challenging. This study presents a 16-target AR-SSVEP-BCI on HoloLens 2 and conducts a controlled comparison between a conventional single-frequency paradigm and three dual-frequency binocular paradigms derived from joint frequency-phase modulation. To address calibration burden, we propose a calibration-efficient encoding-decoding framework that leverages a row-column encoding strategy and a row-column decoding strategy with a task-related component analysis (TRCA)-based ensemble spatial filtering scheme, enabling reuse of shared frequency-phase components across targets. In offline evaluations, the best-performing right-and-left field dual-frequency and phase modulation paradigm achieved an average information transfer rate of 99.79 ± 18.96 bits/min with only five calibration blocks. Building on this paradigm, we developed an online AR-SSVEP-BCI with a training-free dynamic stopping strategy and a control-state detection module for asynchronous decision making. In online tasks, under the optimal world-referenced mode, the system reached 89.32 ± 8.43% accuracy in a 16-target Random Cue Task and 95.13 ± 4.39% accuracy in an 8-command Unmanned Aerial Vehicle (UAV) Control Task, demonstrating robust, calibration-efficient multi-command control. These findings provide practical guidance for designing calibration-efficient, wearable AR-SSVEP BCIs that can support accessible assistive control-an important step toward real-world applications.},
}

@article {pmid42740182,
year = {2026},
author = {Peksa, J},
title = {Dataset Fragmentation, Cognitive Variability, and Reproducibility Challenges in EEG-Based Brain-Computer Interfaces: A PRISMA-Based Systematic Review.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740182},
issn = {1424-8220},
mesh = {Humans ; *Brain-Computer Interfaces ; *Electroencephalography ; Reproducibility of Results ; *Cognition/physiology ; },
abstract = {Public EEG-based brain-computer interface (BCI) datasets are expanding rapidly, yet differences in sensors, experimental protocols, task/event semantics, preprocessing, participant context, and evaluation limit reproducibility and cross-dataset learning. This review examined whether heterogeneous EEG-BCI resources can support reproducible analysis across sources. A PRISMA-based systematic mapping review of literature published from 2014 to June 2026 was conducted across Scopus, Web of Science Core Collection, IEEE Xplore, PubMed, and ACM Digital Library, yielding 16,920 records. Following screening and evidence-focused curation, a curated synthesis corpus of 129 publications was retained and confirmed by full-text review. Evidence was coded across structural, semantic, procedural, human/contextual, and computational fragmentation, and reporting transparency was assessed using ten criteria. The synthesis identified heterogeneity in acquisition, channel layouts, task/event definitions, preprocessing, participant/session context, and evaluation design. Existing standards, ontologies, software platforms, benchmark frameworks, and transfer-learning methods address complementary layers but do not provide complete semantic interoperability. Within the retained corpus, the median transparency score was 9/10; data availability was stated in 61.2% and code or pipeline availability in 20.9%. These frequencies describe the curated corpus rather than the field as a whole. Scalable cross-dataset analysis requires analysis-dependent compatibility rules, explicit provenance, contextual metadata, and auditable transformations that preserve dataset identity, uncertainty, and information loss.},
}

Humans
*Brain-Computer Interfaces
*Electroencephalography
Reproducibility of Results
*Cognition/physiology

@article {pmid42740196,
year = {2026},
author = {Röhrling, L and Breuer, S and Arnberger, C and Aigner, C and Grechenig, T and Baranyi, R},
title = {Motor Imagery Acquisition and Classification Using a Low-Cost 8-Channel EEG System in a VR ADHD Serious Game Environment: A Case Study.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740196},
issn = {1424-8220},
mesh = {Humans ; *Electroencephalography/methods ; *Attention Deficit Disorder with Hyperactivity/physiopathology ; Brain-Computer Interfaces ; *Video Games ; *Virtual Reality ; Signal Processing, Computer-Assisted ; },
abstract = {Attention-deficit/hyperactivity disorder (ADHD) involves difficulties in sustaining attention and resisting distraction. This has motivated the development of feedback-driven environments for cognitive control training. Integrating electroencephalography (EEG) sensors into Virtual Reality (VR) serious games for cognitive therapy remains relatively underexplored and requires reliable, non-invasive brain-computer interfaces. The existing solutions use multi-channel systems that primarily suffer from requiring complex hardware, while not combining motor imagery (MI) with concentration levels. Therefore, this case study evaluates the feasibility and data quality of a lightweight, cost-effective sensor configuration for real-time control of mental state. A non-invasive, eight-channel OpenBCI Cyton board was integrated with an EEG cap using the international 10-20 placement system, alongside a Meta Quest 2 headset, to capture MI and concentration signals directly from the user's scalp. Signal acquisition was hindered by high impedance and channel railing, which required conductive gel mitigation, while mechanical tension from the VR headset strap introduced motion artifacts and noise. Nevertheless, under stable signal conditions, the optimized eight-channel sensor setup achieved a subject-specific online classification accuracy of up to 90% using the deep learning model "EEGNet". The findings demonstrate the technical feasibility of acquiring and classifying EEG activity using a low-cost eight-channel sensor configuration in an interactive VR-BCI Serious Gaming application, provided that skin-electrode impedance and mechanical sensor interferences are managed. The results provide a basis for future investigation of such systems in cognitive-training applications, while further studies, including clinical evaluations, are required to assess their applicability in therapeutic contexts.},
}

Humans
*Electroencephalography/methods
*Attention Deficit Disorder with Hyperactivity/physiopathology
Brain-Computer Interfaces
*Video Games
*Virtual Reality
Signal Processing, Computer-Assisted

@article {pmid42740237,
year = {2026},
author = {Mokienko, O and Lukyanov, E and Kim, L and Isaev, M and Gabuzov, G and Bobrov, D and Lyukmanov, R and Suponeva, N and Ustinova, K and Bobrov, P},
title = {EEG vs. Hybrid EEG-fNIRS BCI for FES Control in Healthy Subjects: A Blind Randomized Study and an Open Dataset.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740237},
issn = {1424-8220},
support = {125022602910-2.//Ministry of Health of the Russian Federation/ ; },
mesh = {Humans ; *Brain-Computer Interfaces ; *Electroencephalography/methods ; Male ; Adult ; Spectroscopy, Near-Infrared/methods ; Female ; *Electric Stimulation ; Algorithms ; Healthy Volunteers ; Young Adult ; },
abstract = {Among the various brain-computer interface (BCI) modifications used in post-stroke rehabilitation, BCI systems combined with functional electrical stimulation (FES) are considered the most effective. As a preliminary step toward optimizing such systems for clinical application, it remains unclear whether using electroencephalography (EEG) alone versus a hybrid EEG and functional near-infrared spectroscopy (fNIRS) approach affects real-time three-class BCI-FES control performance in healthy individuals. In a blind randomized study, 16 healthy volunteers completed five BCI-FES training sessions across three days. In one group, FES of wrist extensor muscles was driven by a hybrid EEG-fNIRS classifier; in the other, by EEG only. Classification accuracy, sense of agency, attention, and physical comfort were assessed. No statistically significant between-group differences were found in any outcome measure (p > 0.05). Median real-time three-class classification recall was 53.5% in the hybrid group and 57.3% in the EEG-only group. The median agency score reached approximately 75% of the maximum possible value in both groups. Simulation analysis showed comparable accuracy for unimodal fNIRS-only and EEG-only classifiers. Genetic algorithm-based channel selection identified C3 and C4 as the most informative EEG channels, while optimal fNIRS placement required individual optimization. Within the constraints of the classification and fusion pipeline used here, these findings suggest that signal acquisition modality does not significantly influence BCI-FES performance or sense of agency in healthy subjects. The complete EEG-fNIRS dataset is publicly available through NITRC.},
}

Humans
*Brain-Computer Interfaces
*Electroencephalography/methods
Male
Adult
Spectroscopy, Near-Infrared/methods
Female
*Electric Stimulation
Algorithms
Healthy Volunteers
Young Adult

@article {pmid42740363,
year = {2026},
author = {Zhou, T and Qi, Y and Jia, S and Zhang, L and Feng, F and Cui, ZX and Liang, D},
title = {Highly Accelerating Joint Intracranial and Carotid Vessel Wall Imaging Using ESPIRiT-Driven Diffusion Model Reconstruction.},
journal = {Magnetic resonance in medicine},
volume = {},
number = {},
pages = {},
doi = {10.1002/mrm.70567},
pmid = {42740363},
issn = {1522-2594},
support = {62125111//National Natural Science Foundation of China/ ; 62206273//National Natural Science Foundation of China/ ; 62301548//National Natural Science Foundation of China/ ; 62476268//National Natural Science Foundation of China/ ; 2021YFF0501503//National Key Research and Development Program of China/ ; 2022YFA1004203//National Key Research and Development Program of China/ ; 2025A1515010915//Basic and Applied Basic Research Foundation of Guangdong Province/ ; 2024B1212010010//Guangdong Provincial Key Laboratory of Multimodality Non-Invasive Brain-Computer Interfaces/ ; B2502039//Shenzhen Medical Research Fund/ ; JCYJ20240813155840052//Shenzhen Science and Technology Innovation Program/ ; JCYJ20241202124859016//Shenzhen Science and Technology Innovation Program/ ; },
abstract = {PURPOSE: To propose ESPIRiT-Diffusion, a physics-guided score-based diffusion reconstruction framework incorporating multi-set ESPIRiT map-based data-consistency constraints for 8.8- and 10.7-fold accelerated joint intracranial and carotid vessel wall imaging (VWI) with an isotropic resolution of 0.6 mm[3].

THEORY AND METHODS: ESPIRiT-Diffusion exploits the powerful generative capability of the diffusion framework for the reconstruction of large-FOV 3D VWI images, aiming to recover vessel wall details and improve image quality at high acceleration factors. By further incorporating multi-set ESPIRiT coil sensitivity maps into the Langevin equation, it enforces accurate data consistency, thereby improving VWI reconstruction quality while constraining unreliable generation. In addition, diffusion performed directly in the image domain leads to clearer fine details and faster reconstruction.

RESULTS: In retrospective experiments with Cartesian, CAIPI, and variable-density undersampling at acceleration factors of 8.8× and 10.7×, ESPIRiT-Diffusion showed improved reconstruction performance compared with ESPIRiT, DL-ESPIRiT, SENSE-Diffusion, and SPIRiT-Diffusion in the evaluated retrospective experiments, with better preservation of fine vessel wall structures. In prospective patient experiments, ESPIRiT-Diffusion provided favorable visualization of vessel wall lesions, with no statistically significant differences in reader scores from the 3-fold CS reference across either individual vascular segments or Overall comparisons.

CONCLUSIONS: ESPIRiT-Diffusion for VWI reconstruction mitigates some limitations related to instability and sampling-pattern dependence in unfolding-based methods, while also alleviating image blurring and reducing reconstruction time compared with k-space diffusion. As a result, ESPIRiT-Diffusion showed improved reconstruction quality and clearer fine structural details in the evaluated experiments, while reducing the required acquisition time.},
}

@article {pmid42740917,
year = {2026},
author = {Wang, H and Yin, M},
title = {Beyond privacy calculus: public acceptance of non-invasive therapeutic brain-computer interfaces in China.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1904359},
pmid = {42740917},
issn = {2296-2565},
mesh = {Humans ; China ; Female ; *Brain-Computer Interfaces/psychology ; Adult ; Cross-Sectional Studies ; Male ; Surveys and Questionnaires ; Middle Aged ; *Privacy ; Young Adult ; },
abstract = {BACKGROUND AND OBJECTIVE: Non-invasive brain-computer interfaces (BCIs) are rapidly transitioning from laboratory settings to clinical rehabilitation and mental health applications. However, unlike ordinary consumer technologies, therapeutic BCIs are adopted under health imperatives rather than discretionary choice. In such contexts, the "privacy calculus" logic underlying the Value-based Adoption Model (VAM), which assumes users rationally weigh benefits against sacrifices, may not adequately capture adoption decisions. This study aimed to explore the public's acceptance of non-invasive therapeutic BCIs in China, identify influencing factors, and examine the moderating roles of age, monthly income, and disease status.

METHODS: Using a cross-sectional survey design, 337 valid questionnaires were collected from Chinese adults via snowball sampling on the Wenjuanxing online platform. A structural equation model (SEM) incorporating perceived benefit, perceived sacrifice, perceived value, and a second-order latent variable "external drivers" was constructed and tested. Hierarchical regression analysis examined moderation effects.

RESULTS: The mean usage intention score was 3.93 (SD = 0.63). Perceived benefit strongly and positively predicted perceived value (β = 0.951, p < 0.001), while perceived value (β = 0.749, p < 0.001) and external drivers (β = 0.241, p = 0.027) positively predicted usage intention. The negative effect of perceived sacrifice on perceived value was non-significant (β = -0.091, p = 0.061); a post-hoc power analysis confirmed the study was adequately powered (power > 0.99 for a medium effect), suggesting this effect is negligible. Age positively moderated the "perceived sacrifice → perceived value" path (β = 0.118, p < 0.01), with older respondents showing greater tolerance for technological costs.

CONCLUSION: In the context of non-invasive therapeutic BCIs, the negative effect of perceived sacrifice on perceived value was not supported, suggesting that the classic privacy calculus logic may be attenuated when health imperatives are salient. We propose "cost desensitization" as a tentative mechanism warranting further mixed-methods validation research. These findings inform clinical expectation management and ethical governance of emerging neurotechnologies.},
}

Humans
China
Female
*Brain-Computer Interfaces/psychology
Adult
Cross-Sectional Studies
Male
Surveys and Questionnaires
Middle Aged
*Privacy
Young Adult

@article {pmid42742411,
year = {2026},
author = {Zhang, T and Meng, W and Yu, X and Pan, G and Han, R},
title = {SimCP-NS: Similarity-based Copy Paste for Semi-Supervised 3D EM Neuron Segmentation.},
journal = {Bioinformatics (Oxford, England)},
volume = {},
number = {},
pages = {},
doi = {10.1093/bioinformatics/btag560},
pmid = {42742411},
issn = {1367-4811},
abstract = {MOTIVATION: Semi-supervised neuron segmentation in 3D electron microscopy (EM) is important for connectomics because it enables accurate neuron reconstruction while reducing dependence on costly manual annotations. However, existing approaches remain limited by the distribution mismatch between the small labeled dataset and the much larger unlabeled dataset, where the labeled data fails to adequately capture the true data distribution, leading models trained on them to generate low-quality segmentation masks and ultimately degrading overall performance.

RESULTS: To address this issue, we propose a similarity-based copy-paste for semi-supervised 3D EM neuron segmentation (SimCP-NS) method, which employs a similarity-based copy-paste strategy to exchange the least similar labeled and unlabeled sub-volumes, thereby enriching data diversity and mitigating distribution mismatch. A teacher network is first pre-trained on unlabeled volumes to capture structural priors, which subsequently guides the student segmentation network. During student training, the similarity-based copy-paste mechanism generates hybrid samples and constructs supervision targets by fusing teacher-generated pseudo-labels with ground-truth affinity maps, optimized via mean squared error loss. Invariant representation learning is further integrated to enhance robustness of the proposed method. Extensive experiments demonstrate the superior performance of SimCP-NS over existing 3D EM neuron segmentation methods.

SUPPLEMENTARY INFORMATION: Codes and other supporting materials are provided in the Supplementary Material.},
}

@article {pmid42743800,
year = {2026},
author = {Wu, H and Wu, Z and Liu, X},
title = {Mamba-GRN: A Mamba-inspired framework for no-overlap held-out regulatory edge prediction.},
journal = {Computational biology and chemistry},
volume = {126},
number = {Pt 1},
pages = {109369},
doi = {10.1016/j.compbiolchem.2026.109369},
pmid = {42743800},
issn = {1476-928X},
abstract = {Reliable evaluation of gene regulatory network (GRN) inference requires strict separation between training and held-out regulatory edges, particularly for negative edges in sparse networks. We present Mamba-GRN, a compact Mamba-inspired gene representation and edge-decoding framework evaluated under a corrected no-overlap protocol in which validation and test negatives are excluded from the training-negative pool. The implemented encoder combines expression-derived features and learnable gene-identity embeddings with residual blocks composed of layer normalization, linear expansion, depthwise one-dimensional convolution, GELU activation, and linear projection; it does not implement a selective-scan state-space recurrence. Across seven non-tiny GSD datasets and three random seeds, the full model achieved mean AUROC 0.6225, AUPRC 0.4754, and Precision@P 0.4444, compared with 0.5708/0.4022/0.4444 for GENIE3 and 0.5671/0.4446/0.3810 for GRNBoost2. Paired mean improvements over the mature tree-based baselines were positive, but Holm-adjusted Wilcoxon tests did not reach the 0.05 threshold; the revised analysis therefore reports effect estimates, bootstrap confidence intervals, and win rates without claiming universal statistical superiority. Sensitivity analyses showed broadly stable performance across 1:1, 2:1, and 5:1 training-negative ratios, while larger representation dimensions improved mean performance at increased parameter cost. In an independent K562 Perturb-seq benchmark with 2284 aligned genes and 20,795 perturbation-response associations, source-matched hard-negative evaluation yielded AUROC 0.7582 ± 0.0071 and AUPRC 0.6114 ± 0.0124. The pretrained frozen backbone provided only a modest, seed-dependent advantage over a randomly initialized frozen backbone. These results support Mamba-GRN as a controlled framework for held-out edge recovery, while limiting the claims to the evaluated networks, candidate-edge setting, and functional perturbation-response associations.},
}

@article {pmid42729330,
year = {2026},
author = {Fu, K and Li, P and Peng, X and Li, S and Zhao, Y and Chen, X and Ding, Y and Ye, C},
title = {From technological closed-loop to human-machine trust: a systematic review of ethical and communication challenges of brain-computer interface in elderly care.},
journal = {Frontiers in digital health},
volume = {8},
number = {},
pages = {1877688},
pmid = {42729330},
issn = {2673-253X},
abstract = {As the global population ages, brain-computer interfaces (BCIs) have emerged as a promising technological pathway for restoring communication, motor function, and cognitive support in elderly care settings. However, the ethical and communication challenges accompanying BCI deployment in these contexts remain insufficiently understood. This systematic review identified 177 studies meeting the inclusion criteria from 12,423 records. Through comprehensive analysis, six core ethical themes were identified: privacy and data security, informed consent and autonomy, personhood and identity, technical risks and safety, equity and accessibility, and risk-benefit trade-offs. Beyond cataloging these ethical challenges, this review proposes a three-level analytical framework encompassing human-computer interaction, interpersonal communication, and public opinion dissemination to examine how ethical risks manifest as communication breakdowns across the closed-loop BCI process of neural signal acquisition, intention decoding, and external feedback. Furthermore, a three-dimensional mapping integrating ethical issues, communication challenges, and application scenarios (rehabilitation assistance, communication assistance, monitoring and prevention, and emotional support) is constructed to reveal scenario-specific ethical configurations. The findings indicate that BCI's ethical risks are not peripheral but structurally embedded in the technology's interaction logic-decoding uncertainty can translate into care misjudgment, neural data inferability extends privacy risks beyond information leakage to psychological exposure and power asymmetry, and technology-mediated communication creates structural tensions in trust and responsibility. The review concludes that responsible BCI deployment in elderly care requires not merely algorithmic improvement but the systematic engineering of ethical principles into care processes, including uncertainty disclosure at the interface level, data minimization and layered informed consent at the institutional level, and interdisciplinary collaboration with long-term support systems.},
}

@article {pmid42729429,
year = {2026},
author = {Shen, Y and Degras, D},
title = {A confidence-gated source selection strategy for cross-session transfer in brain-computer interfaces.},
journal = {Frontiers in human neuroscience},
volume = {20},
number = {},
pages = {1895016},
pmid = {42729429},
issn = {1662-5161},
abstract = {Cross-session variability remains a major obstacle to the reliable operation of motor imagery (MI)-based brain-computer interfaces (BCI), particularly when systems are reused across multiple days. When multiple prior sessions from the same subject are available, two key questions arise before domain transfer: which source sessions to select and how to effectively utilize them. We address these questions by developing confidence-gated, selective-transfer pipelines: a Minimum-Distance Multi-Source Pipeline (MMP) that only uses source sessions close to the target, and a Bridge Domain Pipeline (BDP) that exploits both near and far sources to improve robustness. We evaluated these novel pipelines against uniform-pooling (MAP) and distance-weighted-pooling (DWP) baseline methods on two public motor imagery EEG datasets under matched experimental configurations of feature extraction, classification, and domain adaptation algorithms. The benchmark results support an endpoint-specific interpretation rather than a single accuracy ranking. Specifically, MAP achieved the highest maximum-configuration accuracy, DWP demonstrated the highest average accuracy across configurations, and on the primary dataset MAP, DWP, and BDP exhibited no statistically significant differences as the top-performing pipelines for data-driven configuration selection. In contrast, MMPmta performed similarly under fixed configurations but proved less effective during data-driven configuration selection. Overall, the best-performing proposed pipeline (BDP) ranks among the highest-performing approaches with respect to accuracy while requiring substantially reduced execution time and fewer source sessions than full pooling-demonstrating that BDP transforms the CI-gated retention idea into a more reliable and computationally efficient framework for automated configuration selection. These results indicate that in cross-session MI decoding, the primary challenge in selective transfer extends beyond session selection alone to encompass how retained sessions are integrated downstream, offering significant implications for longitudinal rehabilitation and assistive BCI use.},
}

@article {pmid42729594,
year = {2026},
author = {Hu, P and Chen, C and Zang, Y and Li, X and Ming, D},
title = {Intracortical Microstimulation in Brain-Computer Interfaces: Evoking Perception and Plasticity.},
journal = {Cyborg and bionic systems (Washington, D.C.)},
volume = {7},
number = {},
pages = {0690},
pmid = {42729594},
issn = {2692-7632},
abstract = {Intracortical microstimulation (ICMS), the activation of specific neuronal populations via microelectrodes implanted in the cortex, has emerged as a key technology for invasive brain-computer interfaces (BCIs). This article reviews the technical foundations and functional applications of ICMS within the BCI field, highlighting its diverse capabilities in both perception construction and targeted neuromodulation, while emphasizing the interface and parameter constraints that shape its long-term use. At the technical level, we analyze the evolution of ICMS microelectrode interfaces from rigid arrays to flexible, biomimetic, and biohybrid strategies, alongside key pulse-train parameters relevant to neural recruitment and application safety. Functionally, we discuss how biomimetic and spatiotemporally patterned ICMS generates high-resolution artificial tactile and visual perception, and how ICMS can serve as learnable information channels to guide behavior. We further consider temporally contingent and closed-loop ICMS as plasticity-based approaches for modulating cortical functional connectivity and pathological network activity in selected experimental models, while noting translational challenges related to stability, scalability, safety, and patient variability. Finally, we extend the discussion to novel biohybrid neural interfaces, including cell-seeded interface modifications, axon-guidance strategies, and stem-cell- and brain-organoid-integrated platforms, which provide a theoretical reference for next-generation biointegrated neuromodulation technologies in BCIs. Together, this review evaluates ICMS in BCIs along 2 central lines: evoking artificial perception and engaging plasticity-based modulation, while highlighting that long-term translation will require coordinated advances in interface reliability, stimulation encoding, closed-loop calibration, safety evaluation, and biohybrid integration.},
}

@article {pmid42730660,
year = {2026},
author = {Huang, Y and Guan, S and Zhang, Y and Peng, F and Guo, T and Yao, J and Li, W and Zhang, L and Zhang, L and Wang, T},
title = {A Multimodal Assay to Infer Body Temperature Set-Point Shifts in Freely Moving Mice.},
journal = {Journal of visualized experiments : JoVE},
volume = {},
number = {235},
pages = {},
doi = {10.3791/71693},
pmid = {42730660},
issn = {1940-087X},
mesh = {Animals ; Mice ; *Body Temperature Regulation/physiology ; *Body Temperature/physiology ; Adipose Tissue, Brown/physiology ; Male ; },
abstract = {Homeothermic animals maintain a stable core body temperature (Tc) at a set-point around 37 °C. Thermoregulatory homeostasis maintains Tc around the set-point, even when ambient temperature varies considerably. While most studies of thermoregulation focus on laboratory animals' systemic responses to changes in ambient temperature, little is known about how the central nervous system controls the Tc set-point. To facilitate such research, we developed an experimental strategy to infer Tc set-point shifts in freely moving mice. The core assay is based on the relationship between Tc and preferred environmental temperature (Tp), measured simultaneously within a thermal gradient apparatus (15-50 °C), thereby enabling evaluation of inferred Tc set-point changes through integrated physiological and behavioral responses in a single experiment. To support the interpretation of inferred set-point shifts, complementary thermoregulatory readouts were incorporated, including brown adipose tissue (BAT) surface temperature (TBAT) as an indirect proxy for thermogenesis and tail skin temperature (Ttail) as a measure of cutaneous heat loss. To demonstrate the utility of this assay, we bidirectionally manipulated the neuronal activity of EP3 receptor-expressing neurons in the medial preoptic area of the hypothalamus (MPA[EP3R] neurons). Chemogenetic activation was performed in hM3Dq-expressing mice (n = 7), whereas inhibition was performed in hM4Di-expressing mice (n = 6). Deschloroclozapine and vehicle treatments were administered using a randomized within-subject design with a 24 h washout interval. Chemogenetic activation of MPA[EP3R] neurons reduced Tc, along with coordinated cold-seeking behavior, reduced thermogenesis, and enhanced heat-loss responses, consistent with an inferred downward shift in the Tc set-point. Conversely, inhibition of these neurons induced warm-seeking behavior, enhanced thermogenesis, and heat-conservation responses, accompanied by elevated Tc, suggesting an inferred upward shift in the Tc set-point. Overall, this strategy provides a practical and reproducible approach for inferring Tc set-point dynamics in mice and will facilitate mechanistic studies of thermoregulation.},
}

Animals
Mice
*Body Temperature Regulation/physiology
*Body Temperature/physiology
Adipose Tissue, Brown/physiology
Male

@article {pmid42730848,
year = {2026},
author = {Wu, X and Huang, Y and Xu, H},
title = {Vagal PIEZO2-Positive Neurons Mediate Blood Volume Sensing and Circulatory Homeostasis Regulation.},
journal = {Neuroscience bulletin},
volume = {},
number = {},
pages = {},
pmid = {42730848},
issn = {1995-8218},
}

@article {pmid42730849,
year = {2026},
author = {Deng, L and Li, F and Song, M},
title = {Speech Brain-Computer Interfaces: A New Pathway for Restoring Communication in Anarthria.},
journal = {Neuroscience bulletin},
volume = {},
number = {},
pages = {},
pmid = {42730849},
issn = {1995-8218},
}

@article {pmid42732314,
year = {2026},
author = {G, A},
title = {Target-Session early stopping for cross-session EEG mental workload classification: a reusable deployment-oriented method.},
journal = {MethodsX},
volume = {17},
number = {},
pages = {104125},
pmid = {42732314},
issn = {2215-0161},
abstract = {Cross-session EEG mental workload classifiers degrade severely when applied to new recording sessions from the same individual. A key but overlooked cause is the model selection criterion: standard within-session validation rewards checkpoints that exploit session-specific noise, systematically selecting against cross-session generalisation. This article describes Target-Session Early Stopping (TSES), a method that replaces the within-session validation set used for early stopping with a small held-out set of 50 labelled epochs from the target session. TSES requires no gradient updates on target-session data, no architectural changes, and no additional hyperparameter tuning. It improves binary cross-session accuracy on all 14 directional transfer pairs tested across three EEG subsets spanning two drift regimes. Combined with a two-sample Kolmogorov-Smirnov drift screen on the same 50 epochs, the complete pre-deployment protocol requires approximately four minutes of dedicated target-session recording. • TSES improved binary cross-session accuracy on all 14 directional transfer pairs tested across three EEG subsets spanning both high-drift (100% feature shift) and low-drift (52% feature shift) conditions. • Target-session early stopping is more data-efficient than calibration fine-tuning, which requires >100 labelled target epochs before showing any benefit under high drift. • Combined with a Kolmogorov-Smirnov drift screen on the same 50 epochs, the complete pre-deployment protocol requires approximately four minutes of dedicated target-session recording.},
}

@article {pmid42732697,
year = {2026},
author = {Zhang, B and Wang, J and Zhu, J and Zhao, W and Yang, D and Ni, G},
title = {Are there distinctive EEG Signatures of tinnitus-related emotional distress? Evidence from spectral parameterization and source-level functional connectivity.},
journal = {Hearing research},
volume = {481},
number = {},
pages = {109807},
doi = {10.1016/j.heares.2026.109807},
pmid = {42732697},
issn = {1878-5891},
abstract = {Subjective tinnitus is the perception of sound in the absence of an external acoustic source. This study used resting-state electroencephalography (EEG) to characterize abnormal neural oscillatory activity and electrophysiological features potentially associated with tinnitus-related emotional distress. Resting-state EEG data were collected from patients with tinnitus and healthy controls. Spectral parameterization was applied to separate aperiodic and periodic components and to extract the alpha center frequency. At the same time, source-level phase-locking value (PLV) was calculated to assess inter-regional functional connectivity. Patients with tinnitus exhibited a significantly higher aperiodic exponent than healthy controls, consistent with altered cortical excitation-inhibition (E/I) balance. In addition, the alpha peak frequency was significantly reduced in temporal regions, indicating slowing of local oscillatory activity within auditory cortical networks. Functional connectivity analysis revealed increased synchronization within and between auditory and parietal regions, accompanied by decreased connectivity involving the auditory regions, the anterior cingulate cortex, and prefrontal regions. These findings suggest that tinnitus is characterized by altered neural oscillatory activity and functional connectivity. These alterations may reflect abnormal auditory-network synchronization and altered cortical dynamics in tinnitus and may represent electrophysiological characteristics associated with tinnitus-related emotional distress that are not fully consistent with some findings previously reported in primary depressive disorders. These results further clarify the neurophysiological basis of tinnitus and may inform future neuromodulatory interventions.},
}

@article {pmid42733633,
year = {2026},
author = {Smutny, Z and Hudec, M and Kožuh, I},
title = {Vision Restoration to People with Long-Term Blindness Using the Brain-Computer Interface Technology: A Sociotechnical Research Framework to Improve Usefulness for Users.},
journal = {Patient preference and adherence},
volume = {20},
number = {},
pages = {615486},
pmid = {42733633},
issn = {1177-889X},
abstract = {Invasive and non-invasive brain-computer interface (BCI) represent a promising technology for treating various diseases and disabilities. BCI-based invasive solutions also include visual prostheses. Currently, there is rapid development of cortical prostheses and bold statements, eg, about the potential of Neuralink's experimental neuroprosthetic Blindsight to restore vision. However, questions arise about the usefulness of such solutions for people with long-term blindness, considering other compensatory aids and referring to the empirical basis of cases where vision has been successfully restored surgically in the past. These cases reveal that biological restoration of sight does not guarantee functional vision. Moreover, technological limitations, such as low-resolution phosphene-based vision, individual variability or postoperative complications, reduce usability and usefulness for potential users. Therefore, we draw on literature on visual prostheses, documented cases of vision restoration, and employ a sociotechnical approach used in design science to discuss aspects that influence the usefulness of the vision restoration to people with long-term blindness, with emphasis on cortical prostheses. This approach emphasises the need to include or inscribe social values into designed BCI solutions to reveal what people with blindness need and what can be achieved with current technology. Research on user values and needs must shape the visual prostheses design, and their functions must be helpful to the user and synergistically complement his or her sociotechnical context (eg, interacting with other used aids and smart environments, or supporting needed social skills). Sociotechnical research can guide iterative design, improve future user acceptance and adoption, align prosthetic development with real-life needs, and prevent users from reverting to life with blindness due to cognitive overload or poor functional adaptation. Thus, we call for systematic and long-term sociotechnical research, which is lacking in this area. For this purpose, a relevant sociotechnical research framework and future research agenda are presented.},
}

@article {pmid42735423,
year = {2026},
author = {Davidson, LS and Uchanski, RM and Geers, AE and Spehar, B},
title = {The Effect of Between-Ear Speech Perception Asymmetry on Localization, Spoken Language, and Literacy for Adolescents With Cochlear Implants.},
journal = {Journal of speech, language, and hearing research : JSLHR},
volume = {},
number = {},
pages = {1-14},
doi = {10.1044/2026_JSLHR-25-01063},
pmid = {42735423},
issn = {1558-9102},
abstract = {PURPOSE: This study aimed to examine the effects of between-ear speech perception asymmetry on localization, spoken language, and reading in adolescents with early cochlear implants (CIs).

METHOD: Eighty adolescents, who have long-term bilateral device use, participated: 10 with bimodal (BM) devices (CI plus hearing aid at the nonimplanted ear) and 70 with bilateral CIs (BCIs; 14 simultaneous, 56 sequential). Participants completed localization, unilateral speech perception, receptive language, and reading tests. Principal component analysis created composite scores for better-ear speech perception and between-ear speech perception asymmetry. Hierarchical regression examined the effects of demographics, audiological factors, and asymmetry on outcomes.

RESULTS: Localization scores for the two BCI groups did not differ significantly. Both BCI groups' localization scores were, however, significantly better than those of the BM group. Language and reading scores were not significantly different for the three groups. Regression analyses of localization scores revealed positive effects for earlier receipt of CI/s and negative effects of longer duration of acoustic experience, although this effect was moderated by degree of residual hearing. Larger speech perception asymmetry negatively affected localization scores but had no effect on language or reading scores.

CONCLUSIONS: Speech perception asymmetry negatively affected localization but not language or reading in adolescent CI users. Prolonged acoustic experience (via BM use) increased speech perception asymmetry and reduced localization skills. Localization skills had no significant effects on spoken language or reading scores in adolescence. Clinically, asymmetry guides device recommendations, but asymmetry's impact, if any, differs by outcome. For children with better residual hearing, early acoustic hearing (via BM use) benefits both localization and language. Thus, careful timing of BCIs is advised.

SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.33490615.},
}

@article {pmid42735699,
year = {2026},
author = {Fink Skular, A and Tostaeva, G and Ho, E and Dister, J and Cummins, DD and Barth, K and Nunez, L and Poole, A and Mermel, CH and Rapoport, BI and Bederson, JB and Saez, I},
title = {Ultra high-density, 4096-channel intraoperative neurophysiological brain mapping for functional localization of the human central sulcus.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/aea70f},
pmid = {42735699},
issn = {1741-2552},
abstract = {Intraoperative localization of the central sulcus (CS) using somatosensory evoked-potential (SSEP) phase reversal is routinely performed with sparse subdural strip electrodes. We evaluated whether a multi-array, 4096-channel surface micro-electrocorticography (μECoG) configuration could provide dense two-dimensional sampling of stimulus-dependent sensorimotor responses within a standard neurosurgical workflow. Approach. Four Precision Neuroscience Layer 7 μECoG arrays (1024 platinum electrodes per array on a flexible polyimide substrate, 400 μm electrode pitch, ~1.5 cm[2] active area per array) were deployed during resection of a right parafalcine meningioma in a 56-year-old male. Two arrays were placed horizontally on the exposed precentral gyrus; two were inserted under the intact dura overlying the postcentral gyrus, using a custom flexible stylet. SSEPs were recorded across five contralateral stimulation conditions (median nerve, ulnar nerve, index finger, middle finger, ring finger). Per-electrode SSEP responses were classified without anatomical labels, and spatial organization was quantified across stimulation conditions. Stimulus-locked high-gamma activity, digit-response maps, and signal quality across micro- and macroelectrodes were also evaluated. Main results. Aggregate channel yield was 91.3% (3739/4096) at a 2 MΩ impedance criterion (per-array range 86.7-97.0%). Per-electrode amplitude maps resolved continuous phase-reversal contours with stimulus-specific spatial structure; reversal latencies were 19, 21, 25, 26, and 25 ms for median, ulnar, index, middle, and ring stimulation respectively. Phase reversal occurred within a single array in eight of ten sensory-array recordings, with the phase-reversal pattern varying across stimulation conditions. Digit responses showed measurable spatial differentiation within substantially overlapping response fields. Automated classification of the phase-reversal responses recovered the expected motor and sensory organization, consistent with the standard-of-care intraoperative localization performed in the same case. Significance. The deployment shows that a four-array Layer 7 μECoG configuration can be used within a standard neurosurgical exposure and provides dense two-dimensional sampling of stimulus-dependent phase-reversal patterns across the peri-Rolandic recording field. The measured responses were correlated across approximately 3-4 mm of cortex, an order of magnitude coarser than the 400 μm electrode pitch, so the contribution demonstrated here is dense spatial sampling rather than submillimeter physiological resolution. Dense sampling rendered the polarity transition as a continuous two-dimensional boundary across the recording field rather than as a reversal between two adjacent contacts. The platform supports future evaluation of high-density surface μECoG for intraoperative mapping and chronic brain-computer-interface applications. .},
}

@article {pmid42736349,
year = {2026},
author = {Chen, Y and Tang, A and Xu, X and Li, J and Ding, K and Chen, Y and Wang, Y and Hu, S and Lai, J},
title = {Gut single-microbe landscape in patients with major depressive disorder and bipolar disorder.},
journal = {Molecular psychiatry},
volume = {},
number = {},
pages = {},
pmid = {42736349},
issn = {1476-5578},
support = {82471542//National Natural Science Foundation of China (National Science Foundation of China)/ ; 82571735//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
abstract = {Microbial communities in the human gut are highly diverse and complex, and many play critical roles in health and disease. Their functioning depends not only on species composition and diversity but also on intra- and intercellular transcriptional dynamics. Robust technologies capable of capturing single-microbe RNA sequencing information are urgently needed to understand microbial heterogeneity and host interactions. In this exploratory study, we applied droplet-based single-microbe RNA sequencing (smRNA-seq2) to analyze gut microbiomes from five patients with major depressive disorder (MDD), five with bipolar disorder (BD), and five healthy participants (HP), generating a transcriptional atlas of 33,174 single microbial cells. Unsupervised clustering based on RNA expression profiles partitioned these cells into 37 distinct clusters, reflecting both taxonomic diversity and intra-species functional heterogeneity. The most dominant clusters were identified as Fusicatenibacter saccharivorans, Phocaeicola dorei, Enterocloster sp000431375, and Clostridium_Q sp003024715. Compositional and transcriptional differences were observed across diagnostic groups, with clustering patterns appearing to be influenced by disease, gender, and age. Functional heterogeneity was evident in oxidative stress and metabolic genes such as sodB, mdh2, and eno2 in Phocaeicola dorei, while stress-response genes (htpG_1, groL, dnaK, clpB) were upregulated in BD. Focusing on the ko03110 pathway (chaperones and folding catalysts), species-specific patterns emerged: Clostridium_Q_sp003024715 was positively associated with health but decreased in disease status; Enterocloster_sp000431375 and Fusicatenibacter saccharivorans were upregulated in BD; and Phocaeicola dorei was downregulated in MDD. Together, these findings suggest the presence of functional and phenotypic heterogeneity within the gut microbiome in mood disorders and identify exploratory microbial transcriptomic features that may be associated with group-level differences, warranting further validation in larger cohorts.},
}

@article {pmid42736405,
year = {2026},
author = {Qi, Y},
title = {High-performance handwriting brain-computer interfaces.},
journal = {Nature reviews. Neuroscience},
volume = {},
number = {},
pages = {},
pmid = {42736405},
issn = {1471-0048},
}

@article {pmid42736415,
year = {2026},
author = {Brosler, SC and Liu, JR and Silva, AB and Hallinan, IP and Kurtz-Miott, CM and Dunkel Wilker, JFB and Tu-Chan, A and Ganguly, K and Chang, EF},
title = {Simultaneous speech and gesture decoding for multimodal communication in paralysis.},
journal = {Nature neuroscience},
volume = {},
number = {},
pages = {},
pmid = {42736415},
issn = {1546-1726},
support = {JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; JPMJMS2012//MEXT | Japan Science and Technology Agency (JST)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; 5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; },
abstract = {Stroke and neurodegenerative diseases can impair speech and nonverbal gestures, limiting natural communication. Brain-computer interfaces (BCIs) aim to restore these functions by translating neural activity into commands for external devices, although prior work has primarily focused on decoding speech or gestures in isolation. Here we show that neural signals recorded with a single high-density electrocorticography implant can support simultaneous decoding of speech and gestures in people with paralysis. We first show that isolated upper-limb and orofacial movements can be reliably decoded among three participants. Using parallel speech and gesture decoders, we then enabled participants to control a personalized virtual avatar by attempting speech and gestures simultaneously or in isolation. Training models on both isolated and simultaneous data improved performance across behavioral contexts. These findings demonstrate that one cortical implant can support multi-effector control and provide a step toward BCIs that enable more natural communication for people with paralysis.},
}

@article {pmid42737467,
year = {2026},
author = {Shin, H and Kwon, YJ and Hwang, H and Ko, T and Choi, EB and Kim, YT and Han, YM and Kim, JG and Zhou, Q and Yang, S and Yang, S},
title = {Altered Excitation-Inhibition Balance and mGluR1/5-Driven Plasticity in the Motor Cortical Surface in a Rat Model of Parkinson's Disease.},
journal = {International journal of molecular sciences},
volume = {27},
number = {17},
pages = {},
pmid = {42737467},
issn = {1422-0067},
support = {RS-2022-NR069408//National Research Foundation of Korea/ ; },
mesh = {Animals ; *Receptors, Metabotropic Glutamate/metabolism ; *Motor Cortex/metabolism/physiopathology ; Rats ; *Neuronal Plasticity ; *Parkinson Disease/metabolism/physiopathology/etiology ; Disease Models, Animal ; *Receptor, Metabotropic Glutamate 5/metabolism ; Oxidopamine ; Excitatory Postsynaptic Potentials ; Male ; Receptors, AMPA/metabolism ; Rats, Sprague-Dawley ; },
abstract = {Parkinson's disease (PD) is characterized by progressive dopaminergic degeneration and maladaptive motor cortical plasticity. However, the cellular pathways underlying cortical surface activity in the primary motor cortex (M1) remain unclear, despite serving as a potential target for electrotherapy. We investigated the excitatory-inhibitory (E-I) balance and synaptic plasticity of superficial M1 circuits in a unilateral 6-hydroxydopamine (6-OHDA)-induced rat model of PD. Using extracellular local field potential and whole-cell patch recordings from the contralateral and ipsilateral M1 hemispheres of hemi-parkinsonian rats, we observed a significantly elevated field excitatory postsynaptic potential (fEPSP) input-output function but unchanged intrinsic neuronal excitability in the M1 superficial layer. An altered relative contribution between alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)- and N-methyl-D-aspartate receptor (NMDAR)-mediated transmission was reflected by a significantly increased AMPA/NMDA ratio. Markedly reduced inhibitory synaptic tone was also evidenced by the decreased amplitude and frequency of spontaneous inhibitory postsynaptic currents (sIPSCs), supporting an E-I imbalance favoring excitation in PD. Furthermore, group I metabotropic glutamate receptor (mGluR1/5)-dependent long-term depression (LTD) was abolished in the ipsilateral PD hemisphere, whereas NMDAR-dependent LTD remained intact. In summary, dopamine depletion appears to enhance network excitation and disrupt mGluR1/5-mediated control of M1 surface circuitry. Our findings identify altered cortical surface mGluR-dependent plasticity in the hemi-parkinsonian model; however, the relationship between these electrophysiological alterations and individual motor outcomes remains to be determined.},
}

Animals
*Receptors, Metabotropic Glutamate/metabolism
*Motor Cortex/metabolism/physiopathology
Rats
*Neuronal Plasticity
*Parkinson Disease/metabolism/physiopathology/etiology
Disease Models, Animal
*Receptor, Metabotropic Glutamate 5/metabolism
Oxidopamine
Excitatory Postsynaptic Potentials
Male
Receptors, AMPA/metabolism
Rats, Sprague-Dawley

@article {pmid42738542,
year = {2026},
author = {Yang, L and Ma, Y and Li, Z and Li, M},
title = {Dynamic Hippocampal-Striatal Information Flow Accompanies Behavioral Strategy Transitions During Sequential Learning in Pigeons: A Preliminary Study.},
journal = {Animals : an open access journal from MDPI},
volume = {16},
number = {17},
pages = {},
pmid = {42738542},
issn = {2076-2615},
support = {62301496//National Natural Science Foundation of China/ ; },
abstract = {Sequential decision-making requires animals to flexibly balance model-based (MB) and model-free (MF) strategies to adapt to changing environments. The hippocampus (Hp) and striatum (ST) are two important components of the broader neural networks supporting these processes; however, how their dynamic interactions reorganize during learning-dependent strategy transitions remains poorly understood. Here, we trained pigeons on a two-step sequential decision-making task while simultaneously recording local field potentials (LFPs) from the Hp and ST. A dynamic reinforcement learning framework combined with a sliding-window approach was used to characterize temporal changes in behavioral strategies, and phase transfer entropy (PTE) was applied to estimate directed information flow between the Hp and ST across theta, beta, and broad gamma (30-80 Hz) frequency bands. Behavioral modeling revealed a gradual transition from early MB-like, task-structure-sensitive control toward later MF-like value-guided behavior as learning progressed. PTE analysis demonstrated a consistent Hp-to-ST directional bias across all analyzed frequency bands during task acquisition. Notably, gamma-band Hp-to-ST information flow exhibited a consistent decline over training, whereas theta- and beta-band interactions showed less consistent changes across individuals. Additional analyses showed that relative MB model evidence and gamma-band Hp-to-ST information flow covaried across learning, but this association was no longer significant after controlling for learning progression, indicating parallel rather than independently coupled changes. These preliminary findings indicate that hippocampal-striatal communication undergoes frequency-specific reorganization during sequential learning. The reduction in gamma-band Hp-to-ST information flow accompanies, rather than independently predicts, the behavioral strategy transition, suggesting learning-related modulation of interregional coordination as task demands change.},
}

@article {pmid42740021,
year = {2026},
author = {Wu, J and Zhang, X and Zhang, X and Huang, D},
title = {DSGF-Net: A Lightweight Dual-Stream Gated Fusion Network for Cross-Subject fNIRS Motor Task Classification.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740021},
issn = {1424-8220},
mesh = {Humans ; Spectroscopy, Near-Infrared/methods ; Brain-Computer Interfaces ; *Neural Networks, Computer ; Algorithms ; Signal Processing, Computer-Assisted ; },
abstract = {Functional near-infrared spectroscopy (fNIRS) has become an important signal source in motor imagery (MI) brain-computer interface research due to its non-invasive nature and high application flexibility. However, fNIRS signals exhibit significant inter-subject variability, complementary information from oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR), and complex spatiotemporal dynamics, making their efficient and robust classification challenging. To address these issues, this paper proposes a Dual-Stream Gated Fusion Network (DSGF-Net). This model employs a dual-branch architecture to perform complementary feature modeling of fNIRS signals: one branch focuses on extracting multi-scale temporal dynamic features, while the other learns the spatial distribution of hemodynamic features across channels, thereby effectively characterizing the signals from different perspectives. Upon this foundation, a gated fusion mechanism was designed to adaptively adjust the importance of different feature dimensions after the fusion of the two feature streams, thereby enhancing the discriminative power of the fused representation. On two public datasets, MI and UFFT, experimental results based on leave-one-subject-out (LOSO) cross-validation show that the proposed method achieves competitive performance across metrics such as classification accuracy, F1-score, and Kappa coefficient. Furthermore, a comparative analysis of performance under different network component configurations validates the contributions of the dual-branch structure and the gated fusion mechanism to performance improvements. Furthermore, complexity analysis results show that DSGF-Net achieves superior classification performance while maintaining a relatively small parameter size, striking a good balance between performance and computational complexity. DSGF-Net provides an effective, lightweight deep learning framework for offline fNIRS-based motor task classification, with potential applications in cross-subject BCI systems and brain signal decoding.},
}

Humans
Spectroscopy, Near-Infrared/methods
Brain-Computer Interfaces
*Neural Networks, Computer
Algorithms
Signal Processing, Computer-Assisted

@article {pmid42740056,
year = {2026},
author = {Liang, Y and Zhang, L and Jiang, Y and Zhu, J and Zhao, Y and Qin, P and Chen, D and Peng, J and Li, Y and Hu, X},
title = {A Wearable Multimodal Assistive Interface for Virtual Cursor Control in Stroke Survivors with Upper-Limb Impairment.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740056},
issn = {1424-8220},
support = {2022ZD0208900//STI 2030-Major Projects/ ; 2018B030339001//the Key R&D Program of Guangdong Province, China/ ; 202007030007//the Key Realm Research and Development Program of Guangzhou, China/ ; 2024D02J0008//the Guangzhou Talent Plan/ ; 32371098//National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Stroke/physiopathology ; *Wearable Electronic Devices ; *User-Computer Interface ; Female ; Male ; Electroencephalography ; *Upper Extremity/physiopathology ; *Stroke Rehabilitation/methods ; Middle Aged ; Electrooculography ; Adult ; Survivors ; Aged ; },
abstract = {Stroke survivors with upper-limb impairments often have difficulty using conventional computer interfaces, which limits their ability to perform daily computer-related activities independently. This study developed a wearable multimodal assistive interface that enables computer interaction through a virtual cursor. A lightweight headband equipped with electrooculography (EOG), electroencephalography (EEG), and an inertial measurement unit (IMU) was used to acquire multimodal signals for interaction control. EOG signals were processed to detect voluntary blinks to generate clicks, head movements were mapped to cursor movements through IMU-based control, and frontal EEG signals were used to estimate attention as an auxiliary mechanism for command verification. A rapid user-specific calibration procedure was introduced to adapt blink-detection thresholds to individual EOG characteristics without requiring extensive training. Thirty stroke patients with upper-limb impairments participated in experiments involving common computer tasks, including news reading, video playback, and character spelling. The system achieved an average operation accuracy of 87.53 ± 4.92%, an average operation time of 3.49 ± 0.49 s, and an information transfer rate of 62.04 ± 15.93 bits/min in the spelling task. The mean NASA-TLX score was 32.1 ± 5.4, indicating a moderate subjective workload during system use. These results demonstrate the feasibility of the proposed wearable multimodal assistive interface for supporting computer interaction in stroke survivors with upper-limb impairments.},
}

Humans
*Stroke/physiopathology
*Wearable Electronic Devices
*User-Computer Interface
Female
Male
Electroencephalography
*Upper Extremity/physiopathology
*Stroke Rehabilitation/methods
Middle Aged
Electrooculography
Adult
Survivors
Aged

@article {pmid42740064,
year = {2026},
author = {Żyliński, M and Śmigielski, BT and Cybulski, G},
title = {The Deep-Match Framework for Event-Related Potential Detection in EEG.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740064},
issn = {1424-8220},
mesh = {*Electroencephalography/methods ; Humans ; *Evoked Potentials/physiology ; Signal Processing, Computer-Assisted ; Deep Learning ; Algorithms ; Neural Networks, Computer ; Signal-To-Noise Ratio ; },
abstract = {Reliable detection of event-related potentials (ERPs) at the single-trial level remains a challenge due to low signal-to-noise ratio and high variability in electroencephalography (EEG) recordings. This work investigates the use of the Deep-Match framework (Deep-MF) for ERP detection. We examine whether incorporating prior knowledge of an ERP template into deep learning models improves detection performance. As a proof-of-concept study, the framework was evaluated on a single dataset with multi-channel EEG recordings during laser stimulation. The model was trained in two stages. First, an encoder-decoder architecture was trained to reconstruct input EEG signals in order to learn compact signal representations. In the second stage, the decoder was replaced with a detection module and the network was fine-tuned for ERP identification. Two model variants were evaluated: a standard model with randomly initialized filters and a Deep-MF model in which input kernels were initialized using ERP templates. Models performance was assessed on a single-trial ERP detection task during leave-one-out validation, and then compared with matched filter detector. The neural network models outperformed the matched filter detector and proposed that the Deep-MF model slightly outperformed the detector with standard kernel initialization for the majority of held-out subjects. Although both approaches exhibited substantial inter-subject variability, Deep-MF achieved a higher average F1-score (0.37) compared to the standard network (0.34), indicating improved robustness to cross-subject differences. Performance varied considerably across participants. The best performance obtained by Deep-MF reached an F1-score of 0.71, exceeding the maximum score achieved by the standard model (0.59). These results showed that ERP-informed kernel initialization provides improvements in single-trial ERP detection under subject-independent evaluation. These findings demonstrate that integrating domain knowledge with deep learning architectures can improve single-trial ERP detection. The proposed approach provides a step towards practical wearable EEG and passive brain-computer interface applications, as well as towards real-time monitoring of cognitive processes.},
}

*Electroencephalography/methods
Humans
*Evoked Potentials/physiology
Signal Processing, Computer-Assisted
Deep Learning
Algorithms
Neural Networks, Computer
Signal-To-Noise Ratio

@article {pmid42740092,
year = {2026},
author = {Chen, C and Lv, D and Sun, J and Liu, L and Li, S and Pan, M and Tian, C and Li, Z and Wu, F and Zhang, N and Jing, T},
title = {EEG Subject Identification and Open-Set Rejection Across Paradigms.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {17},
pages = {},
pmid = {42740092},
issn = {1424-8220},
support = {2025CXGC010610, 2023CXPT039//Key R&D Program of Shandong Province/ ; 202428048//Jinan Science and Technology Plan "Challenge-Driven" Project/ ; },
mesh = {*Electroencephalography/methods ; Humans ; Machine Learning ; Signal Processing, Computer-Assisted ; Algorithms ; },
abstract = {Objective: To compare electroencephalography (EEG)-based subject-identification and open-set rejection performance across experimental paradigms while examining model robustness and cross-session generalization. Methods: The M3CV database was analyzed across resting state, transient sensory stimulation, steady-state sensory stimulation, P300 Oddball, and motor execution. Closed-set identification was evaluated across feature representations, conventional machine-learning models, and raw-EEG deep-learning baselines. Open-set performance was further assessed using an identity-first leakage-free nested procedure with 60 enrolled identities, 15 development unknown identities, and 20 final-test unknown identities. Results: Under the P4 within-session protocol, transient sensory stimulation achieved the highest Rank-1 accuracy (98.10%). Differential entropy and shrinkage linear discriminant analysis achieved mean Rank-1 accuracies of 98.01% and 98.29%, respectively. Under leakage-free nested open-set evaluation, transient sensory stimulation achieved DIR@FPIR = 5%, DIR@FPIR = 1%, and AU-OSCR values of 91.75%, 77.32%, and 97.36%, respectively. Deep-learning analyses confirmed strong within-session identity discrimination but showed model-dependent open-set paradigm rankings. In contrast, strict cross-session transfer produced marked degradation across all model families, with Rank-1 accuracy falling to approximately 1.9-5.4% and verification AUC to approximately 0.53-0.56; unsupervised target normalization provided little recovery. Conclusions: EEG paradigms exhibited strong but largely session-dependent identity discriminability. Transient sensory stimulation provided the most favorable within-session open-set performance under the primary conventional framework, whereas cross-session variability dominated paradigm-dependent differences under zero-shot transfer.},
}

*Electroencephalography/methods
Humans
Machine Learning
Signal Processing, Computer-Assisted
Algorithms

@article {pmid42729169,
year = {2026},
author = {Ko, KJ and Chung, JH},
title = {Early continence and postoperative urodynamic findings after single-port transvesical robot-assisted radical prostatectomy: a preliminary prospective physiologic case series.},
journal = {Translational andrology and urology},
volume = {15},
number = {8},
pages = {279},
pmid = {42729169},
issn = {2223-4691},
abstract = {BACKGROUND: Single-port transvesical robot-assisted radical prostatectomy (SP-TVRP), which enables early continence outcomes, has recently emerged. This study aimed to describe objective postoperative urodynamic findings at 3 months after SP-TVRP and to determine whether these findings are compatible with early continence recovery in a preliminary prospective physiologic case series.

METHODS: This prospective single-center, single-surgeon case series enrolled 11 patients who underwent SP-TVRP for prostate cancer without radiologic nodal or distant metastasis. All patients completed validated functional questionnaires and underwent comprehensive urodynamic study (UDS) at 3 months postoperatively.

RESULTS: Postoperative UDS showed a favorable storage profile, with a median maximum cystometric capacity (MCC) of 450 mL and median bladder compliance of 64 mL/cmH2O. Median bladder outlet obstruction index (BOOI) and bladder contractility index (BCI) values were 16 and 93, respectively. After correction for intravesical-pressure drift during urethral pressure (Pura) profilometry, functional urethral length (FUL) estimates ranged from ≤1 cm to approximately 2.4 cm. Abdominal leak point pressure (ALPP) testing showed no provoked leakage in 72.7% of patients. Zero-pad continence rates were 36.4%, 54.5%, and 90.9% immediately after catheter removal, at 1 month, and at 3 months, respectively, and the 3-month 0-1 safety-pad rate was 100%. The positive surgical margin rate was 45.5%, and prostate-specific antigen (PSA) persistence occurred in 18.2% of patients, emphasizing important oncologic limitations in this initial experience.

CONCLUSIONS: In this preliminary physiologic case series, 3-month postoperative UDS findings were compatible with favorable early continence recovery after SP-TVRP. However, because preoperative UDS and a control group were not available, these data cannot establish true preservation, improvement, or superiority of continence mechanisms. The high positive surgical margin rate and PSA persistence require cautious interpretation, careful patient selection, and longer oncologic follow-up before SP-TVRP can be considered broadly applicable.},
}

@article {pmid42728336,
year = {2026},
author = {Abdelmagid, M and Yusuf, M and ElHalawany, BM and Fares, A},
title = {NeuroStream: spectral-spatio-temporal deep learning for visual stimulus classification from EEG.},
journal = {Scientific reports},
volume = {16},
number = {1},
pages = {},
pmid = {42728336},
issn = {2045-2322},
mesh = {Humans ; *Deep Learning ; *Electroencephalography/methods ; *Photic Stimulation/methods ; Signal Processing, Computer-Assisted ; Wavelet Analysis ; Algorithms ; },
abstract = {Electroencephalography (EEG)-based visual classification is a challenging task due to low spatial resolution, complex temporal dynamics, and potential experimental confounds, yet with the recent advances in EEG classification, it offers a cost-effective, portable alternative with millisecond-level temporal resolution to Functional Magnetic Resonance Imaging (fMRI) for large scale studies and real-time applications. We propose a novel Spectral-Spatio-Temporal (SST) representation that transforms raw EEG signals into a structured, video-like format. Specifically, we compute wavelet transforms for all channels, aggregate log power into frequency bands, and map these features to electrode positions over time, thereby synthesizing the signal's multi-dimensional dynamics into a unified, high-fidelity sequence. Building on this representation, we introduce the NeuroStream-SST framework, featuring a lightweight deep learning architecture optimized for spatiotemporal feature extraction. Experiments on the EEGCVPR40 dataset show that our approach reaches [Formula: see text] accuracy in the high-gamma band using standard dataset splits, outperforming existing methods evaluated under an identical protocol and demonstrating its ability to capture complex neural characteristics effectively. Furthermore, we implement a set of evaluation protocols designed to expose and quantify the contribution of temporal correlations to reported accuracy. decoding performance declines steadily as the association between class labels and recording sessions is weakened, and falls to the majority-class baseline once the sessions of the evaluated classes are withheld entirely. These findings highlight our framework as a promising direction for EEG-based visual decoding, with implications for brain-computer interfaces and cognitive neuroscience.},
}

Humans
*Deep Learning
*Electroencephalography/methods
*Photic Stimulation/methods
Signal Processing, Computer-Assisted
Wavelet Analysis
Algorithms