@article {pmid40242802,
year = {2025},
author = {Iosif, R and Skrbinšek, T and Erős, N and Konec, M and Boljte, B and Jan, M and Promberger-Fürpass, B},
title = {Wolf Population Size and Composition in One of Europe's Strongholds, the Romanian Carpathians.},
journal = {Ecology and evolution},
volume = {15},
number = {4},
pages = {e71200},
pmid = {40242802},
issn = {2045-7758},
abstract = {Strategies of coexistence with large carnivores should integrate scientific evidence, population monitoring providing an opportunity for advancing outdated management paradigms. We estimated wolf population density and social dynamics across a 1400 km[2] area in a data-poor region of the Romanian Carpathians. Across three consecutive years (2017-2018 until 2019-2020), we collected and genotyped 505 noninvasive DNA wolf samples (scat, hair and urine) to identify individuals, reconstruct pedigrees, and check for the presence of hybridization with domestic dogs. We identified 27 males, 20 females, and one F1 wolf-dog hybrid male. We delineated six wolf packs, with pack size varying between two and seven individuals, and documented yearly changes in pack composition. Using a spatial capture-recapture approach, we estimated population density at 2.35 wolves/100 km[2] (95% BCI = 1.68-3.03) and population abundance at 70 individuals (95% BCI = 49-89). Noninvasive DNA data collection coupled with spatial capture-recapture has the potential to inform on wolf population size and dynamics at broader spatial scales, across different sampling areas representative of the diverse Carpathian landscapes, and across different levels of human impact, supporting wildlife decision making in one of Europe's main strongholds for large carnivores.},
}

@article {pmid40242584,
year = {2025},
author = {Hu, S and Lin, C and Wang, H and Wang, X},
title = {Psychedelics and Eating Disorders: Exploring the Therapeutic Potential for Anorexia Nervosa and Beyond.},
journal = {ACS pharmacology & translational science},
volume = {8},
number = {4},
pages = {910-916},
pmid = {40242584},
issn = {2575-9108},
abstract = {Anorexia nervosa (AN) is a severe psychiatric disorder characterized by extreme food restriction, an intense fear of weight gain, and a distorted body image, leading to significant morbidity and mortality. Conventional treatments such as cognitive-behavioral therapy (CBT) and pharmacotherapy often prove inadequate, especially in severe cases, highlighting the need for novel therapeutic approaches. Recent research into psychedelics, such as psilocybin and 3,4-methylenedioxymethamphetamine (MDMA), offers promising avenues for treating anorexia nervosa by targeting its neurobiological and psychological underpinnings. These psychedelics disrupt maladaptive neural circuits, enhance cognitive flexibility, and facilitate emotional processing, offering potential relief for patients unresponsive to traditional therapies. Early studies have shown positive outcomes with psychedelics, including reductions in anorexia nervosa symptoms and improvements in psychological well-being. However, further research is needed to establish their long-term safety, efficacy, and integration into clinical practice. Addressing the legal, ethical, and safety challenges will be crucial in determining whether psychedelics can transform the treatment landscape for anorexia nervosa and other eating disorders.},
}

@article {pmid40242456,
year = {2025},
author = {Yan, W and Luo, Q and Du, C},
title = {Channel component correlation analysis for multi-channel EEG feature component extraction.},
journal = {Frontiers in neuroscience},
volume = {19},
number = {},
pages = {1522964},
pmid = {40242456},
issn = {1662-4548},
abstract = {INTRODUCTION: Electroencephalogram (EEG) analysis has shown significant research value for brain disease diagnosis, neuromodulation and brain-computer interface (BCI) application. The analysis and processing of EEG signals is complex since EEG are nonstationary, nonlinear, and often contaminated by intense background noise. Principal component analysis (PCA) and independent component analysis (ICA), as the commonly used methods for multi-dimensional signal feature component extraction, still have some limitations in terms of performance and calculation.

METHODS: In this study, channel component correlation analysis (CCCA) method was proposed to extract feature components of multi-channel EEG. Firstly, empirical wavelet transform (EWT) decomposed each channel signal into different frequency bands, and reconstructed them into a multi-dimensional signal. Then the objective optimization function was constructed by maximizing the covariance between multi-dimensional signals. Finally the feature components of multi-channel EEG were extracted using the calculated weight coefficient.

RESULTS: The results showed that the CCCA method could find the most relevant frequency band between multi-channel EEG. Compared with PCA and ICA methods, CCCA could extract the common components of multi-channel EEG more effectively, which is of great significance for the accurate analysis of EEG.

DISCUSSION: The CCCA method proposed in this study has shown excellent performance in the feature component extraction of multi-channel EEG and could be considered for practical engineering applications.},
}

@article {pmid40241786,
year = {2025},
author = {Hernández-Gloria, JJ and Jaramillo-Gonzalez, A and Savić, AM and Mrachacz-Kersting, N},
title = {Toward brain-computer interface speller with movement-related cortical potentials as control signals.},
journal = {Frontiers in human neuroscience},
volume = {19},
number = {},
pages = {1539081},
pmid = {40241786},
issn = {1662-5161},
abstract = {Brain Computer Interface spellers offer a promising alternative for individuals with Amyotrophic Lateral Sclerosis (ALS) by facilitating communication without relying on muscle activity. This study assessed the feasibility of using movement related cortical potentials (MRCPs) as a control signal for a Brain-Computer Interface speller in an offline setting. Unlike motor imagery-based BCIs, this study focused on executed movements. Fifteen healthy subjects performed three spelling tasks that involved choosing specific letters displayed on a computer screen by performing a ballistic dorsiflexion of the dominant foot. Electroencephalographic signals were recorded from 10 sites centered around Cz. Three conditions were tested to evaluate MRCP performance under varying task demands: a control condition using repeated selections of the letter "O" to isolate movement-related brain activity; a phrase spelling condition with structured text ("HELLO IM FINE") to simulate a meaningful spelling task with moderate cognitive load; and a random condition using a randomized sequence of letters to introduce higher task complexity by removing linguistic or semantic context. The success rate, defined as the presence of an MRCP, was manually determined. It was approximately 69% for both the control and phrase conditions, with a slight decrease in the random condition, likely due to increased task complexity. Significant differences in MRCP features were observed between conditions with Laplacian filtering, whereas no significant differences were found in single-site Cz recordings. These results contribute to the development of MRCP-based BCI spellers by demonstrating their feasibility in a spelling task. However, further research is required to implement and validate real-time applications.},
}

@article {pmid40241515,
year = {2025},
author = {Jin, F and Li, M and Yang, L and Yang, L and Shang, Z},
title = {Exploring the value learning in pigeons: The role of dual pathways in the basal ganglia and synaptic plasticity.},
journal = {The Journal of experimental biology},
volume = {},
number = {},
pages = {},
doi = {10.1242/jeb.249507},
pmid = {40241515},
issn = {1477-9145},
support = {62301496//National Natural Science Foundation of China/ ; GZC20232447//National Postdoctoral Researcher Program/ ; 252102210008//Key Scientific and Technological Projects of Henan Province/ ; },
abstract = {Understanding value learning in animals is a key focus in cognitive neuroscience. Current models used in research are often simple, and while more complex models have been proposed, it remains unclear which assumptions align with actual value learning strategies of animals. This study investigated the computational mechanisms behind value learning in pigeons using a free-choice task. Three models were constructed based on different assumptions about the role of the basal ganglia's dual pathways and synaptic plasticity in value computation, followed by model comparison and neural correlation analysis. Among the three models tested, the dual-pathway reinforcement learning model with Hebbian rules most closely matched the pigeons' behavior. Furthermore, the striatal gamma band connectivity showed the highest correlation with the values estimated by this model. Additionally, enhanced beta band connectivity in the nidopallium caudolaterale supported value learning. This study provides valuable insights into reinforcement learning mechanisms in non-human animals.},
}

@article {pmid40240152,
year = {2025},
author = {Ma, YN and Karako, K and Song, P and Hu, X and Xia, Y},
title = {Integrative neurorehabilitation using brain-computer interface: From motor function to mental health after stroke.},
journal = {Bioscience trends},
volume = {},
number = {},
pages = {},
doi = {10.5582/bst.2025.01109},
pmid = {40240152},
issn = {1881-7823},
abstract = {Stroke remains a leading cause of mortality and long-term disability worldwide, frequently resulting in impairments in motor control, cognition, and emotional regulation. Conventional rehabilitation approaches, while partially effective, often lack individualization and yield suboptimal outcomes. In recent years, brain-computer interface (BCI) technology has emerged as a promising neurorehabilitation tool by decoding neural signals and providing real-time feedback to enhance neuroplasticity. This review systematically explores the use of BCI systems in post-stroke rehabilitation, focusing on three core domains: motor function, cognitive capacity, and emotional regulation. This review outlines the neurophysiological principles underpinning BCI-based motor rehabilitation, including neurofeedback training, Hebbian plasticity, and multimodal feedback strategies. It then examines recent advances in upper limb and gait recovery using BCI integrated with functional electrical stimulation (FES), robotics, and virtual reality (VR). Moreover, it highlights BCI's potential in cognitive and language rehabilitation through EEG-based neurofeedback and the integration of artificial intelligence (AI) and immersive VR environments. In addition, it discusses the role of BCI in monitoring and regulating post-stroke emotional disorders via closed-loop systems. While promising, BCI technologies face challenges related to signal accuracy, device portability, and clinical validation. Future research should prioritize multimodal integration, AI-driven personalization, and large-scale randomized trials to establish long-term efficacy. This review underscores BCI's transformative potential in delivering intelligent, personalized, and cross-domain rehabilitation solutions for stroke survivors.},
}

@article {pmid40238867,
year = {2025},
author = {Li, X and Deng, Z and Zhang, W and Zhou, W and Liu, X and Quan, H and Li, J and Li, P and Li, Y and Hu, C and Li, F and Niu, L and Tian, Z and Meng, L and Zheng, H},
title = {Oscillating microbubble array-based metamaterials (OMAMs) for rapid isolation of high-purity exosomes.},
journal = {Science advances},
volume = {11},
number = {16},
pages = {eadu8915},
doi = {10.1126/sciadv.adu8915},
pmid = {40238867},
issn = {2375-2548},
mesh = {*Microbubbles ; *Exosomes/metabolism/chemistry ; Humans ; Acoustics ; },
abstract = {Exosomes secreted by cells hold substantial potential for disease diagnosis and treatment. However, the rapid isolation of high-purity exosomes and their subpopulations from biofluids (e.g., undiluted whole blood) remains challenging. This study presents oscillating microbubble array-based metamaterials (OMAMs) for enabling the rapid isolation of high-purity exosomes and their subpopulations from biofluids without labeling or preprocessing. Particularly, leveraging acoustically excited microbubble oscillation, OMAMs can generate numerous acoustofluidic traps for filtering in-fluid micro/nanoparticles, thus allowing for removing bioparticles larger than exosomes to obtain high-purity (93%) exosomes from undiluted whole blood in ~3 minutes. Moreover, exosome subpopulations in different size ranges can be isolated by tuning the microbubble oscillation amplitude. Additionally, as each oscillating microbubble functions as an ultradeep subwavelength (~λ/186) acoustic amplifier and a nonlinear source, OMAMs can generate high-resolution complex acoustic energy patterns and tune the patterns by activating different-sized microbubbles at their distinct resonance frequencies.},
}

*Microbubbles
*Exosomes/metabolism/chemistry
Humans
Acoustics

@article {pmid40236895,
year = {2025},
author = {Wen, D and Xing, Y and Yao, Y and Liang, G and Xing, Y and Jung, TP and Yu, H and Xie, X and Wan, X and Liu, T and Duan, D and Li, D and Zhou, Y},
title = {Transforming long-term adjunctive therapy for cognitive impairment: the role of multimodal self-adaptive digital medicine.},
journal = {Frontiers in neurology},
volume = {16},
number = {},
pages = {1571817},
pmid = {40236895},
issn = {1664-2295},
}

@article {pmid40236742,
year = {2025},
author = {Wei, B and Cheng, S and Feng, Y},
title = {Neural personal information and its legal protection: evidence from China.},
journal = {Journal of law and the biosciences},
volume = {12},
number = {1},
pages = {lsaf006},
doi = {10.1093/jlb/lsaf006},
pmid = {40236742},
issn = {2053-9711},
abstract = {The rapid advancements in neuroscience highlight the pressing need to safeguard neural personal information (NPI). China has achieved significant progress in brain-computer interface technology and its clinical applications. Considering the intrinsic vulnerability of NPI and the paucity of legal scrutiny concerning NPI breaches, a thorough assessment of the adequacy of China's personal information protection legislation is essential. This analysis contends that NPI should be classified as sensitive personal information. The absence of bespoke provisions for NPI in current legislation underscores persistent challenges in its protection. To address these gaps, this work proposes the establishment of a concentric-circle hard-soft law continuum to support a hybrid governance model for NPI, rooted in fundamental human rights principles.},
}

@article {pmid40236412,
year = {2025},
author = {Jude, JJ and Levi-Aharoni, H and Acosta, AJ and Allcroft, SB and Nicolas, C and Lacayo, BE and Card, NS and Wairagkar, M and Brandman, DM and Stavisky, SD and Willett, FR and Williams, ZM and Simeral, JD and Hochberg, LR and Rubin, DB},
title = {An intuitive, bimanual, high-throughput QWERTY touch typing neuroprosthesis for people with tetraplegia.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
doi = {10.1101/2025.04.01.25324990},
pmid = {40236412},
abstract = {Recognizing keyboard typing as a familiar, high information rate communication paradigm, we developed an intracortical brain computer interface (iBCI) typing neuroprosthesis providing bimanual QWERTY keyboard functionality for people with paralysis. Typing with this iBCI involves only attempted finger movements, which are decoded accurately with as few as 30 calibration sentences. Sentence decoding is improved using a 5-gram language model. This typing neuroprosthesis performed well for two iBCI clinical trial participants with tetraplegia - one with ALS and one with spinal cord injury. Typing speed is user-regulated, reaching 110 characters per minute, resulting in 22 words per minute with a word error rate of 1.6%. This resembles able-bodied typing accuracy and provides higher throughput than current state-of-the-art hand motor iBCI decoding. In summary, a typing neuroprosthesis decoding finger movements, provides an intuitive, familiar, and easy-to-learn paradigm for individuals with impaired communication due to paralysis.},
}

@article {pmid40236074,
year = {2025},
author = {Busch, EL and Fincke, EC and Lajoie, G and Krishnaswamy, S and Turk-Browne, NB},
title = {Accelerated learning of a noninvasive human brain-computer interface via manifold geometry.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
doi = {10.1101/2025.03.29.646109},
pmid = {40236074},
issn = {2692-8205},
abstract = {Brain-computer interfaces (BCIs) promise to restore and enhance a wide range of human capabilities. However, a barrier to the adoption of BCIs is how long it can take users to learn to control them. We hypothesized that human BCI learning could be accelerated by leveraging the naturally occurring geometric structure of brain activity, or its intrinsic manifold, extracted using a data-diffusion process. We trained participants on a noninvasive BCI that allowed them to gain real-time control of an avatar in a virtual reality game by modulating functional magnetic resonance imaging (fMRI) activity in brain regions that support spatial navigation. We then perturbed the mapping between fMRI activity patterns and the movement of the avatar to test our manifold hypothesis. When the new mapping respected the intrinsic manifold, participants succeeded in regaining control of the BCI by aligning their brain activity within the manifold. When the new mapping did not respect the intrinsic manifold, participants could not learn to control the avatar again. These findings show that the manifold geometry of brain activity constrains human learning of a complex cognitive task in higher-order brain regions. Manifold geometry may be a critical ingredient for unlocking the potential of future human neurotechnologies.},
}

@article {pmid40235786,
year = {2025},
author = {Wang, LP and Yang, C and Fu, JY and Zhang, XY and Shen, XM and Shi, NL and Wu, HL and Gao, XR},
title = {A preliminary study of steady-state visually-evoked potential-based non-invasive brain-computer interface technology as a communication aid for patients with amyotrophic lateral sclerosis.},
journal = {Quantitative imaging in medicine and surgery},
volume = {15},
number = {4},
pages = {3469-3479},
pmid = {40235786},
issn = {2223-4292},
abstract = {BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that affects motor neurons, leading to severe disability and ultimately death. Communication difficulties are common in ALS patients as the disease progresses; thus, alternative communication aids need to be explored. This study sought to examine the use and effect of steady-state visually-evoked potential (SSVEP)-based non-invasive brain-computer interface (BCI) technology as a communication aid for patients with ALS and to examine possible influencing factors.

METHODS: In total, 12 patients with ALS were selected, and a 40-character target selection was performed using SSVEP-based non-invasive BCI technology. The patients were presented with specific visual stimuli, and nine-lead electroencephalogram (EEG) signals in the occipital region were acquired when the patients were looking at the target. Using the feature recognition analysis method, the final output was the characters recognized by the patients. The basic clinical data of the patients (e.g., age, gender, course of disease, affected area, and ALS functional scale score) were collected, and the BCI accuracy rate, information transmission rate, and average SSVEP recognition time were calculated.

RESULTS: The results revealed that the recognition efficiency of the ALS patients varied. The accuracy potential increased as the stimulus duration extended, highlighting the possibility for improvement via further optimization. The results also showed that the experimental design schedules typically used for healthy individuals may not be entirely suitable for ALS patients, which presents an exciting opportunity to tailor future studies to better meet the unique needs of ASL patients. Further, the results revealed the necessity of using customized experimental schedules in future studies, which could lead to more relevant and effective data collection for ALS patients.

CONCLUSIONS: The study found that SSVEP-based non-invasive BCI technology has promising potential as a communication aid for ALS patients. While further algorithm optimization and comprehensive studies with larger sample sizes are necessary, the initial findings are encouraging, and could lead to the development of more effective communication solutions that are specifically tailored to address the challenges faced by ALS patients.},
}

@article {pmid40234729,
year = {2025},
author = {Webster, P},
title = {Can AI-powered brain-computer interfaces boost human intelligence?.},
journal = {Nature medicine},
volume = {31},
number = {4},
pages = {1045-1047},
doi = {10.1038/s41591-025-03641-7},
pmid = {40234729},
issn = {1546-170X},
}

@article {pmid40234486,
year = {2025},
author = {Zhao, W and Zhang, B and Zhou, H and Wei, D and Huang, C and Lan, Q},
title = {Multi-scale convolutional transformer network for motor imagery brain-computer interface.},
journal = {Scientific reports},
volume = {15},
number = {1},
pages = {12935},
pmid = {40234486},
issn = {2045-2322},
support = {3502Z202374054//Natural Science Foundation of Xiamen, China/ ; 2023J01785//Natural Science Foundation of Fujian Province of China/ ; JAT191153 and JAT201045//Education and Scientific Research Project for Young and Middle-aged Teachers of Fujian Province of China/ ; CKZ24016//Jimei University Chengyi College Provincial and Ministerial-Level Scientific Research Cultivation Project/ ; CKZ24016//Jimei University Chengyi College Provincial and Ministerial-Level Scientific Research Cultivation Project/ ; },
mesh = {*Brain-Computer Interfaces ; Humans ; Electroencephalography/methods ; *Neural Networks, Computer ; *Imagination/physiology ; *Brain/physiology ; Signal Processing, Computer-Assisted ; },
abstract = {Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencephalography (MI-EEG) signals in BCIs. However, traditional CNN-based methods face challenges such as individual variability in EEG signals and the limited receptive fields of CNNs. This study presents the Multi-Scale Convolutional Transformer (MSCFormer) model that integrates multiple CNN branches for multi-scale feature extraction and a Transformer module to capture global dependencies, followed by a fully connected layer for classification. The multi-branch multi-scale CNN structure effectively addresses individual variability in EEG signals, enhancing the model's generalization capabilities, while the Transformer encoder strengthens global feature integration and improves decoding performance. Extensive experiments on the BCI IV-2a and IV-2b datasets show that MSCFormer achieves average accuracies of 82.95% (BCI IV-2a) and 88.00% (BCI IV-2b), with kappa values of 0.7726 and 0.7599 in five-fold cross-validation, surpassing several state-of-the-art methods. These results highlight MSCFormer's robustness and accuracy, underscoring its potential in EEG-based BCI applications. The code has been released in https://github.com/snailpt/MSCFormer .},
}

*Brain-Computer Interfaces
Humans
Electroencephalography/methods
*Neural Networks, Computer
*Imagination/physiology
*Brain/physiology
Signal Processing, Computer-Assisted

@article {pmid40234393,
year = {2025},
author = {Bertoni, T and Noel, JP and Bockbrader, M and Foglia, C and Colachis, S and Orset, B and Evans, N and Herbelin, B and Rezai, A and Panzeri, S and Becchio, C and Blanke, O and Serino, A},
title = {Pre-movement sensorimotor oscillations shape the sense of agency by gating cortical connectivity.},
journal = {Nature communications},
volume = {16},
number = {1},
pages = {3594},
pmid = {40234393},
issn = {2041-1723},
support = {163951//Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)/ ; },
mesh = {Humans ; *Motor Cortex/physiology ; Male ; Adult ; Female ; Electroencephalography ; Young Adult ; Movement/physiology ; Brain-Computer Interfaces ; Alpha Rhythm/physiology ; Hand/physiology ; Sense of Agency ; },
abstract = {Our sense of agency, the subjective experience of controlling our actions, is a crucial component of self-awareness and motor control. It is thought to originate from the comparison between intentions and actions across broad cortical networks. However, the underlying neural mechanisms are still not fully understood. We hypothesized that oscillations in the theta-alpha range, thought to orchestrate long-range neural connectivity, may mediate sensorimotor comparisons. To test this, we manipulated the relation between intentions and actions in a tetraplegic user of a brain machine interface (BMI), decoding primary motor cortex (M1) activity to restore hand functionality. We found that the pre-movement phase of low-alpha oscillations in M1 predicted the participant's agency judgements. Further, using EEG-BMI in healthy participants, we found that pre-movement alpha oscillations in M1 and supplementary motor area (SMA) correlated with agency ratings, and with changes in their functional connectivity with parietal, temporal and prefrontal areas. These findings argue for phase-driven gating as a key mechanism for sensorimotor integration and sense of agency.},
}

Humans
*Motor Cortex/physiology
Male
Adult
Female
Electroencephalography
Young Adult
Movement/physiology
Brain-Computer Interfaces
Alpha Rhythm/physiology
Hand/physiology
Sense of Agency

@article {pmid40232894,
year = {2025},
author = {Wang, D and Wei, Q},
title = {SMANet: A Model Combining SincNet, Multi-branch Spatial-Temporal CNN and Attention Mechanism for Motor Imagery BCI.},
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.2025.3560993},
pmid = {40232894},
issn = {1558-0210},
abstract = {Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an end-to-end deep learning model, Sinc-multibranch-attention network (SMANet), which combines a SincNet, a multibranch spatial-temporal convolutional neural network (MBSTCNN), and an attention mechanism for MI-BCI classification. Firstly, Sinc convolution is utilized as a band-pass filter bank for data filtering; Second, pointwise convolution facilitates the effective integration of feature information across different frequency ranges, thereby enhancing the overall feature expression capability; Next, the resulting data are fed into the MBSTCNN to learn a deep feature representation. Thereafter, the outputs of the MBSTCNN are concatenated and then passed through an efficient channel attention (ECA) module to enhance local channel feature extraction and calibrate feature mapping. Ultimately, the feature maps yielded by ECA are classified using a fully connected layer. This model SMANet enhances discriminative features through a multi-objective optimization scheme that integrates cross-entropy loss and central loss. The experimental outcomes reveal that our model attains an average accuracy of 80.21% on the four-class MI dataset (BCI Competition IV 2a), 84.02% on the two-class MI dataset (BCI Competition IV 2b), and 72.70% on the two-class MI dataset (OpenBMI). These results are superior to those of the current state-of-the-art methods. The SMANet is capable to effectively decoding the spatial-spectral-temporal information of EEG signals, thereby enhancing the performance of MI-BCIs.},
}

@article {pmid40231563,
year = {2025},
author = {Park, K and Hong, J and Shin, H and Choi, J and Xu, D and Lee, J and Ryu, J and Kim, S and Jeong, H and Choe, J and Yang, S and Yang, S and Ahn, JH},
title = {2D Material-Based Injectable Sensor for Minimally-Invasive Cerebral Blood Flow Monitoring.},
journal = {Small (Weinheim an der Bergstrasse, Germany)},
volume = {},
number = {},
pages = {e2501744},
doi = {10.1002/smll.202501744},
pmid = {40231563},
issn = {1613-6829},
support = {20012355//Ministry of Trade, Industry and Energy/ ; },
abstract = {Monitoring cerebral blood flow is an important method for diagnosing and treating brain diseases. Thermal transport caused by blood flow provides valuable information for detecting abnormalities in blood flow. Here, a minimally invasive, injectable blood flow sensor is reported, consisting of a flexible, graphene-based thin film heater and MoS2-based temperature sensor array integrated on a mesh-structured polymer substrate. Upon injection through a small skull hole in the skull, the device unfolds and achieves conformal contact on the cortical surface, aligning with the target vessel. By measuring temperature variations in response to the heater activation, the injectable sensor continuously monitors blood flow changes in the underlying vessel. This approach offers a new potential for cerebral blood flow sensing via minimally invasive implantation.},
}

@article {pmid40230710,
year = {2025},
author = {Finney, JN and Levy, IR and Chandrasekaran, S and Collinger, JL and Boninger, ML and Gaunt, RA and Helm, ER and Fisher, LE},
title = {Techniques to mitigate lead migration for percutaneous trials of cervical spinal cord stimulation.},
journal = {Frontiers in surgery},
volume = {12},
number = {},
pages = {1458572},
pmid = {40230710},
issn = {2296-875X},
abstract = {INTRODUCTION: Epidural spinal cord stimulation (SCS) is a clinical neuromodulation technique that is commonly used to treat neuropathic pain, with patients typically undergoing a one-week percutaneous trial phase before permanent implantation. Traditional SCS involves stimulation of the thoracic spinal cord, but there has been substantial recent interest in cervical SCS to treat upper extremity pain, restore sensation from the missing hand after amputation, or restore motor function to paretic limbs in people with stroke and spinal cord injury. Because of the additional mobility of the neck, as compared to the trunk, lead migration can be a major challenge for cervical SCS, especially during the percutaneous trial phase. The objective of this study was to optimize the implantation procedure of cervical SCS leads to minimize lead migration and increase lead stability during SCS trials.

METHODS: In this study, four subjects underwent percutaneous placement of three SCS leads targeting the cervical spinal segments as part of a clinical trial aiming to restore sensation for people with upper-limb amputation. The leads were maintained for up to 29 days and weekly x-ray imaging was used to measure rostrocaudal and mediolateral lead migration based on bony landmarks.

RESULTS AND DISCUSSION: Lead migration was primarily confined to the rostrocaudal axis with the most migration occurring during the first week. Iterative improvements to the implantation procedure were implemented to increase lead stability across subjects. There was a decrease in lead migration for patients who had more rostral placement of the SCS leads. The average migration from the day of lead implant to lead removal was 29.7 mm for Subject 1 (lead placement ranging from T3-T4 to T1-T2), 41.9 mm for Subject 2 (T2-T3 to C7-T1), 1.9 mm for Subject 3 (T1-T2 to C7-T1), and 16.6 mm for Subject 4 (T1-T2 to C7-T1). We found that initial placement of spinal cord stimulator leads in the cervical epidural space as rostral as possible was critical to minimizing subsequent rostrocaudal lead migration.},
}

@article {pmid40228689,
year = {2025},
author = {Hesam-Shariati, N and Alexander, L and Stapleton, F and Newton-John, T and Lin, CT and Zahara, P and Chen, K and Restrepo, S and Skinner, IW and McAuley, JH and Moseley, GL and Jensen, MP and Gustin, SM},
title = {The Effect of an EEG Neurofeedback Intervention for Corneal Neuropathic Pain: A Single-Case Experimental Design with Multiple Baselines.},
journal = {The journal of pain},
volume = {},
number = {},
pages = {105394},
doi = {10.1016/j.jpain.2025.105394},
pmid = {40228689},
issn = {1528-8447},
abstract = {Corneal neuropathic pain is a complex condition, rarely responsive to current treatments. This trial investigated the potential effect of a novel home-based self-directed EEG neurofeedback intervention on corneal neuropathic pain using a multiple-baseline single-case experimental design. Four Participants completed a predetermined baseline of 7, 10, 14, and 17 days, randomly assigned to each participant, followed by 20 intervention sessions over four weeks. Two one-week follow-ups occurred immediately and five weeks post-intervention during which participants were encouraged to practice mental strategies. Daily pain severity and pain interference observations were the outcome measures, while anxiety, depression, or sleep problems were the generalisation measures. The results showed a medium effect on pain severity and interference across participants when comparing baseline to five-week post-intervention according to Tau-U effect sizes. At the individual level, both Tau-U and NAP effect sizes indicated significant reductions in pain severity and interference for three participants when comparing baseline to five-week post-intervention. However, the reductions indicated by the visual inspection were not considered clinically meaningful. This single-case experimental design study raises the possibility that the intervention may improve pain severity and interference for some individuals, variability in outcomes highlights the need for future research to better understand individual responses and optimize the intervention effect. REGISTRATION: Australian New Zealand Clinical Trial Registry ACTRN12623000173695 PERSPECTIVE: This trial demonstrates the potential of EEG neurofeedback to reduce pain severity and interference in individuals with corneal neuropathic pain. It also highlights user preferences for technology-based interventions, emphasizing ease of use, accessibility, and self-administration to enhance adherence, especially for individuals with limited mobility or restricted healthcare access.},
}

@article {pmid40228398,
year = {2025},
author = {Grigoryan, KA and Mueller, K and Wagner, M and Masri, D and Pine, KJ and Villringer, A and Sehm, B},
title = {Short-term BCI intervention enhances functional brain connectivity associated with motor performance in chronic stroke.},
journal = {NeuroImage. Clinical},
volume = {46},
number = {},
pages = {103772},
doi = {10.1016/j.nicl.2025.103772},
pmid = {40228398},
issn = {2213-1582},
abstract = {BACKGROUND: Evidence suggests that brain-computer interface (BCI)-based rehabilitation strategies show promise in overcoming the limited recovery potential in the chronic phase of stroke. However, the specific mechanisms driving motor function improvements are not fully understood.

OBJECTIVE: We aimed at elucidating the potential functional brain connectivity changes induced by BCI training in participants with chronic stroke.

METHODS: A longitudinal crossover design was employed with two groups of participants over the span of 4 weeks to allow for within-subject (n = 21) and cross-group comparisons. Group 1 (n = 11) underwent a 6-day motor imagery-based BCI training during the second week, whereas Group 2 (n = 10) received the same training during the third week. Before and after each week, both groups underwent resting state functional MRI scans (4 for Group 1 and 5 for Group 2) to establish a baseline and monitor the effects of BCI training.

RESULTS: Following BCI training, an increased functional connectivity was observed between the medial prefrontal cortex of the default mode network (DMN) and motor-related areas, including the premotor cortex, superior parietal cortex, SMA, and precuneus. Moreover, these changes were correlated with the increased motor function as confirmed with upper-extremity Fugl-Meyer assessment scores, measured before and after the training.

CONCLUSIONS: Our findings suggest that BCI training can enhance brain connectivity, underlying the observed improvements in motor function. They provide a basis for developing novel rehabilitation approaches using non-invasive brain stimulation for targeting functionally relevant brain regions, thereby augmenting BCI-induced neuroplasticity and enhancing motor recovery.},
}

@article {pmid40227907,
year = {2025},
author = {Zhong, Y and Wang, Y and Farina, D and Yao, L},
title = {A Closed-Loop Tactile Stimulation Training Protocol for Motor Imagery-Based BCI: Boosting BCI Performance for BCI-Deficiency Users.},
journal = {IEEE transactions on bio-medical engineering},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TBME.2025.3560713},
pmid = {40227907},
issn = {1558-2531},
abstract = {BACKGROUND: Brain-computer interfaces (BCIs) enable users to control and communicate with the external environment. However, a significant challenge in BCI research is the occurrence of "BCI-illiteracy" or "BCI-deficiency", where a notable percentage of users (estimated at 15 to 30%) are unable to achieve successful BCI control. For those users, they are struggling to generate stable and distinguishable brain activity patterns, which are essential for BCI control. Existing neurofeedback training protocols, often rely on the trial-and-error process, which is time-consuming and inefficient, particularly for these low-performing users.

METHODS: To address this issue, we propose a closed-loop tactile stimulation training protocol, in which tactile stimulation training is incorporated within the closed neurofeedback loop, providing users with explicit guidance on how to correctly perform MI tasks. When a subject performs an incorrect MI trial, tactile-assisted MI training is provided to guide the user toward the correct brain state, while no training is given during correct performance.

RESULTS: The results from our study demonstrated that the proposed training protocol significantly enhances BCI decoding performance, with an improvement of 16.9%. Moreover, the BCI-deficiency rate was reduced by 61.5%. Further analysis revealed that the training process also led to enhanced motor imagery-related cortical activation.

CONCLUSION: The proposed training protocol significantly improved BCI decoding performance, enabling previously BCI-deficient users to surpass the 70% control threshold.

SIGNIFICANCE: This study demonstrates the effectiveness of closed-loop tactile-assisted training in enhancing BCI accessibility and efficiency, paving the way for more inclusive neurofeedback-based BCI training strategies.},
}

@article {pmid40227903,
year = {2025},
author = {Mai, X and Meng, J and Ding, Y and Zhu, X and Guan, C},
title = {SRRNet: Unseen SSVEP Response Regression from Stimulus for Cross-stimulus Transfer in SSVEP-BCIs.},
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.2025.3560434},
pmid = {40227903},
issn = {1558-0210},
abstract = {The prolonged calibration time required by steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) poses a significant challenge to real-life applications. Cross-stimulus transfer emerges as a promising solution, wherein a model trained on a subset of classes (seen classes) can predict both seen and unseen classes. Existing approaches extracted common components from SSVEP templates of seen classes to construct templates for unseen classes; however, they are limited by the class-specific activities and noise contained in these components, leading to imprecise templates that degrade classification performance. To address this issue, this study proposed an SSVEP Response Regression Network (SRRNet), which learned the regression mapping between sine-cosine reference signals and SSVEP templates using seen class data. This network reconstructed SSVEP templates for unseen classes utilizing their corresponding sine-cosine signals. Additionally, an SSVEP template regressing and spatial filtering (SRSF) framework was introduced, where both test data and SSVEP templates were projected by task-related component analysis (TRCA) spatial filters, and correlations were computed for target prediction. Comparative evaluations on two public datasets revealed that our method significantly outperformed state-of-the-art methods, elevating the information transfer rate (ITR) from 173.33 bits/min to 203.79 bits/min. By effectively modeling the regression from sine-cosine reference signals to SSVEP templates, SRRNet can construct SSVEP templates for unseen classes without training samples from those classes. By integrating regressed SSVEP templates with spatial filtering-based methods, our method enhances cross-stimulus transfer performance in SSVEP-BCIs, thus advancing their practical applicability. The code is available at https://github.com/MaiXiming/SRRNet.},
}

@article {pmid40227525,
year = {2025},
author = {Yan, L and Liu, Z and Wang, J and Yu, L},
title = {Integrating Hard Silicon for High-Performance Soft Electronics via Geometry Engineering.},
journal = {Nano-micro letters},
volume = {17},
number = {1},
pages = {218},
pmid = {40227525},
issn = {2150-5551},
abstract = {Soft electronics, which are designed to function under mechanical deformation (such as bending, stretching, and folding), have become essential in applications like wearable electronics, artificial skin, and brain-machine interfaces. Crystalline silicon is one of the most mature and reliable materials for high-performance electronics; however, its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics. Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials, such as transforming them into thin nanomembranes or nanowires. This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics, from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates, and ultimately to shaping silicon nanowires using vapor-liquid-solid or in-plane solid-liquid-solid techniques. We explore the latest developments in Si-based soft electronic devices, with applications in sensors, nanoprobes, robotics, and brain-machine interfaces. Finally, the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.},
}

@article {pmid40231170,
year = {2024},
author = {Cubillos, LH and Revach, G and Mender, MJ and Costello, JT and Temmar, H and Hite, A and Zutshi, D and Wallace, DM and Ni, X and Kelberman, MM and Willsey, MS and van Sloun, RJG and Shlezinger, N and Patil, P and Draelos, A and Chestek, CA},
title = {Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces.},
journal = {Advances in neural information processing systems},
volume = {37},
number = {},
pages = {133975-133998},
pmid = {40231170},
issn = {1049-5258},
abstract = {People with brain or spinal cord-related paralysis often need to rely on others for basic tasks, limiting their independence. A potential solution is brain-machine interfaces (BMIs), which could allow them to voluntarily control external devices (e.g., robotic arm) by decoding brain activity to movement commands. In the past decade, deep-learning decoders have achieved state-of-the-art results in most BMI applications, ranging from speech production to finger control. However, the 'black-box' nature of deep-learning decoders could lead to unexpected behaviors, resulting in major safety concerns in real-world physical control scenarios. In these applications, explainable but lower-performing decoders, such as the Kalman filter (KF), remain the norm. In this study, we designed a BMI decoder based on KalmanNet, an extension of the KF that augments its operation with recurrent neural networks to compute the Kalman gain. This results in a varying "trust" that shifts between inputs and dynamics. We used this algorithm to predict finger movements from the brain activity of two monkeys. We compared KalmanNet results offline (pre-recorded data, n = 13 days) and online (real-time predictions, n = 5 days) with a simple KF and two recent deep-learning algorithms: tcFNN (non-ReFIT version) and LSTM. KalmanNet achieved comparable or better results than other deep learning models in offline and online modes, relying on the dynamical model for stopping while depending more on neural inputs for initiating movements. We further validated this mechanism by implementing a heteroscedastic KF that used the same strategy, and it also approached state-of-the-art performance while remaining in the explainable domain of standard KFs. However, we also see two downsides to KalmanNet. KalmanNet shares the limited generalization ability of existing deep-learning decoders, and its usage of the KF as an inductive bias limits its performance in the presence of unseen noise distributions. Despite this trade-off, our analysis successfully integrates traditional controls and modern deep-learning approaches to motivate high-performing yet still explainable BMI designs.},
}

@article {pmid40226198,
year = {2025},
author = {Nirabi, A and Rahman, FA and Habaebi, MH and Sidek, KA and Yusoff, S},
title = {Cognitive load assessment through EEG: A dataset from arithmetic and Stroop tasks.},
journal = {Data in brief},
volume = {60},
number = {},
pages = {111477},
pmid = {40226198},
issn = {2352-3409},
abstract = {This study introduces a thoughtfully curated dataset comprising electroencephalogram (EEG) recordings designed to unravel mental stress patterns through the perspective of cognitive load. The dataset incorporates EEG signals obtained from 15 subjects, with a gender distribution of 8 females and 7 males, and a mean age of 21.5 years [1]. Recordings were collected during the subjects' engagement in diverse tasks, including the Stroop color-word test and arithmetic problem-solving tasks. The recordings are categorized into four classes representing varying levels of induced mental stress: normal, low, mid, and high. Each task was performed for a duration of 10-20 s, and three trials were conducted for comprehensive data collection. Employing an OpenBCI device with an 8-channel Cyton board, the EEG captures intricate responses of the frontal lobe to cognitive challenges posed by the Stroop and Arithmetic Tests, recorded at a sampling rate of 250 Hz. The proposed dataset serves as a valuable resource for advancing research in the realm of brain-computer interfaces and offers insights into identifying EEG patterns associated with stress. The proposed dataset serves as a valuable resource for researchers, offering insights into identifying EEG patterns that correlate with different stress states. By providing a solid foundation for the development of algorithms capable of detecting and classifying stress levels, the dataset supports innovations in non-invasive monitoring tools and contributes to personalized healthcare solutions that can adapt to the cognitive states of users. This study's foundation is crucial for advancing stress classification research, with significant implications for cognitive function and well-being.},
}

@article {pmid40225841,
year = {2025},
author = {Kashou, N},
title = {Editorial: New horizons in stroke management.},
journal = {Frontiers in human neuroscience},
volume = {19},
number = {},
pages = {1587791},
doi = {10.3389/fnhum.2025.1587791},
pmid = {40225841},
issn = {1662-5161},
}

@article {pmid40225573,
year = {2025},
author = {Bai, R and Jia, Y and Wang, B and Wang, Z and Han, G and Liang, L and Chen, L and Ming, Y and Zhu, G and Hsu, YC and Zhao, P and Zhang, Y and Liu, Z and Liu, C and Li, Z and Liu, Y},
title = {In vivo spatiotemporal mapping of proliferation activity in gliomas via water-exchange dynamic contrast-enhanced MRI.},
journal = {Theranostics},
volume = {15},
number = {10},
pages = {4693-4707},
pmid = {40225573},
issn = {1838-7640},
mesh = {*Glioma/diagnostic imaging/pathology ; *Magnetic Resonance Imaging/methods ; Animals ; Humans ; *Cell Proliferation ; Temozolomide/pharmacology ; Cell Line, Tumor ; *Contrast Media ; Aquaporin 4/metabolism ; *Brain Neoplasms/diagnostic imaging/pathology ; *Water/metabolism ; Mice ; },
abstract = {Proliferation activity mapping is crucial for the guidance of first biopsy and treatment evaluation of gliomas due to the highly heterogenous nature of glioma tumor. Here we propose and demonstrate an ease-of-use way of in vivo spatiotemporal mapping of proliferation activity by simply tracking transmembrane water dynamics with magnetic resonance imaging (MRI). Specifically, we demonstrated that proliferation activity can accelerate the transmembrane water transport in glioma cells. Method: The transmembrane water-efflux rate (k io) measured by water-exchange dynamic contrast-enhanced (DCE) MRI. Immunofluorescence, immunohistochemistry, and immunocytochemistry staining were used to validate results obtained from the in vivo imaging studies. Results: In glioma cell cultures, k io precisely followed the dynamic changes of proliferation activity in growth cycles and response to temozolomide (TMZ) treatment. In both animal glioma model and human glioma, k io linearly and strongly correlated with the spatial heterogeneity of intra-tumoral proliferation activity. More importantly, proliferation activity predicted by the single MRI parameter k io is much more accurate than those predicted by state-of-the-art methods using multimodal standard MRIs and advanced machine learning. Upregulated aquaporin 4 (AQP4) expression were observed in most proliferating glioma cells and the knockout of AQP4 could largely slow down proliferation activity, suggesting AQP4 is the potential molecule connecting MRI-k io with proliferation activity. Conclusion: This study provides an ease-of-use, accurate, and non-invasive imaging method for the spatiotemporal monitoring of proliferation activity in glioma.},
}

*Glioma/diagnostic imaging/pathology
*Magnetic Resonance Imaging/methods
Animals
Humans
*Cell Proliferation
Temozolomide/pharmacology
Cell Line, Tumor
*Contrast Media
Aquaporin 4/metabolism
*Brain Neoplasms/diagnostic imaging/pathology
*Water/metabolism
Mice

@article {pmid40223771,
year = {2025},
author = {Kapur, A and Van Til, M and Daignault-Newton, S and Seibel, C and Nagpal, S and Ippolito, GM and Smith, AL and Lucioni, A and Lee, U and Suskind, A and Anger, J and Chung, D and Reynolds, WS and Cameron, A and Tenggardjaja, C and Padmanabhan, P and Brucker, BM and , },
title = {Association Between Urodynamic Findings and Urinary Retention After Onabotulinumtoxin A for Idiopathic Overactive Bladder.},
journal = {Neurourology and urodynamics},
volume = {},
number = {},
pages = {},
doi = {10.1002/nau.70050},
pmid = {40223771},
issn = {1520-6777},
support = {//This secondary analysis did not receive any external sources of funding. Funding for the primary analysis which utilized the same original data set as the current study was Society of Urodynamics, Female Pelvic Medicine and Urogenital Reconstruction Foundation (SUFU); National Institutes of Health, Grant/Award Number: UL1TR002240./ ; },
abstract = {INTRODUCTION: Onabotulinumtoxin A (BTX-A) is a minimally invasive therapy for idiopathic overactive bladder (iOAB). Incomplete bladder emptying is a known risk of the procedure, with an overall rate as high as 20% in male and female patients. Risk factors for incomplete bladder emptying after BTX-A have been reported in the literature, but are widely variable amongst studies and therefore patients at increased risk of this adverse effect cannot easily be identified by clinicians. The aim of this study was to evaluate whether pre-procedure urodynamics (UDS) findings are associated with incomplete bladder emptying after intradetrusor BTX-A injection for iOAB.

METHODS: Data were analyzed from the SUFU Research Network (SURN) multi-institutional retrospective database. Men and women undergoing first-time injection of 100 units BTX-A for iOAB in 2016 were included. Subjects were excluded if they did not have record of pre-procedure and post-procedure (within 1 month) post-void residual volume (PVR). The primary outcome was incidence of urinary retention within 1 month after BTX-A, defined as PVR > 300 mL and/or initiation of self-catheterization or indwelling catheter. We assessed the association of pre-procedure UDS parameters with urinary retention using Wilcoxon rank tests, Fisher's exact test, and chi-squared tests.

RESULTS: A total of 167 subjects (141 women, 26 men) were included. Ninety-nine subjects (59%) had urodynamic data. Thirty-seven subjects (22%) had urinary retention within 1 month of BTX-A. There were no significant differences in age, gender, race, or body mass index between the retention and non-retention groups. There was no statistically significant difference in median Qmax between those who did and did not have postprocedure retention (10.0 vs. 14.3 mL/s respectively, p = 0.06). Mean PVR at the start of UDS was not statistically significant when comparing the retention and non-retention groups (22.5 vs. 10.0 mL respectively, p = 0.70). Bladder outlet obstruction index (BOOI), bladder contractility index (BCI), and presence of detrusor overactivity (DO) were not found to be associated with posttreatment retention.

CONCLUSION: This retrospective multi-institutional cohort study revealed that of patients who receive UDS before BTX-A, there are no significant UDS parameters or baseline demographic factors associated with incomplete bladder emptying after intradetrusor BTX-A injections for iOAB. Future studies that focus on better defining objective evidence-based predictors of incomplete emptying after BTX are needed to optimize patient perception of efficacy and satisfaction with this therapy.},
}

@article {pmid40223534,
year = {2025},
author = {Jung, M and Abu Shihada, J and Decke, S and Koschinski, L and Graff, PS and Maruri Pazmino, S and Höllig, A and Koch, H and Musall, S and Offenhäusser, A and Rincón Montes, V},
title = {Flexible 3D Kirigami Probes for In Vitro and In Vivo Neural Applications.},
journal = {Advanced materials (Deerfield Beach, Fla.)},
volume = {},
number = {},
pages = {e2418524},
doi = {10.1002/adma.202418524},
pmid = {40223534},
issn = {1521-4095},
support = {VH-NG-1611//Helmholtz Association/ ; GRK2610//Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)/ ; 424556709//Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)/ ; GRK2416//Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)/ ; 368482240//Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)/ ; },
abstract = {3D microelectrode arrays (MEAs) are gaining popularity as brain-machine interfaces and platforms for studying electrophysiological activity. Interactions with neural tissue depend on the electrochemical, mechanical, and spatial features of the recording platform. While planar or protruding 2D MEAs are limited in their ability to capture neural activity across layers, existing 3D platforms still require advancements in manufacturing scalability, spatial resolution, and tissue integration. In this work, a customizable, scalable, and straightforward approach to fabricate flexible 3D kirigami MEAs containing both surface and penetrating electrodes, designed to interact with the 3D space of neural tissue, is presented. These novel probes feature up to 512 electrodes distributed across 128 shanks in a single flexible device, with shank heights reaching up to 1 mm. The 3D kirigami MEAs are successfully deployed in several neural applications, both in vitro and in vivo, and identified spatially dependent electrophysiological activity patterns. Flexible 3D kirigami MEAs are therefore a powerful tool for large-scale electrical sampling of complex neural tissues while improving tissue integration and offering enhanced capabilities for analyzing neural disorders and disease models where high spatial resolution is required.},
}

@article {pmid40223097,
year = {2025},
author = {Wu, Y and Liu, Y and Yang, Y and Yao, MS and Yang, W and Shi, X and Yang, L and Li, D and Liu, Y and Yin, S and Lei, C and Zhang, M and Gee, JC and Yang, X and Wei, W and Gu, S},
title = {A concept-based interpretable model for the diagnosis of choroid neoplasias using multimodal data.},
journal = {Nature communications},
volume = {16},
number = {1},
pages = {3504},
pmid = {40223097},
issn = {2041-1723},
support = {62236009//National Science Foundation of China | Key Programme/ ; },
mesh = {Humans ; *Choroid Neoplasms/diagnosis/diagnostic imaging ; *Melanoma/diagnosis/diagnostic imaging ; Machine Learning ; Artificial Intelligence ; Female ; Uveal Melanoma ; Male ; *Uveal Neoplasms/diagnostic imaging/diagnosis ; Hemangioma/diagnosis/diagnostic imaging ; Middle Aged ; Diagnosis, Differential ; Multimodal Imaging/methods ; Adult ; },
abstract = {Diagnosing rare diseases remains a critical challenge in clinical practice, often requiring specialist expertise. Despite the promising potential of machine learning, the scarcity of data on rare diseases and the need for interpretable, reliable artificial intelligence (AI) models complicates development. This study introduces a multimodal concept-based interpretable model tailored to distinguish uveal melanoma (0.4-0.6 per million in Asians) from hemangioma and metastatic carcinoma following the clinical practice. We collected a comprehensive dataset on Asians to date on choroid neoplasm imaging with radiological reports, encompassing over 750 patients from 2013 to 2019. Our model integrates domain expert insights from radiological reports and differentiates between three types of choroidal tumors, achieving an F1 score of 0.91. This performance not only matches senior ophthalmologists but also improves the diagnostic accuracy of less experienced clinicians by 42%. The results underscore the potential of interpretable AI to enhance rare disease diagnosis and pave the way for future advancements in medical AI.},
}

Humans
*Choroid Neoplasms/diagnosis/diagnostic imaging
*Melanoma/diagnosis/diagnostic imaging
Machine Learning
Artificial Intelligence
Female
Uveal Melanoma
Male
*Uveal Neoplasms/diagnostic imaging/diagnosis
Hemangioma/diagnosis/diagnostic imaging
Middle Aged
Diagnosis, Differential
Multimodal Imaging/methods
Adult

@article {pmid40223012,
year = {2025},
author = {Lorente-Piera, J and Manrique-Huarte, R and Picciafuoco, S and Lima, JP and Calavia, D and Serra, V and Manrique, M},
title = {Optimization of surgical interventions in auditory rehabilitation for chronic otitis media: comparative between passive middle ear implants, bone conduction implants, and active middle ear systems.},
journal = {European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery},
volume = {},
number = {},
pages = {},
pmid = {40223012},
issn = {1434-4726},
abstract = {INTRODUCTION: In otology consultations, patients with chronic otitis media (COM) often present as candidates for various hearing rehabilitation options. Selecting the most suitable approach requires careful consideration of patient preferences and expectations, the risk of disease progression, and the integrity of the bone conduction pathway. This study aims to evaluate and compare postoperative hearing outcomes in COM patients undergoing tympanoplasty (with or without passive middle ear implants), bone conduction systems (BCI), or active middle ear implants (AMEI). The objective is to assess the effectiveness of each surgical approach in hearing rehabilitation, considering the type and severity of hearing loss as well as the duration of the disease.

METHODS: Retrospective data analysis in a tertiary referral center studying average PTA across six different frequencies, speech perception at 65 dB, influence of Eustachian tube dysfunction, reintervention rate and adverse effects, and the influence of disease duration on functional outcomes via linear regression analysis.

RESULTS: 116 patients underwent surgery due to COM between 1998 and 2024. With a slight female predominance (54.31%). AMEIs and bone conduction devices provided the highest amplification in terms of PTA and speech discrimination, with a lower reintervention rate when comparing both groups with passive middle ear implants, OR in BCI group of 0.30 (0.10; 0.89, p = 0.030), OR in VSB group of 0.15 (0.04; 0.56, p = 0.005). It was also observed that a longer evolution time could be associated with greater auditory gain, with a p-value = 0.033.

CONCLUSIONS: The selection of each treatment option primarily depends on bone conduction thresholds, along with surgical risk, patient preferences, and MRI compatibility. In our study, AMEIs demonstrated the highest functional gain in terms of speech discrimination and frequency-specific amplification, followed by BCI. These findings support the use of implantable hearing solutions as effective alternatives for auditory rehabilitation in COM patients.},
}

@article {pmid40222332,
year = {2025},
author = {Choi, JY and Kim, YJ and Shin, JS and Choi, E and Kim, Y and Kim, MG and Kim, YT and Park, BS and Kim, JK and Kim, JG},
title = {Integrative metabolic profiling of hypothalamus and skeletal muscle in a mouse model of cancer cachexia.},
journal = {Biochemical and biophysical research communications},
volume = {763},
number = {},
pages = {151766},
doi = {10.1016/j.bbrc.2025.151766},
pmid = {40222332},
issn = {1090-2104},
abstract = {Cancer cachexia is a multifactorial metabolic syndrome characterized by progressive weight loss, muscle wasting, and systemic inflammation. Despite its clinical significance, the underlying mechanisms linking central and peripheral metabolic changes remain incompletely understood. In this study, we employed a murine model of cancer cachexia induced by intraperitoneal injection of Lewis lung carcinoma (LLC1) cells to investigate tissue-specific metabolic adaptations. Cachectic mice exhibited reduced food intake, body weight loss, impaired thermoregulation, and decreased energy expenditure. Metabolomic profiling of serum, skeletal muscle, and hypothalamus revealed distinct metabolic shifts, with increased fatty acid and ketone body utilization and altered amino acid metabolism. Notably, hypothalamic metabolite changes diverged from peripheral tissues, showing decreased neurotransmitter-related metabolites and enhanced lipid-based energy signatures. Gene expression analysis further confirmed upregulation of glycolysis- and lipid oxidation-related genes in both hypothalamus and muscle. These findings highlight coordinated yet compartmentalized metabolic remodeling in cancer cachexia and suggest that hypothalamic adaptations may play a central role in the systemic energy imbalance associated with cachexia progression.},
}

@article {pmid40221457,
year = {2025},
author = {Rybář, M and Poli, R and Daly, I},
title = {Simultaneous EEG and fNIRS recordings for semantic decoding of imagined animals and tools.},
journal = {Scientific data},
volume = {12},
number = {1},
pages = {613},
pmid = {40221457},
issn = {2052-4463},
mesh = {Humans ; *Electroencephalography ; *Brain-Computer Interfaces ; Spectroscopy, Near-Infrared ; *Semantics ; *Imagination ; Animals ; Male ; Female ; Adult ; Brain/physiology ; },
abstract = {Semantic neural decoding aims to identify which semantic concepts an individual focuses on at a given moment based on recordings of their brain activity. We investigated the feasibility of semantic neural decoding to develop a new type of brain-computer interface (BCI) that allows direct communication of semantic concepts, bypassing the character-by-character spelling used in current BCI systems. We provide data from our study to differentiate between two semantic categories of animals and tools during a silent naming task and three intuitive sensory-based imagery tasks using visual, auditory, and tactile perception. Participants were instructed to visualize an object (animal or tool) in their minds, imagine the sounds produced by the object, and imagine the feeling of touching the object. Simultaneous electroencephalography (EEG) and near-infrared spectroscopy (fNIRS) signals were recorded from 12 participants. Additionally, EEG signals were recorded from 7 other participants in a follow-up experiment focusing solely on the auditory imagery task. These datasets can serve as a valuable resource for researchers investigating semantic neural decoding, brain-computer interfaces, and mental imagery.},
}

Humans
*Electroencephalography
*Brain-Computer Interfaces
Spectroscopy, Near-Infrared
*Semantics
*Imagination
Animals
Male
Female
Adult
Brain/physiology

@article {pmid40219565,
year = {2025},
author = {Liu, N and Man, L and He, F and Huang, G and Zhai, J},
title = {[Correlation between urination intermittences and urodynamic parameters in benign prostatic hyperplasia patients].},
journal = {Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences},
volume = {57},
number = {2},
pages = {328-333},
pmid = {40219565},
issn = {1671-167X},
mesh = {Humans ; Male ; *Prostatic Hyperplasia/physiopathology/complications ; *Urodynamics/physiology ; Aged ; Retrospective Studies ; Middle Aged ; Aged, 80 and over ; *Urination/physiology ; Urinary Bladder Neck Obstruction/physiopathology ; Urinary Bladder/physiopathology ; },
abstract = {OBJECTIVE: To explore the impact factors and the clinical significance of the urination intermittences in benign prostatic hyperplasia (BPH) patients.

METHODS: A retrospective study was performed in BPH patients who underwent urodynamic studies in Beijing Jishuitan Hospital form January 2016 to June 2021. The patients were aged 45 to 84 years with a median age of 63 years, and all the patients had no previous history of neurological disease and had no positive findings in neurological examinations. All the patients had free uroflometry followed by urethral catheterization and urodynamic tests. The voiding work of bladder was calculated using the detrusor power curve method, and the voiding power of bladder and the voiding energy consumption were also calculated. The frequency of urination intermittences generated in uroflometry was also recorded and the patients were divided into different groups according to it. The detrusor pressure at maximal flow rate (PdetQmax), the maximal flow rate (Qmax), the bladder contractile index (BCI), the bladder outlet obstruction index (BOOI), the voiding work, the voiding power, and the voiding energy consumption were compared among the different groups. Multiva-riate analyses associated with presence of urination intermittences were performed using step-wise Logistic regressions.

RESULTS: There were 272 patients included in this study, of whom, 179 had no urination intermittence (group A), 46 had urination intermittence for only one time (group B), 22 had urination intermittence for two times (group C), and 25 had urination intermittence for three times and more (group D). The BCI were 113.4±28.2, 101.0±30.2, 83.3±30.2, 81.0±30.5 in groups A, B, C, and D, respectively; The voiding power were (29.2±14.8) mW, (16.4±9.6) mW, (14.5±7.1) mW, (8.5±5.0) mW in groups A, B, C, and D, respectively, and the differences were significant (P < 0.05). The BOOI were 41.6±29.3, 46.4±31.0, 41.4±29.0, 42.7±22.8 in groups A, B, C, and D, respectively; The voiding energy consumption were (5.41±2.21) J/L, (4.83±2.31) J/L, (5.02±2.54) J/L, (4.39±2.03) J/L in groups A, B, C, and D, respectively, and the differences were insignificant (P>0.05). Among the patients, 179 cases were negative in presence of urination intermittences and 93 cases were positive. Step-wise Logistic regression analysis showed that bladder power (OR=0.814, 95%CI: 0.765-0.866, P < 0.001), BCI (OR=1.023, 95%CI: 1.008-1.038, P=0.003), and bladder work (OR=2.232, 95%CI: 1.191-4.184, P=0.012) were independent risk factors for urination intermittences in the BPH patients.

CONCLUSION: The presence of urination intermittences in the BPH patients was mainly influenced by bladder contractile functions, and was irrelevant to the degree of bladder outlet obstruction. The increase of frequency of urination intermittences seemed to be a sign of the decrease of the bladder contractile functions in the BPH patients.},
}

Humans
Male
*Prostatic Hyperplasia/physiopathology/complications
*Urodynamics/physiology
Aged
Retrospective Studies
Middle Aged
Aged, 80 and over
*Urination/physiology
Urinary Bladder Neck Obstruction/physiopathology
Urinary Bladder/physiopathology

@article {pmid40218833,
year = {2025},
author = {Ranjbar Koleibi, E and Lemaire, W and Koua, K and Benhouria, M and Bostani, R and Serri Mazandarani, M and Gauthier, LP and Besrour, M and Ménard, J and Majdoub, M and Gosselin, B and Roy, S and Fontaine, R},
title = {Design and Implementation of a Low-Power Biopotential Amplifier in 28 nm CMOS Technology with a Compact Die-Area of 2500 μm[2] and an Ultra-High Input Impedance.},
journal = {Sensors (Basel, Switzerland)},
volume = {25},
number = {7},
pages = {},
pmid = {40218833},
issn = {1424-8220},
abstract = {Neural signal recording demands compact, low-power, high-performance amplifiers, to enable large-scale, multi-channel electrode arrays. This work presents a bioamplifier optimized for action potential detection, designed using TSMC 28 nm HPC CMOS technology. The amplifier integrates an active low-pass filter, eliminating bulky DC-blocking capacitors and significantly reducing the size and power consumption. It achieved a high input impedance of 105.5 GΩ, ensuring minimal signal attenuation. Simulation and measurement results demonstrated a mid-band gain of 58 dB, a -3 dB bandwidth of 7 kHz, and an input-referred noise of 11.1 μVrms, corresponding to a noise efficiency factor (NEF) of 8.4. The design occupies a compact area of 2500 μm2, making it smaller than previous implementations for similar applications. Additionally, it operates with an ultra-low power consumption of 3.4 μW from a 1.2 V supply, yielding a power efficiency factor (PEF) of 85 and an area efficiency factor of 0.21. These features make the proposed amplifier well suited for multi-site in-skull neural recording systems, addressing critical constraints regarding miniaturization and power efficiency.},
}

@article {pmid40218817,
year = {2025},
author = {Andreev, A and Cattan, G and Congedo, M},
title = {The Riemannian Means Field Classifier for EEG-Based BCI Data.},
journal = {Sensors (Basel, Switzerland)},
volume = {25},
number = {7},
pages = {},
pmid = {40218817},
issn = {1424-8220},
mesh = {*Brain-Computer Interfaces ; Humans ; *Electroencephalography/methods ; Algorithms ; Signal Processing, Computer-Assisted ; },
abstract = {: A substantial amount of research has demonstrated the robustness and accuracy of the Riemannian minimum distance to mean (MDM) classifier for all kinds of EEG-based brain-computer interfaces (BCIs). This classifier is simple, fully deterministic, robust to noise, computationally efficient, and prone to transfer learning. Its training is very simple, requiring just the computation of a geometric mean of a symmetric positive-definite (SPD) matrix per class. We propose an improvement of the MDM involving a number of power means of SPD matrices instead of the sole geometric mean. By the analysis of 20 public databases, 10 for the motor-imagery BCI paradigm and 10 for the P300 BCI paradigm, comprising 587 individuals in total, we show that the proposed classifier clearly outperforms the MDM, approaching the state-of-the art in terms of performance while retaining the simplicity and the deterministic behavior. In order to promote reproducible research, our code will be released as open source.},
}

*Brain-Computer Interfaces
Humans
*Electroencephalography/methods
Algorithms
Signal Processing, Computer-Assisted

@article {pmid40218770,
year = {2025},
author = {Gómez-Morales, ÓW and Collazos-Huertas, DF and Álvarez-Meza, AM and Castellanos-Dominguez, CG},
title = {EEG Signal Prediction for Motor Imagery Classification in Brain-Computer Interfaces.},
journal = {Sensors (Basel, Switzerland)},
volume = {25},
number = {7},
pages = {},
pmid = {40218770},
issn = {1424-8220},
mesh = {*Brain-Computer Interfaces ; *Electroencephalography/methods ; Humans ; *Signal Processing, Computer-Assisted ; *Imagination/physiology ; Algorithms ; Male ; Adult ; *Brain/physiology ; Female ; },
abstract = {Brain-computer interfaces (BCIs) based on motor imagery (MI) generally require EEG signals recorded from a large number of electrodes distributed across the cranial surface to achieve accurate MI classification. Not only does this entail long preparation times and high costs, but it also carries the risk of losing valuable information when an electrode is damaged, further limiting its practical applicability. In this study, a signal prediction-based method is proposed to achieve high accuracy in MI classification using EEG signals recorded from only a small number of electrodes. The signal prediction model was constructed using the elastic net regression technique, allowing for the estimation of EEG signals from 22 complete channels based on just 8 centrally located channels. The predicted EEG signals from the complete channels were used for feature extraction and MI classification. The results obtained indicate a notable efficacy of the proposed prediction method, showing an average performance of 78.16% in classification accuracy. The proposed method demonstrated superior performance compared to the traditional approach that used few-channel EEG and also achieved better results than the traditional method based on full-channel EEG. Although accuracy varies among subjects, from 62.30% to an impressive 95.24%, these data indicate the capability of the method to provide accurate estimates from a reduced set of electrodes. This performance highlights its potential to be implemented in practical MI-based BCI applications, thereby mitigating the time and cost constraints associated with systems that require a high density of electrodes.},
}

*Brain-Computer Interfaces
*Electroencephalography/methods
Humans
*Signal Processing, Computer-Assisted
*Imagination/physiology
Algorithms
Male
Adult
*Brain/physiology
Female

@article {pmid25761881,
year = {2015},
author = {Feng, X and Zhang, Y and Shao, N and Wang, Y and Zhuang, Z and Wu, P and Lee, MJ and Liu, Y and Wang, X and Zhuang, J and Delpire, E and Gu, D and Cai, H},
title = {Aldosterone modulates thiazide-sensitive sodium chloride cotransporter abundance via DUSP6-mediated ERK1/2 signaling pathway.},
journal = {American journal of physiology. Renal physiology},
volume = {308},
number = {10},
pages = {F1119-27},
pmid = {25761881},
issn = {1522-1466},
support = {DK093501/DK/NIDDK NIH HHS/United States ; K08 DK068226S-1/DK/NIDDK NIH HHS/United States ; R01 GM074771/GM/NIGMS NIH HHS/United States ; GM074771/GM/NIGMS NIH HHS/United States ; I01 BX000994/BX/BLRD VA/United States ; },
mesh = {Aldosterone/metabolism/*pharmacology ; Animals ; Dual Specificity Phosphatase 6/*metabolism ; Electrolytes/metabolism ; MAP Kinase Signaling System/*drug effects/physiology ; Mice ; Mice, Knockout ; Models, Animal ; Phosphorylation/drug effects/physiology ; Protein Serine-Threonine Kinases/*deficiency/genetics/metabolism ; Signal Transduction/drug effects/physiology ; Sodium Chloride Symporters/*drug effects/*metabolism ; Sodium Chloride, Dietary/pharmacology ; Thiazides/*pharmacology ; Ubiquitination/drug effects/physiology ; },
abstract = {Thiazide-sensitive sodium chloride cotransporter (NCC) plays an important role in maintaining blood pressure. Aldosterone is known to modulate NCC abundance. Previous studies reported that dietary salts modulated NCC abundance through either WNK4 [with no lysine (k) kinase 4]-SPAK (Ste20-related proline alanine-rich kinase) or WNK4-extracellular signal-regulated kinase-1 and -2 (ERK1/2) signaling pathways. To exclude the influence of SPAK signaling pathway on the role of the aldosterone-mediated ERK1/2 pathway in NCC regulation, we investigated the effects of dietary salt changes and aldosterone on NCC abundance in SPAK knockout (KO) mice. We found that in SPAK KO mice low-salt diet significantly increased total NCC abundance while reducing ERK1/2 phosphorylation, whereas high-salt diet decreased total NCC while increasing ERK1/2 phosphorylation. Importantly, exogenous aldosterone administration increased total NCC abundance in SPAK KO mice while increasing DUSP6 expression, an ERK1/2-specific phosphatase, and led to decreasing ERK1/2 phosphorylation without changing the ratio of phospho-T53-NCC/total NCC. In mouse distal convoluted tubule (mDCT) cells, aldosterone increased DUSP6 expression while reducing ERK1/2 phosphorylation. DUSP6 Knockdown increased ERK1/2 phosphorylation while reducing total NCC expression. Inhibition of DUSP6 by (E)-2-benzylidene-3-(cyclohexylamino)-2,3-dihydro-1H-inden-1-one increased ERK1/2 phosphorylation and reversed the aldosterone-mediated increments of NCC partly by increasing NCC ubiquitination. Therefore, these data suggest that aldosterone modulates NCC abundance via altering NCC ubiquitination through a DUSP6-dependent ERK1/2 signal pathway in SPAK KO mice and part of the effects of dietary salt changes may be mediated by aldosterone in the DCTs.},
}

Aldosterone/metabolism/*pharmacology
Animals
Dual Specificity Phosphatase 6/*metabolism
Electrolytes/metabolism
MAP Kinase Signaling System/*drug effects/physiology
Mice
Mice, Knockout
Models, Animal
Phosphorylation/drug effects/physiology
Protein Serine-Threonine Kinases/*deficiency/genetics/metabolism
Signal Transduction/drug effects/physiology
Sodium Chloride Symporters/*drug effects/*metabolism
Sodium Chloride, Dietary/pharmacology
Thiazides/*pharmacology
Ubiquitination/drug effects/physiology

@article {pmid24970835,
year = {2014},
author = {Feeney, A and Nilsson, E and Skinner, MK},
title = {Cytokine (IL16) and tyrphostin actions on ovarian primordial follicle development.},
journal = {Reproduction (Cambridge, England)},
volume = {148},
number = {3},
pages = {321-331},
pmid = {24970835},
issn = {1741-7899},
support = {R01 ES012974/ES/NIEHS NIH HHS/United States ; R01 HD048898/HD/NICHD NIH HHS/United States ; },
mesh = {Animals ; CD4 Antigens/metabolism ; Female ; Interleukin-16/*metabolism ; Ovarian Follicle/growth & development/*metabolism ; Ovary/growth & development/*metabolism ; Rats ; Rats, Sprague-Dawley ; Tyrphostins/*metabolism ; },
abstract = {An ovarian follicle is composed of an oocyte and surrounding theca and granulosa cells. Oocytes are stored in an arrested state within primordial follicles until they are signaled to re-initiate development by undergoing primordial-to-primary follicle transition. Previous gene bionetwork analyses of primordial follicle development identified a number of critical cytokine signaling pathways and genes potentially involved in the process. In the current study, candidate regulatory genes and pathways from the gene network analyses were tested for their effects on the formation of primordial follicles (follicle assembly) and on primordial follicle transition using whole ovary organ culture experiments. Observations indicate that the tyrphostin inhibitor (E)-2-benzylidene-3-(cyclohexylamino)-2,3-dihydro-1H-inden-1-one increased follicle assembly significantly, supporting a role for the MAPK signaling pathway in follicle assembly. The cytokine interleukin 16 (IL16) promotes primordial-to-primary follicle transition as compared with the controls, where as Delta-like ligand 4 (DLL4) and WNT-3A treatments have no effect. Immunohistochemical experiments demonstrated the localization of both the cytokine IL16 and its receptor CD4 in the granulosa cells surrounding each oocyte within the ovarian follicle. The tyrphostin LDN193189 (LDN) is an inhibitor of the bone morphogenic protein receptor 1 within the TGFB signaling pathway and was found to promote the primordial-to-primary follicle transition. Observations support the importance of cytokines (i.e., IL16) and cytokine signaling pathways in the regulation of early follicle development. Insights into regulatory factors affecting early primordial follicle development are provided that may associate with ovarian disease and translate to improved therapy in the future.},
}

Animals
CD4 Antigens/metabolism
Female
Interleukin-16/*metabolism
Ovarian Follicle/growth & development/*metabolism
Ovary/growth & development/*metabolism
Rats
Rats, Sprague-Dawley
Tyrphostins/*metabolism

@article {pmid24842488,
year = {2014},
author = {Liu, L and Doran, S and Xu, Y and Manwani, B and Ritzel, R and Benashski, S and McCullough, L and Li, J},
title = {Inhibition of mitogen-activated protein kinase phosphatase-1 (MKP-1) increases experimental stroke injury.},
journal = {Experimental neurology},
volume = {261},
number = {},
pages = {404-411},
pmid = {24842488},
issn = {1090-2430},
support = {R01 NS078446/NS/NINDS NIH HHS/United States ; R21 NS079137/NS/NINDS NIH HHS/United States ; R21NS079137/NS/NINDS NIH HHS/United States ; },
mesh = {Animals ; Brain Injuries/etiology/prevention & control ; Cyclohexylamines/adverse effects ; Disease Models, Animal ; Dose-Response Relationship, Drug ; Dual Specificity Phosphatase 1/*deficiency/genetics ; Encephalitis/*etiology ; Enzyme Activation/drug effects/genetics ; Enzyme Inhibitors/pharmacology ; Gene Expression Regulation, Enzymologic/drug effects/*genetics ; Indenes/adverse effects ; Infarction, Middle Cerebral Artery/*complications/*etiology/genetics ; MAP Kinase Kinase 4/metabolism ; Male ; Mice, Knockout ; Neurologic Examination ; p38 Mitogen-Activated Protein Kinases/metabolism ; },
abstract = {BACKGROUND AND PURPOSE: Activation of mitogen-activated protein kinases (MAPKs), particularly c-jun-N-terminal kinases (JNK) and p38 exacerbates stroke injury by provoking pro-apoptotic and pro-inflammatory cellular signaling. MAPK phosphatase-1 (MKP-1) restrains the over-activation of MAPKs via rapid de-phosphorylation of the MAPKs. We therefore examined the role of MKP-1 in stroke and studied its inhibitory effects on MAPKs after experimental stroke.

METHODS: Male mice were subjected to transient middle cerebral artery occlusion (MCAO). MKP-1 knockout (KO) mice and a MKP-1 pharmacological inhibitor were utilized. We utilized flow cytometry, immunohistochemistry (IHC), and Western blots analysis to explore MKP-1 signaling and its effects on apoptosis/inflammation in the brain and specifically in microglia after stroke.

RESULTS: MKP-1 was highly expressed in the nuclei of both neurons and microglia after stroke. MKP-1 genetic deletion exacerbated stroke outcome by increasing infarct, neurological deficits and hemorrhagic transformation. Additionally, delayed treatment of the MKP-1 pharmacological inhibitor worsened stroke outcome in wild type (WT) mice but had no effect in MKP-1 KO mice. Furthermore, MKP-1 deletion led to increased c-jun-N-terminal kinase (JNK) activation and microglial p38 activation after stroke. Finally, MKP-1 deletion or inhibition increased inflammatory and apoptotic response as evidenced by the increased levels of interleukin-6 (IL-6), tumor necrosis factor α (TNFα), ratio of p-c-jun/c-jun and cleaved caspase-3 following ischemia.

CONCLUSIONS: We have demonstrated that MKP-1 signaling is an endogenous protective mechanism in stroke. Our data imply that MKP-1 possesses anti-apoptotic and anti-inflammatory properties by simultaneously controlling the activities of JNK and microglial p38.},
}

Animals
Brain Injuries/etiology/prevention & control
Cyclohexylamines/adverse effects
Disease Models, Animal
Dose-Response Relationship, Drug
Dual Specificity Phosphatase 1/*deficiency/genetics
Encephalitis/*etiology
Enzyme Activation/drug effects/genetics
Enzyme Inhibitors/pharmacology
Gene Expression Regulation, Enzymologic/drug effects/*genetics
Indenes/adverse effects
Infarction, Middle Cerebral Artery/*complications/*etiology/genetics
MAP Kinase Kinase 4/metabolism
Male
Mice, Knockout
Neurologic Examination
p38 Mitogen-Activated Protein Kinases/metabolism

@article {pmid23023500,
year = {2012},
author = {Li, G and Yu, M and Lee, WW and Tsang, M and Krishnan, E and Weyand, CM and Goronzy, JJ},
title = {Decline in miR-181a expression with age impairs T cell receptor sensitivity by increasing DUSP6 activity.},
journal = {Nature medicine},
volume = {18},
number = {10},
pages = {1518-1524},
pmid = {23023500},
issn = {1546-170X},
support = {R01 AI044142/AI/NIAID NIH HHS/United States ; P01 HL058000/HL/NHLBI NIH HHS/United States ; U19 AI090019/AI/NIAID NIH HHS/United States ; R01 EY011916/EY/NEI NIH HHS/United States ; R01 AG015043/AG/NIA NIH HHS/United States ; U19 AI057266/AI/NIAID NIH HHS/United States ; R01 AR042527/AR/NIAMS NIH HHS/United States ; },
mesh = {Adult ; Aged ; Aged, 80 and over ; Aging/*immunology ; CD4-Positive T-Lymphocytes/*immunology/*metabolism ; Cell Differentiation ; Cell Proliferation ; Cells, Cultured ; Cyclohexylamines/pharmacology ; Dual Specificity Phosphatase 6/*metabolism ; Extracellular Signal-Regulated MAP Kinases/genetics/metabolism ; Female ; Humans ; Indenes/pharmacology ; Lymphocyte Activation ; MAP Kinase Signaling System ; Male ; MicroRNAs/*metabolism ; Middle Aged ; Phosphorylation ; Receptors, Antigen, T-Cell/genetics/*immunology ; ZAP-70 Protein-Tyrosine Kinase/metabolism ; },
abstract = {The ability of the human immune system to respond to vaccination declines with age. We identified an age-associated defect in T cell receptor (TCR)-induced extracellular signal-regulated kinase (ERK) phosphorylation in naive CD4(+) T cells, whereas other signals, such as ζ chain-associated protein kinase 70 (ZAP70) and phospholipase C-γ1 phosphorylation, were not impaired. The defective ERK signaling was caused by the dual specific phosphatase 6 (DUSP6), whose protein expression increased with age due to a decline in repression by miR-181a. Reconstitution of miR-181a lowered DUSP6 expression in naive CD4(+) T cells in elderly individuals. DUSP6 repression using miR-181a or specific siRNA and DUSP6 inhibition by the allosteric inhibitor (E)-2-benzylidene-3-(cyclohexylamino)-2,3-dihydro-1H-inden-1-one improved CD4(+) T cell responses, as seen by increased expression of activation markers, improved proliferation and supported preferential T helper type 1 cell differentiation. DUSP6 is a potential intervention target for restoring T cell responses in the elderly, which may augment the effectiveness of vaccination.},
}

Adult
Aged
Aged, 80 and over
Aging/*immunology
CD4-Positive T-Lymphocytes/*immunology/*metabolism
Cell Differentiation
Cell Proliferation
Cells, Cultured
Cyclohexylamines/pharmacology
Dual Specificity Phosphatase 6/*metabolism
Extracellular Signal-Regulated MAP Kinases/genetics/metabolism
Female
Humans
Indenes/pharmacology
Lymphocyte Activation
MAP Kinase Signaling System
Male
MicroRNAs/*metabolism
Middle Aged
Phosphorylation
Receptors, Antigen, T-Cell/genetics/*immunology
ZAP-70 Protein-Tyrosine Kinase/metabolism

@article {pmid40218647,
year = {2025},
author = {Xu, H and Hassan, SA and Haider, W and Sun, Y and Yu, X},
title = {A Frequency-Shifting Variational Mode Decomposition-Based Approach to MI-EEG Signal Classification for BCIs.},
journal = {Sensors (Basel, Switzerland)},
volume = {25},
number = {7},
pages = {},
doi = {10.3390/s25072134},
pmid = {40218647},
issn = {1424-8220},
support = {U2033202, U1333119//National Natural Science Foundation of China and Civil Aviation Administration of China/ ; 52172387//National Natural Science Foundation of China/ ; ILA22032-1A//Fundamental Research Funds for the Central Universities/ ; 2022Z071052001//Aeronautical Science Foundation of China/ ; 2022JGZ14//Northwestern Polytechnical University/ ; },
mesh = {*Electroencephalography/methods ; Humans ; *Signal Processing, Computer-Assisted ; Support Vector Machine ; Neural Networks, Computer ; *Brain-Computer Interfaces ; Algorithms ; Brain/physiology ; },
abstract = {Electroencephalogram (EEG) signal analysis is crucial for understanding neural activity and advancing diagnostics in neurology. However, traditional signal decomposition (SD) techniques are hindered by two critical issues, mode mixing and mode aliasing, that compromise the quality of the decomposed signal. These challenges result in poor signal integrity, which significantly affects the accuracy of subsequent EEG interpretations and classifications. As EEG analysis is widely used in diagnosing conditions such as epilepsy, brain injuries, and sleep disorders, the impact of these shortcomings can be far-reaching, leading to misdiagnoses or delayed treatments. Despite extensive research on SD techniques, these issues remain largely unresolved, emphasizing the urgent need for a more reliable and precise approach. This study proposes a novel solution through the frequency-shifting variational mode decomposition (FS-VMD) method, which overcomes the limitations of traditional SD techniques by providing better resolution of intrinsic mode functions (IMFs). The FS-VMD method works by extracting and shifting the fundamental frequency of the EEG signal to a lower frequency range, followed by an iterative decomposition process that enhances signal clarity and reduces mode aliasing. By integrating advanced feature selection techniques and classifiers such as support vector machines (SVM), convolutional neural networks (CNN), and feature-weighted k-nearest neighbors (FWKNN), this approach offers a significant improvement in classification accuracy, with SVM achieving up to 99.99% accuracy in the 18-channel EEG setup with a standard deviation of 0.25. The results demonstrate that FS-VMD can address the critical issues of mode mixing and aliasing, providing a more accurate and efficient solution for EEG signal analysis and diagnostics.},
}

*Electroencephalography/methods
Humans
*Signal Processing, Computer-Assisted
Support Vector Machine
Neural Networks, Computer
*Brain-Computer Interfaces
Algorithms
Brain/physiology

@article {pmid40215960,
year = {2025},
author = {Chen, LN and Zhou, H and Xi, K and Cheng, S and Liu, Y and Fu, Y and Ma, X and Xu, P and Ji, SY and Wang, WW and Shen, DD and Zhang, H and Shen, Q and Chai, R and Zhang, M and Yang, L and Han, F and Mao, C and Cai, X and Zhang, Y},
title = {Proton perception and activation of a proton-sensing GPCR.},
journal = {Molecular cell},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.molcel.2025.02.030},
pmid = {40215960},
issn = {1097-4164},
abstract = {Maintaining pH at cellular, tissular, and systemic levels is essential for human health. Proton-sensing GPCRs regulate physiological and pathological processes by sensing the extracellular acidity. However, the molecular mechanism of proton sensing and activation of these receptors remains elusive. Here, we present cryoelectron microscopy (cryo-EM) structures of human GPR4, a prototypical proton-sensing GPCR, in its inactive and active states. Our studies reveal that three extracellular histidine residues are crucial for proton sensing of human GPR4. The binding of protons induces substantial conformational changes in GPR4's ECLs, particularly in ECL2, which transforms from a helix-loop to a β-turn-β configuration. This transformation leads to the rearrangements of H-bond network and hydrophobic packing, relayed by non-canonical motifs to accommodate G proteins. Furthermore, the antagonist NE52-QQ57 hinders human GPR4 activation by preventing hydrophobic stacking rearrangement. Our findings provide a molecular framework for understanding the activation mechanism of a human proton-sensing GPCR, aiding future drug discovery.},
}

@article {pmid40215056,
year = {2025},
author = {Fernandez, E},
title = {Invited Session II: Visual Prosthetics: Bidirectional communication with the human visual brain: Towards an advanced cortical visual neuroprosthesis for the blind.},
journal = {Journal of vision},
volume = {25},
number = {5},
pages = {13},
doi = {10.1167/jov.25.5.13},
pmid = {40215056},
issn = {1534-7362},
mesh = {Humans ; *Visual Prosthesis ; *Visual Cortex/physiology/physiopathology ; *Blindness/physiopathology/rehabilitation ; Adult ; Phosphenes/physiology ; Male ; Photic Stimulation/methods ; Electrodes, Implanted ; Female ; Middle Aged ; *Visual Perception/physiology ; Microelectrodes ; Brain-Computer Interfaces ; },
abstract = {A long-held dream by scientists has been to directly transfer information to the visual cortex of blind individuals, to restore a rudimentary form of sight. However, in spite of all the progress in neuroelectronic interfaces, the biological and engineering problems for the success of cortical implants are much more complex than originally believed, and a clinical application has not yet been achieved. We will present our recent results regarding the implantation of intracortical microelectrodes in four blind volunteers (ClinicalTrials.gov identifier NCT02983370). Our findings demonstrate the safety and efficacy of chronic intracortical microstimulation via a large number of electrodes in humans, showing its high potential for restoring functional vision in the blind. The recorded neural activity and the stimulation parameters were stable over the whole experimental period, and multiple electrode stimulation evoked discriminable patterned perceptions that were retained over time. Moreover, there was a learning process that helped the subjects to recognize several simple and complex patterns. Additionally, our results show that we can accurately predict phosphene thresholds, brightness levels, and the number of perceived phosphenes from the recorded neural signals. These results highlight the potential for utilizing the neural activity of neighboring electrodes to accurately infer and control visual perceptions.},
}

Humans
*Visual Prosthesis
*Visual Cortex/physiology/physiopathology
*Blindness/physiopathology/rehabilitation
Adult
Phosphenes/physiology
Male
Photic Stimulation/methods
Electrodes, Implanted
Female
Middle Aged
*Visual Perception/physiology
Microelectrodes
Brain-Computer Interfaces

@article {pmid40213917,
year = {2025},
author = {Wang, N and Wang, Y and Guo, M and Wang, L and Wang, X and Zhu, N and Yang, J and Wang, L and Zheng, C and Ming, D},
title = {Dynamic gamma modulation of hippocampal place cells predominates development of theta sequences.},
journal = {eLife},
volume = {13},
number = {},
pages = {},
pmid = {40213917},
issn = {2050-084X},
support = {2022ZD0205000//National Science and Technology Innovation 2030 Major Project of China/ ; T2322021//National Natural Science Foundation of China/ ; 82271218//National Natural Science Foundation of China/ ; 12271272//National Natural Science Foundation of China/ ; 81925020//National Natural Science Foundation of China/ ; 82371886//National Natural Science Foundation of China/ ; 82202797//National Natural Science Foundation of China/ ; LG-TKN-202204-01//Space Brain Project from Lingang Laboratory/ ; 2022M712365//China Postdoctoral Science Foundation/ ; },
mesh = {Animals ; *Theta Rhythm/physiology ; Rats ; *Gamma Rhythm/physiology ; *Hippocampus/physiology/cytology ; *Place Cells/physiology ; Male ; Rats, Long-Evans ; },
abstract = {The experience-dependent spatial cognitive process requires sequential organization of hippocampal neural activities by theta rhythm, which develops to represent highly compressed information for rapid learning. However, how the theta sequences were developed in a finer timescale within theta cycles remains unclear. In this study, we found in rats that sweep-ahead structure of theta sequences developing with exploration was predominantly dependent on a relatively large proportion of FG-cells, that is a subset of place cells dominantly phase-locked to fast gamma rhythms. These ensembles integrated compressed spatial information by cells consistently firing at precessing slow gamma phases within the theta cycle. Accordingly, the sweep-ahead structure of FG-cell sequences was positively correlated with the intensity of slow gamma phase precession, in particular during early development of theta sequences. These findings highlight the dynamic network modulation by fast and slow gamma in the development of theta sequences which may further facilitate memory encoding and retrieval.},
}

Animals
*Theta Rhythm/physiology
Rats
*Gamma Rhythm/physiology
*Hippocampus/physiology/cytology
*Place Cells/physiology
Male
Rats, Long-Evans

@article {pmid40212471,
year = {2025},
author = {Feng, J and Li, Y and Huang, Z and Chen, Y and Lu, S and Hu, R and Hu, Q and Chen, Y and Wang, X and Fan, Y and He, J},
title = {Heterogeneous transfer learning model for improving the classification performance of fNIRS signals in motor imagery among cross-subject stroke patients.},
journal = {Frontiers in human neuroscience},
volume = {19},
number = {},
pages = {1555690},
pmid = {40212471},
issn = {1662-5161},
abstract = {INTRODUCTION: Motor imagery functional near-infrared spectroscopy (MI-fNIRS) offers precise monitoring of neural activity in stroke rehabilitation, yet accurate cross-subject classification remains challenging due to limited training samples and significant inter-subject variability. This study proposes a Cross-Subject Heterogeneous Transfer Learning Model (CHTLM) to enhance the generalization of MI-fNIRS signal classification in stroke patients.

METHODS: CHTLM leverages labeled electroencephalogram (EEG) data from healthy individuals as the source domain. An adaptive feature matching network aligns task-relevant feature maps and convolutional layers between source (EEG) and target (fNIRS) domains. Multi-scale fNIRS features are extracted, and a sparse Bayesian extreme learning machine classifies the fused deep learning features.

RESULTS: Experiments utilized two MI-fNIRS datasets from eight stroke patients pre- and post-rehabilitation. CHTLM achieved average accuracies of 0.831 (pre-rehabilitation) and 0.913 (post-rehabilitation), with mean AUCs of 0.887 and 0.930, respectively. Compared to five baselines, CHTLM improved accuracy by 8.6-10.5% pre-rehabilitation and 11.3-15.7% post-rehabilitation.

DISCUSSION: The model demonstrates robust cross-subject generalization by transferring task-specific knowledge from heterogeneous EEG data while addressing domain discrepancies. Its performance gains post-rehabilitation suggest clinical potential for monitoring recovery progress. CHTLM advances MI-fNIRS-based brain-computer interfaces in stroke rehabilitation by mitigating data scarcity and variability challenges.},
}

@article {pmid40210930,
year = {2025},
author = {Qi, W and Zhang, Y and Su, Y and Hui, Z and Li, S and Wang, H and Zhang, J and Shi, K and Wang, M and Zhou, L and Zhu, D},
title = {Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.},
journal = {Scientific reports},
volume = {15},
number = {1},
pages = {12285},
pmid = {40210930},
issn = {2045-2322},
mesh = {Humans ; *Cerebral Palsy/physiopathology/rehabilitation ; Child ; Male ; Female ; *Brain-Computer Interfaces ; Child, Preschool ; Electroencephalography ; *Robotics/methods ; *Lower Extremity/physiopathology ; },
abstract = {This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST) paradigms through EEG microstate and functional connectivity (FC) analysis, providing a theoretical basis for applying MI-BCI in the rehabilitation of children with cerebral palsy (CP). This study included 30 subjects aged 4-6 years with GMFCS II-III grade, diagnosed with CP and classified as spastic diplegia. They sequentially completed EEG signal acquisition under REST, MI, and MI-BCI conditions. Clustering analysis was used to analyze EEG microstates and extract EEG microstate temporal parameters. Additionally, the strength of brain FC in different frequency bands was analyzed to compare the differences under various conditions. Four microstate classes (A-D) were identified to best explain the datasets of three groups. Compared to REST, the average duration and coverage rate of microstate D under MI and MI-BCI significantly increased (P < 0.05), while their frequency and the coverage rate and frequency of microstate A decreased. Compared to MI, the average duration of microstate C under MI-BCI significantly decreased (P < 0.05), while the frequency of microstate B significantly increased (P < 0.05). Additionally, the transition probability results showed that other microstates under REST had a higher transition probability to microstate A, while under MI and MI-BCI, other microstates had a higher transition probability to microstate D. The brain network results revealed significant differences in brain network connectivity among REST, MI, and MI-BCI across different frequency bands. No FC differences were found between REST, MI, and MI-BCI in the α2 frequency band. In the δ and γ frequency bands, MI and MI-BCI both had greater inter-electrode connectivity strength than REST. In the θ frequency band, REST had greater inter-electrode connectivity strength than MI-BCI, while MI-BCI had greater inter-electrode connectivity strength than both REST and MI. In the α1 frequency band, MI-BCI had greater inter-electrode connectivity strength than REST, and in the β frequency band, MI-BCI had greater inter-electrode connectivity strength than MI. MI-BCI can significantly alter the brain activity patterns of children with CP, particularly by enhancing the activity intensity of EEG microstates related to attention, motor planning, and execution, as well as the brain FC strength in different frequency bands. It holds high application value in the lower limb motor rehabilitation of children with CP.},
}

Humans
*Cerebral Palsy/physiopathology/rehabilitation
Child
Male
Female
*Brain-Computer Interfaces
Child, Preschool
Electroencephalography
*Robotics/methods
*Lower Extremity/physiopathology

@article {pmid40210429,
year = {2025},
author = {Benioudakis, ES and Kalaitzaki, A and Karlafti, E and Kapageridou, E and Ahanov, O and Kontoninas, Z and Savopoulos, C and Didangelos, T},
title = {Psychometric Properties and Dimensionality of the Greek Version of the Hypoglycemic Confidence Scale.},
journal = {Journal of nursing measurement},
volume = {},
number = {},
pages = {},
doi = {10.1891/JNM-2024-0108},
pmid = {40210429},
issn = {1945-7049},
abstract = {Background and purpose: The prevalence of type 1 diabetes mellitus (T1D) is rising at an alarming rate and is projected to continue increasing in the coming years. The primary approach to preventing diabetes-related complications in individuals with T1D is the exogenous administration of insulin. However, this method can sometimes lead to hypoglycemia, a condition with a wide range of symptoms, including loss of consciousness, seizures, coma, and, in severe cases, death. This study aims to present the psychometric properties of the Greek translation of the Hypoglycemic Confidence Scale (HCS). The HCS measures an individual's sense of personal strength and comfort based on the belief that they possess the necessary resources to manage and prevent hypoglycemia-related complications. Methods: We conducted a forward and backward translation, along with a cultural adaptation, of the HCS into Greek. The psychometric properties of the scale were evaluated through confirmatory factor analysis. To assess the reliability, we calculated the intraclass correlation coefficient, while internal consistency was measured using Cronbach's coefficient α. Construct validity was evaluated through convergent and divergent validity, comparing the HCS-Gr with the Diabetes Quality of Life Brief Clinical Inventory (DQoL-BCI) and hemoglobin A1C levels. Differential validity was assessed using the known-groups method. Results: Ninety-seven adults with T1D, aged between 18 and 57 years (mean age: 38.6 ± 11.7), completed the HCS-Gr. The two structures of the HCS-Gr demonstrated strong internal consistency, with Cronbach's coefficient α values of 0.87 for the eight-item version and 0.86 for the nine-item version. Convergent validity was supported by moderate negative correlations between both HCS-Gr versions and the DQoL-BCI subscales and total score. The HCS-Gr also showed satisfactory test-retest reliability and differential validity, confirming its robustness as a psychometric tool. Conclusion: The HCS-Gr is a valid and reliable tool for assessing confidence (or self-efficacy) in managing hypoglycemic situations among individuals with T1D in Greece.},
}

@article {pmid40209829,
year = {2025},
author = {Ruiz Ibán, MA and García Navlet, M and Marco, SM and Diaz Heredia, J and Hernando, A and Ruiz Díaz, R and Vaquero Comino, C and Alvarez Villar, S and Ávila Lafuente, JL},
title = {AUGMENTATION WITH A BOVINE BIOINDUCTIVE COLLAGEN IMPLANT OF A POSTEROSUPERIOR CUFF REPAIR SHOWS LOWER RETEAR RATES BUT SIMILAR OUTCOMES COMPARED TO NO AUGMENTATION: 2-YEAR RESULTS OF A RANDOMIZED CONTROLLED TRIAL.},
journal = {Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.arthro.2025.03.057},
pmid = {40209829},
issn = {1526-3231},
abstract = {PURPOSE: To assess the clinical and radiological outcomes of the addition of a bioinductive collagen implant (BCI) over the repair of medium-to-large posterosuperior rotator cuff tears at 24-month follow-up.

METHODS: This is an update of a randomized controlled trial that was extended from one to two-year follow-up. 124 subjects with symptomatic full-thickness posterosuperior rotator cuff tears, with fatty infiltration Goutalier grade ≤2 were randomized to two groups in which a transosseous equivalent repair was performed alone (Control group) or with BCI applied over the repair (BCI group). The outcomes reassessed at 2-year follow-up were: Sugaya grade, retear rate and tendon thickness in MRI; and the clinical outcomes (pain levels, EQ-5D-5L, American Shoulder and Elbow Society[ASES] and Constant-Murley scores[CMS]).

RESULTS: There were no relevant differences in preoperative characteristics. There were no additional complications or reinterventions in the second year of follow-up. 114 (59 males-55 males, age=58.1[SD:7.35] years) of 124 randomized patients (91.9%), underwent MRI evaluation 25.4[1.95] months after surgery. There was a lower retear rate (12.3%[7/57]) in the BCI group compared to the Control group (35.1%[20/57]) (p=0.004; relative risk of retear 0.35[CI-95%:0.16 to 0.76]). Sugaya grade was also better in the BCI group (2.58[1.07] vs 3.14[1.19]; p=0.020). Two-year Clinical follow-up at 25.8[2.75] months performed in 114 of 124 patients(91.9%) showed improvements in both groups (p<0.001), with 87% improving more than the MCID for CMS and 90% for ASES, but there were no differences between groups. In subjects with both MRI and clinical assessment (n=112), those with an intact tendon presented better CMS(p=0.035), ASES(p=0.015) and pain(p=0.006) scores than those with a failed repair.

CONCLUSION: Augmentation with a BCI of a TOE repair in posterosuperior rotator cuff tears clearly reduces the retear rate at two-year follow-up without increased complication rates and similar clinical outcomes. Subjects with failed repairs had poorer clinical outcomes.

LEVEL OF EVIDENCE: Level 1, Randomized controlled trial.},
}

@article {pmid40209163,
year = {2025},
author = {Kurmanavičiūtė, D and Kataja, H and Parkkonen, L},
title = {Comparing MEG and EEG measurement set-ups for a brain-computer interface based on selective auditory attention.},
journal = {PloS one},
volume = {20},
number = {4},
pages = {e0319328},
pmid = {40209163},
issn = {1932-6203},
mesh = {Humans ; *Magnetoencephalography/methods ; *Electroencephalography/methods ; *Brain-Computer Interfaces ; Male ; Female ; Adult ; *Attention/physiology ; Young Adult ; Evoked Potentials, Auditory/physiology ; *Auditory Perception/physiology ; Support Vector Machine ; Acoustic Stimulation ; Algorithms ; },
abstract = {Auditory attention modulates auditory evoked responses to target vs. non-target sounds in electro- and magnetoencephalographic (EEG/MEG) recordings. Employing whole-scalp MEG recordings and offline classification algorithms has been shown to enable high accuracy in tracking the target of auditory attention. Here, we investigated the decrease in accuracy when moving from the whole-scalp MEG to lower channel count EEG recordings and when training the classifier only from the initial or middle part of the recording instead of extracting training trials throughout the recording. To this end, we recorded simultaneous MEG (306 channels) and EEG (64 channels) in 18 healthy volunteers while presented with concurrent streams of spoken "Yes"/"No" words and instructed to attend to one of them. We then trained support vector machine classifiers to predict the target of attention from unaveraged trials of MEG/EEG. Classifiers were trained on 204 MEG gradiometers or on EEG with 64, 30, nine or three channels with trials extracted randomly across or only from the beginning of the recording. The highest classification accuracy, 73.2% on average across the participants for one-second trials, was obtained with MEG when the training trials were randomly extracted throughout the recording. With EEG, the accuracy was 69%, 69%, 66%, and 61% when using 64, 30, nine, and three channels, respectively. When training the classifiers with the same amount of data but extracted only from the beginning of the recording, the accuracy dropped by 11%-units on average, causing the result from the three-channel EEG to fall below the chance level. The combination of five consecutive trials partially compensated for this drop such that it was one to 5%-units. Although moving from whole-scalp MEG to EEG reduces classification accuracy, usable auditory-attention-based brain-computer interfaces can be implemented with a small set of optimally placed EEG channels.},
}

Humans
*Magnetoencephalography/methods
*Electroencephalography/methods
*Brain-Computer Interfaces
Male
Female
Adult
*Attention/physiology
Young Adult
Evoked Potentials, Auditory/physiology
*Auditory Perception/physiology
Support Vector Machine
Acoustic Stimulation
Algorithms

@article {pmid40206150,
year = {2025},
author = {Zhang, H and Wang, X and Chen, G and Zhang, Y and Jian, X and He, F and Xu, M and Ming, D},
title = {Noninvasive Intracranial Source Signal Localization and Decoding with High Spatiotemporal Resolution.},
journal = {Cyborg and bionic systems (Washington, D.C.)},
volume = {6},
number = {},
pages = {0206},
pmid = {40206150},
issn = {2692-7632},
abstract = {High spatiotemporal resolution of noninvasive electroencephalography (EEG) signals is an important prerequisite for fine brain-computer manipulation. However, conventional scalp EEG has a low spatial resolution due to the volume conductor effect, making it difficult to accurately identify the intent of brain-computer manipulation. In recent years, transcranial focused ultrasound modulated EEG technology has increasingly become a research hotspot, which is expected to acquire noninvasive acoustoelectric coupling signals with a high spatial and temporal resolution. In view of this, this study established a transcranial focused ultrasound numerical simulation model and experimental platform based on a real brain model and a 128-array phased array, further constructed a 3-dimensional transcranial multisource dipole localization and decoding numerical simulation model and experimental platform based on the acoustic field platform, and developed a high-precision localization and decoding algorithm. The results show that the simulation-guided phased-array acoustic field experimental platform can achieve accurate focusing in both pure water and transcranial conditions within a safe threshold, with a modulation range of 10 mm, and the focal acoustic pressure can be enhanced by more than 200% compared with that of transducer self-focusing. In terms of dipole localization decoding results, the proposed algorithm in this study has a localization signal-to-noise ratio of 24.18 dB, which is 50.59% higher than that of the traditional algorithm, and the source signal decoding accuracy is greater than 0.85. This study provides a reliable experimental basis and technical support for high-spatiotemporal-resolution noninvasive EEG signal acquisition and precise brain-computer manipulation.},
}

@article {pmid40203098,
year = {2025},
author = {Sîmpetru, RC and Braun, DI and Simon, AU and März, M and Cnejevici, V and de Oliveira, DS and Weber, N and Walter, J and Franke, J and Höglinger, D and Prahm, C and Ponfick, M and Del Vecchio, A},
title = {MyoGestic: EMG interfacing framework for decoding multiple spared motor dimensions in individuals with neural lesions.},
journal = {Science advances},
volume = {11},
number = {15},
pages = {eads9150},
pmid = {40203098},
issn = {2375-2548},
mesh = {Humans ; Male ; Female ; Young Adult ; Adult ; Middle Aged ; *Electromyography/instrumentation ; *Spinal Cord Injuries/rehabilitation ; *Stroke Rehabilitation/instrumentation ; *Amputation, Surgical/rehabilitation ; *Brain-Computer Interfaces ; Machine Learning ; Psychomotor Performance ; Intention ; Software Validation ; },
abstract = {Restoring motor function in individuals with spinal cord injuries (SCIs), strokes, or amputations is a crucial challenge. Recent studies show that spared motor neurons can still be voluntarily controlled using surface electromyography (EMG), even without visible movement. To harness these signals, we developed a wireless, high-density EMG bracelet and a software framework, MyoGestic. Our system enables rapid adaptation of machine learning models to users' needs, allowing real-time decoding of spared motor dimensions. In our study, we successfully decoded motor intent from two participants with traumatic SCI, two with spinal stroke, and three with amputations in real time, achieving multiple controllable motor dimensions within minutes. The decoded neural signals could control a digitally rendered hand, an orthosis, a prosthesis, or a two-dimensional cursor. MyoGestic's participant-centered approach allows a collaborative and iterative development of myocontrol algorithms, bridging the gap between researcher and participant, to advance intuitive EMG interfaces for neural lesions.},
}

Humans
Male
Female
Young Adult
Adult
Middle Aged
*Electromyography/instrumentation
*Spinal Cord Injuries/rehabilitation
*Stroke Rehabilitation/instrumentation
*Amputation, Surgical/rehabilitation
*Brain-Computer Interfaces
Machine Learning
Psychomotor Performance
Intention
Software Validation

@article {pmid40205860,
year = {2025},
author = {Sun, Y and Yu, N and Chen, G and Liu, T and Wen, S and Chen, W},
title = {What Else Is Happening to the Mirror Neurons?-A Bibliometric Analysis of Mirror Neuron Research Trends and Future Directions (1996-2024).},
journal = {Brain and behavior},
volume = {15},
number = {4},
pages = {e70486},
doi = {10.1002/brb3.70486},
pmid = {40205860},
issn = {2162-3279},
support = {21BZX005//National Social Science Fund of China/ ; 21NDQN281YB//Philosophy and Social Sciences Project of Zhejiang Province/ ; 23QNYC19ZD//Special Project for Cultivating Leading Talents in Philosophy and Social Sciences of Zhejiang Province (Cultivation of Young Talents)/ ; },
mesh = {*Bibliometrics ; Humans ; *Mirror Neurons/physiology ; Neurosciences/trends ; Brain/physiology ; Animals ; },
abstract = {BACKGROUND: Since its discovery in the late 20th century, research on mirror neurons has become a pivotal area in neuroscience, linked to various cognitive and social functions. This bibliometric analysis explores the research trajectory, key research topics, and future trends in the field of mirror neuron research.

METHODS: We searched the Web of Science Core Collection (WoSCC) database for publications from 1996 to 2024 on mirror neuron research. Statistical and visualization analyses were performed using CiteSpace and VOSviewer.

RESULTS: Publication output on mirror neurons peaked in 2013 and remained active. High-impact journals such as Science, Brain, Neuron, PNAS, and NeuroImage frequently feature findings on the mirror neuron system, including its distribution, neural coding, and roles in intention understanding, affective empathy, motor learning, autism, and neurological disorders. Keyword clustering reveals major directions in cognitive neuroscience, motor neuroscience, and neurostimulation, whereas burst detection underscores the emerging significance of brain-computer interfaces (BCIs). Research methodologies have been evolving from traditional electrophysiological recordings to advanced techniques such as functional magnetic resonance imaging, transcranial magnetic stimulation, and BCIs, highlighting a dynamic, multidisciplinary progression.

CONCLUSIONS: This study identifies key areas associated with mirror neurons and anticipates that future work will integrate findings with artificial intelligence, clinical interventions, and novel neuroimaging techniques, providing new perspectives on complex socio-cognitive issues and their applications in both basic science and clinical practice.},
}

*Bibliometrics
Humans
*Mirror Neurons/physiology
Neurosciences/trends
Brain/physiology
Animals

@article {pmid40205038,
year = {2025},
author = {Yang, L and Guo, C and Zheng, Z and Dong, Y and Xie, Q and Lv, Z and Li, M and Lu, Y and Guo, X and Deng, R and Liu, Y and Feng, Y and Mu, R and Zhang, X and Ma, H and Chen, Z and Zhang, Z and Dong, Z and Yang, W and Zhang, X and Cui, Y},
title = {Stress dynamically modulates neuronal autophagy to gate depression onset.},
journal = {Nature},
volume = {},
number = {},
pages = {},
pmid = {40205038},
issn = {1476-4687},
abstract = {Chronic stress remodels brain homeostasis, in which persistent change leads to depressive disorders[1]. As a key modulator of brain homeostasis[2], it remains elusive whether and how brain autophagy is engaged in stress dynamics. Here we discover that acute stress activates, whereas chronic stress suppresses, autophagy mainly in the lateral habenula (LHb). Systemic administration of distinct antidepressant drugs similarly restores autophagy function in the LHb, suggesting LHb autophagy as a common antidepressant target. Genetic ablation of LHb neuronal autophagy promotes stress susceptibility, whereas enhancing LHb autophagy exerts rapid antidepressant-like effects. LHb autophagy controls neuronal excitability, synaptic transmission and plasticity by means of on-demand degradation of glutamate receptors. Collectively, this study shows a causal role of LHb autophagy in maintaining emotional homeostasis against stress. Disrupted LHb autophagy is implicated in the maladaptation to chronic stress, and its reversal by autophagy enhancers provides a new antidepressant strategy.},
}

@article {pmid40204716,
year = {2025},
author = {Amann, LK and Casasnovas, V and Gail, A},
title = {Visual target and task-critical feedback uncertainty impair different stages of reach planning in motor cortex.},
journal = {Nature communications},
volume = {16},
number = {1},
pages = {3372},
pmid = {40204716},
issn = {2041-1723},
support = {H2020-FETPROACT-16 732266 WP1//European Commission (EC)/ ; ZN3422//Niedersächsische Ministerium für Wissenschaft und Kultur (Lower Saxony Ministry of Science and Culture)/ ; SFB-889 C4//Deutsche Forschungsgemeinschaft (German Research Foundation)/ ; SFB 1690 B09//Deutsche Forschungsgemeinschaft (German Research Foundation)/ ; },
mesh = {Animals ; Macaca mulatta ; Male ; *Motor Cortex/physiology ; Uncertainty ; *Feedback, Sensory/physiology ; *Psychomotor Performance/physiology ; Movement/physiology ; Brain-Computer Interfaces ; Hand/physiology ; Visual Perception/physiology ; },
abstract = {Sensory uncertainty jeopardizes accurate movement. During reaching, visual uncertainty can affect the estimation of hand position (feedback) and the desired movement endpoint (target). While impairing motor learning, it is unclear how either form of uncertainty affects cortical reach goal encoding. We show that reach trajectories vary more with higher visual uncertainty of the target, but not the feedback. Accordingly, cortical motor goal activities in male rhesus monkeys are less accurate during planning and movement initiation under target but not feedback uncertainty. Yet, when monkeys critically depend on visual feedback to conduct reaches via a brain-computer interface, then visual feedback uncertainty impairs reach accuracy and neural motor goal encoding around movement initiation. Neural state space analyses reveal a dimension that separates population activity by uncertainty level in all tested conditions. Our findings demonstrate that while both target and feedback uncertainty always reflect in neural activity, uncertain feedback only deteriorates neural reach goal information and behavior when it is task-critical, i.e., when having to rely on the sensory feedback and no other more reliable sensory modalities are available. Further, uncertain target and feedback impair reach goal encoding in a time-dependent manner, suggesting that they are integrated during different stages of reach planning.},
}

Animals
Macaca mulatta
Male
*Motor Cortex/physiology
Uncertainty
*Feedback, Sensory/physiology
*Psychomotor Performance/physiology
Movement/physiology
Brain-Computer Interfaces
Hand/physiology
Visual Perception/physiology

@article {pmid40204228,
year = {2025},
author = {Hasegawa, R and Poulin, R},
title = {Effect of parasite infections on fish body condition: a systematic review and meta-analysis.},
journal = {International journal for parasitology},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.ijpara.2025.03.002},
pmid = {40204228},
issn = {1879-0135},
abstract = {Using host body condition indices (BCIs) based on the relationship between host body mass and length is a general and pervasive approach to assess the negative effects of parasites on host health. Although many researchers, especially fish biologists and fisheries managers, commonly utilize BCIs, the overall general patterns among BCI - infection relationships remain unclear. Here, we first systematically reviewed 985 fish BCI - infection relationships from 216 publications and investigated the factors affecting the strength and directionality of effects in BCI - infection relationships. We specifically predicted that the BCI measure used, parasite taxonomic group, and the infection measure used would influence the observed effect size and directionality of BCI - infection relationships. We found that most studies were heavily biased towards specific BCI measures such as Fulton's BCI and Relative BCI. Furthermore, studies using Fulton's BCI were more likely to report significant results compared with those using other BCI measures, suggesting that index choice could lead to an overestimation of the negative effects of parasites. Our meta-regressions uncovered that the use of parasite intensity as an infection measure and studies based on experimental rather than natural infections were more likely to report significant negative effects, however there were no differences among parasite taxonomic groups. Surprisingly, many studies, especially field studies, did not report significant negative correlations between BCI and infection, contrary to widespread expectations among researchers that parasites would negatively affect fish health. We discuss potential mechanisms underlying these results. Finally, we make several recommendations for the use of BCI - infection relationships in future studies.},
}

@article {pmid40204168,
year = {2025},
author = {Tan, H and Hu, YT and Goudswaard, A and Li, YJ and Balesar, R and Swaab, D and Bao, AM},
title = {Increased oxytocin/vasopressin ratio in bipolar disorder in a cohort of human postmortem adults.},
journal = {Neurobiology of disease},
volume = {},
number = {},
pages = {106904},
doi = {10.1016/j.nbd.2025.106904},
pmid = {40204168},
issn = {1095-953X},
abstract = {Bipolar disorder (BD) and major depressive disorder (MDD) share some common characteristics in stress-related brain circuits, but they also exhibit distinct symptoms. Our previous postmortem research on the immunoreactivity (ir) levels of neuropeptide oxytocin (OT) in the hypothalamic paraventricular nucleus (OT[PVN]) and some clinical research on plasma OT levels suggested that increased levels of OT is a potential trait marker for BD. However, dysregulation of the related neuropeptide arginine vasopressin (AVP), that often shows opposite effects for stress responses compared to OT has not been investigated in BD. Moreover, it remains so far unknown what the contribution may be of OT produced in the hypothalamic supraoptic nucleus (SON), another major source of OT (OT[SON]). Therefore, in the present postmortem study, alterations in levels of OT-ir and for the first time in AVP-ir were determined in the SON and PVN among patients with BD, MDD, and matched controls. We observed a significantly increased OT[PVN]-ir but relatively stable AVP[PVN]-ir in male BD, and a significantly decreased AVP[PVN]-ir but relatively stable OT[PVN]-ir in female BD patients. A significantly increased ratio of OT-ir/AVP-ir was observed only in BD patients in both, the PVN and SON. No significant changes in OT-ir or AVP-ir were found in MDD patients compared with controls. Our data illustrate a clear disease- and sex-specificity of the OT and AVP changes in BD. In addition, since increased AVP-ir was observed in female BD patients with lithium nephropathy, increased AVP may have a direct effect on symptoms of BD.},
}

@article {pmid40203859,
year = {2025},
author = {Pang, Y and Wang, X and Zhao, Z and Han, C and Gao, N},
title = {Multi-view collaborative ensemble classification for EEG signals based on 3D second-order difference plot and CSP.},
journal = {Physics in medicine and biology},
volume = {},
number = {},
pages = {},
doi = {10.1088/1361-6560/adcafa},
pmid = {40203859},
issn = {1361-6560},
abstract = {OBJECTIVE: EEG signal analysis methods based on electrical source imaging (ESI) technique have significantly improved classification accuracy and response time. However, for the refined and informative source signals, the current studies have not fully considered their dynamic variability in feature extraction and lacked an effective integration of their dynamic variability and spatial characteristics. Additionally, the adaptability and complementarity of classifiers have not been considered comprehensively. These two aspects lead to the issue of insufficient decoding of source signals, which still limits the application of brain-computer interface (BCI). To address these challenges, this paper proposes a multi-view collaborative ensemble classification method for EEG signals based on three-dimensional second-order difference plot (3D SODP) and common spatial pattern (CSP).

APPROACH: First, EEG signals are mapped to the source domain using the ESI technique, and then the source signals in the region of interest (ROI) are obtained. Next, features from three viewpoints of the source signals are extracted, including 3D SODP features, spatial features, and the weighted fusion of both. Finally, the extracted multi-view features are integrated with subject-specific sub-classifier combination, and a voting mechanism is used to determine the final classification.

MAIN RESULTS: The results show that the proposed method achieves classification accuracy of 81.3% and 82.6% respectively in two sessions of the OpenBMI dataset, which is nearly 5% higher than the state-of-the-art method, and maintains the analysis response time required for online BCI.

SIGNIFICANCE: This paper employs multi-view feature extraction to fully capture the characteristics of the source signals and enhances feature utilization through collaborative ensemble classification. The results demonstrate high accuracy and robust performance, providing a novel approach for online BCI.},
}

@article {pmid40203855,
year = {2025},
author = {Yin, S and Yue, Z and Qu, H and Wang, J and Shi, B and Zhang, J},
title = {Enhancing lower-limb motor imagery using a paradigm with visual and spatiotemporal tactile synchronized stimulation.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/adcaec},
pmid = {40203855},
issn = {1741-2552},
abstract = {UNLABELLED: Vibrotactile stimulation (VS) has been widely used as an appropriate motor imagery (MI) guidance strategy to improve MI performance. However, most vibrotactile stimulation induced by a single vibrator cannot provide spatiotemporal information of tactile sensation associated with the visual guidance of the imagined motion process, not vividly providing MI guidance for subjects.

METHODS: This paper proposed a paradigm with visual and spatiotemporal tactile synchronized stimulation (VSTSS) to provide vivid MI guidance to help subjects perform lower-limb MI tasks and improve MI-based brain-computer interface (MI-BCI) performance, with a focus on poorly performing subjects. The proposed paradigm provided subjects with the natural spatiotemporal tactile sensation associated with the visual guidance of the foot movement process during MI.

EXPERIMENTS: Fourteen healthy subjects were recruited to participate in the MI and Rest tasks and divided into good and poor performers. Furthermore, electrophysiological features and classification performance were analyzed to assess motor cortical activation and MI-BCI performance under no VS (NVS), VS, and VSTSS.

RESULTS: The phenomenon of event-related desynchronization (ERD) in the sensorimotor cortex during MI under the VSTSS was more pronounced compared to the NVS and VS. Specifically, the VSTSS could improve the average ERD values in the motor cortex during the task segment by 34.70% and 14.28% than the NVS and VS in the alpha rhythm for poor performers, respectively. Additionally, the VSTSS could significantly enhance the classification accuracy between the MI and Rest tasks by 12.52% and 4.05% compared to NVS and VS for poor performers, respectively.

CONCLUSION: The proposed paradigm could enhance motor cortical activation during MI and classification performance by providing vivid MI guidance for subjects, offering a crucial promise for practical applications of lower-limb MI-BCI. .},
}

@article {pmid40203854,
year = {2025},
author = {Collinger, J and Vansteensel, MJ and Mrachacz-Kersting, N and Mattia, D and Valeriani, D and Vaughan, TM},
title = {Special Issue on Brain-Computer Interfaces: Highlighting Research from the 10th International Brain-Computer Interface Meeting.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/adcaed},
pmid = {40203854},
issn = {1741-2552},
abstract = {N/A.},
}

@article {pmid40199879,
year = {2025},
author = {Zhao, Y and Wu, JT and Feng, JB and Cai, XY and Wang, XT and Wang, L and Xie, W and Gu, Y and Liu, J and Chen, W and Zhou, L and Shen, Y},
title = {Dual and plasticity-dependent regulation of cerebello-zona incerta circuits on anxiety-like behaviors.},
journal = {Nature communications},
volume = {16},
number = {1},
pages = {3339},
pmid = {40199879},
issn = {2041-1723},
support = {2021ZD0204000//Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology)/ ; 2023YFE0206800//Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology)/ ; 2021ZD0204000//Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology)/ ; 81625006//National Natural Science Foundation of China (National Science Foundation of China)/ ; 31820103005//National Natural Science Foundation of China (National Science Foundation of China)/ ; 32200620//National Natural Science Foundation of China (National Science Foundation of China)/ ; 32225021//National Natural Science Foundation of China (National Science Foundation of China)/ ; 32170976//National Natural Science Foundation of China (National Science Foundation of China)/ ; LY21C090003//Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation)/ ; },
mesh = {Animals ; *Anxiety/physiopathology/metabolism ; Male ; *Neuronal Plasticity/physiology ; Mice ; *Zona Incerta/physiology/physiopathology ; *Cerebellum/physiology ; Mice, Inbred C57BL ; *Cerebellar Nuclei/physiology ; Neurons/physiology/metabolism ; Behavior, Animal/physiology ; Glutamic Acid/metabolism ; Neural Pathways ; Synaptic Transmission/physiology ; },
abstract = {Clinical observation has identified cerebellar cognitive affective syndrome, which is characterized by various non-motor dysfunctions such as social disorders and anxiety. Increasing evidence has revealed reciprocal mono-/poly-synaptic connections of cerebello-cerebral circuits, forming the concept of the cerebellar connectome. In this study, we demonstrate that neurons in the cerebellar nuclei (CN) of male mice project to a subset of zona incerta (ZI) neurons through long-range glutamatergic and GABAergic transmissions, both capable of encoding acute stress. Furthermore, activating or inhibiting glutamatergic and GABAergic transmissions in the CN → ZI pathway can positively or negatively regulate anxiety and place preference through presynaptic plasticity-dependent mechanisms, as well as mediate motor-induced alleviation of anxiety. Our data support the close relationship between the cerebellum and emotional processes and suggest that targeting cerebellar outputs may be an effective approach for treating anxiety.},
}

Animals
*Anxiety/physiopathology/metabolism
Male
*Neuronal Plasticity/physiology
Mice
*Zona Incerta/physiology/physiopathology
*Cerebellum/physiology
Mice, Inbred C57BL
*Cerebellar Nuclei/physiology
Neurons/physiology/metabolism
Behavior, Animal/physiology
Glutamic Acid/metabolism
Neural Pathways
Synaptic Transmission/physiology

@article {pmid40199863,
year = {2025},
author = {Guttmann-Flury, E and Sheng, X and Zhu, X},
title = {Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms.},
journal = {Scientific data},
volume = {12},
number = {1},
pages = {587},
pmid = {40199863},
issn = {2052-4463},
support = {91948302//National Natural Science Foundation of China (National Science Foundation of China)/ ; 91948302//National Natural Science Foundation of China (National Science Foundation of China)/ ; 91948302//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {Humans ; *Electroencephalography ; *Brain-Computer Interfaces ; *Eye-Tracking Technology ; *Eye Movements ; Blinking ; Video Recording ; },
abstract = {In Brain-Computer Interface (BCI) research, the detailed study of blinks is crucial. They can be considered as noise, affecting the efficiency and accuracy of decoding users' cognitive states and intentions, or as potential features, providing valuable insights into users' behavior and interaction patterns. We introduce a large dataset capturing electroencephalogram (EEG) signals, eye-tracking, high-speed camera recordings, as well as subjects' mental states and characteristics, to provide a multifactor analysis of eye-related movements. Four paradigms - motor imagery, motor execution, steady-state visually evoked potentials, and P300 spellers - are selected due to their capacity to evoke various sensory-motor responses and potential influence on ocular activity. This online-available dataset contains over 46 hours of data from 31 subjects across 63 sessions, totaling 2520 trials for each of the first three paradigms, and 5670 for P300. This multimodal and multi-paradigms dataset is expected to allow the development of algorithms capable of efficiently handling eye-induced artifacts and enhancing task-specific classification. Furthermore, it offers the opportunity to evaluate the cross-paradigm robustness involving the same participants.},
}

Humans
*Electroencephalography
*Brain-Computer Interfaces
*Eye-Tracking Technology
*Eye Movements
Blinking
Video Recording

@article {pmid40198632,
year = {2025},
author = {Ueda, M and Ueno, K and Inoue, T and Sakiyama, M and Shiroma, C and Ishii, R and Naito, Y},
title = {Detection of motor-related mu rhythm desynchronization by ear EEG.},
journal = {PloS one},
volume = {20},
number = {4},
pages = {e0321107},
doi = {10.1371/journal.pone.0321107},
pmid = {40198632},
issn = {1932-6203},
mesh = {Humans ; Male ; *Electroencephalography/methods/instrumentation ; Female ; Adult ; Young Adult ; Hand/physiology ; Movement/physiology ; *Ear/physiology ; Brain-Computer Interfaces ; },
abstract = {Event-related desynchronization (ERD) of the mu rhythm (8-13 Hz) is an important indicator of motor execution, neurofeedback, and brain-computer interface in EEG. This study investigated the feasibility of an ear electroencephalography (EEG) device monitoring mu-ERD during hand grasp and release movements. The EEG data of the right hand movement and the eye opened resting condition were measured with an ear EEG device. We calculated and compared mu rhythm power and time-frequency data from 20 healthy participants during right hand movement and eye opened resting. Our results showed a significant difference of mean mu rhythm power between the eye opened rest condition and the right hand movement condition and significant suppression in the 9-12.5 Hz frequency band in the time-frequency data. These results support the utility of ear EEG in detecting motor activity-related mu-ERD. Ear EEG could be instrumental in refining rehabilitation strategies by providing in-situ assessment of motor function and tailored feedback.},
}

Humans
Male
*Electroencephalography/methods/instrumentation
Female
Adult
Young Adult
Hand/physiology
Movement/physiology
*Ear/physiology
Brain-Computer Interfaces

@article {pmid40198304,
year = {2025},
author = {Wang, Z and Li, A and Wang, Z and Zhou, T and Xu, T and Hu, H},
title = {BSAN: A Self-Adapted Motor Imagery Decoding Framework Based on Contextual Information.},
journal = {IEEE journal of biomedical and health informatics},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/JBHI.2025.3557499},
pmid = {40198304},
issn = {2168-2208},
abstract = {In motor imagery (MI) decoding, it still remains challenging to excavate enough contextual information of MI in different brain regions and to bridge the cross-session variance in feature distributions. In light of these issues, our study presents an innovative Bi-Stream Adaptation Network (BSAN) to bolster network efficacy, aiming to improve MI-based brain-computer interface (BCI) robustness across sessions. Our framework consists of the Bi-attention module, feature extractor, classifier, and Bi-discriminator. Precisely, we devise the Bi-attention module to reveal granular context information of MI with performing multi-scale convolutions asymptotically. Then, after features extraction, Bi-discriminator is involved to align the features from different MI sessions such that a uniform and accurate representation of neural patterns is achieved. By such a workflow, the proposed BSAN allows for the effective fusion of context coherence and session-invariance within the network architecture, therefore diminishing the reliance of redundant MI trials for MI-BCI re-calibration. To empirically substantiate BSAN, comprehensive experiments are conducted based on two public MI datasets. With average accuracies of 78.97% and 83.79% on two public datasets, and an inference time of 2.99 ms on CPU-only devices, it is believed that our approach has the potential to accelerate the practical deployment of MI-BCI.},
}

@article {pmid40197656,
year = {2025},
author = {Won, C and Cho, S and Jang, KI and Park, JU and Cho, JH and Lee, T},
title = {Emerging fiber-based neural interfaces with conductive composites.},
journal = {Materials horizons},
volume = {},
number = {},
pages = {},
doi = {10.1039/d4mh01854k},
pmid = {40197656},
issn = {2051-6355},
abstract = {Neural interfaces that enable bidirectional communication between neural systems and external devices are crucial for treating neurological disorders and advancing brain-machine interfaces. Key requirements for these neural interfaces are the ability to modulate electrophysiological activity without causing tissue damage in the nerve system and long-term usability. Recent advances in biomedical neural electrodes aim to reduce mechanical mismatch between devices and surrounding tissues/organs while maintaining their electrical conductivity. Among these, fiber electrodes stand out as essential candidates for future neural interfaces owing to their remarkable flexibility, controllable scalability, and facile integration with systems. Herein, we introduce fiber-based devices with conductive composites, along with their fabrication technologies, and integration strategies for future neural interfaces. Compared to conventional neural electrodes, fiber electrodes readily combine with conductive materials such as metal nanoparticles, carbon-based nanomaterials, and conductive polymers. Their fabrication technologies enable high electrical performance without sacrificing mechanical properties. In addition, the neural modulation techniques of fiber electrodes; electrical, optical, and chemical, and their applications in central and peripheral nervous systems are carefully discussed. Finally, current limitations and potential advancements in fiber-based neural interfaces are highlighted for future innovations.},
}

@article {pmid40196469,
year = {2025},
author = {Tor, A and Clarke, SE and Bray, IE and Nuyujukian, P and , },
title = {Material Damage to Multielectrode Arrays after Electrolytic Lesioning is in the Noise.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
doi = {10.1101/2025.03.26.645429},
pmid = {40196469},
issn = {2692-8205},
abstract = {1The quality of stable long-term recordings from chronically implanted electrode arrays is essential for experimental neuroscience and brain-computer interfaces. This work uses scanning electron microscopy (SEM) to image and analyze eight 96-channel Utah arrays previously implanted in motor cortical regions of four subjects (subject H = 2242 days implanted, F = 1875, U = 2680, C = 594), providing important contributions to a growing body of long-term implant research leveraging this imaging technology. Four of these arrays have been used in electrolytic lesioning experiments (H = 10 lesions, F = 1, U = 4, C = 1), a novel electrolytic perturbation technique using small direct currents. In addition to surveying physical damage, such as biological debris and material deterioration, this work also analyzes whether electrolytic lesioning created damage beyond what is typical for these arrays. Each electrode was scored in six damage categories, identified from the literature: abnormal debris, metal coating cracks, silicon tip breakage, parylene C delamination, parylene C cracks, and shank fracture. This analysis confirms previous results that observed damage on explanted arrays is more severe on the outer-edge electrodes versus inner electrodes. These findings also indicate that are no statistically significant differences between the damage observed on normal electrodes versus electrodes used for electrolytic lesioning. This work provides evidence that electrolytic lesioning does not significantly affect the quality of chronically implanted electrode arrays and can be a useful tool in understanding perturbations to neural systems. Finally, this work also includes the largest collection of single-electrode SEM images for previously implanted multielectrode Utah arrays, spanning eleven different intact arrays and one broken array. As the clinical relevance of chronically implanted electrodes with single-neuron resolution continues to grow, these images may be used to provide the foundation for a larger public database and inform further electrode design and analyses.},
}

@article {pmid40196347,
year = {2025},
author = {Yu, H and Mu, Q and Wang, Z and Guo, Y and Zhao, J and Wang, G and Wang, Q and Meng, X and Dong, X and Wang, S and Sun, J},
title = {A study on early diagnosis for fracture non-union prediction using deep learning and bone morphometric parameters.},
journal = {Frontiers in medicine},
volume = {12},
number = {},
pages = {1547588},
pmid = {40196347},
issn = {2296-858X},
abstract = {BACKGROUND: Early diagnosis of non-union fractures is vital for treatment planning, yet studies using bone morphometric parameters for this purpose are scarce. This study aims to create a fracture micro-CT image dataset, design a deep learning algorithm for fracture segmentation, and develop an early diagnosis model for fracture non-union.

METHODS: Using fracture animal models, micro-CT images from 12 rats at various healing stages (days 1, 7, 14, 21, 28, and 35) were analyzed. Fracture lesion frames were annotated to create a high-resolution dataset. We proposed the Vision Mamba Triplet Attention and Edge Feature Decoupling Module UNet (VM-TE-UNet) for fracture area segmentation. And we extracted bone morphometric parameters to establish an early diagnostic evaluation system for the non-union of fractures.

RESULTS: A dataset comprising 2,448 micro-CT images of the rat fracture lesions with fracture Region of Interest (ROI), bone callus and healing characteristics was established and used to train and test the proposed VM-TE-UNet which achieved a Dice Similarity Coefficient of 0.809, an improvement over the baseline's 0.765, and reduced the 95th Hausdorff Distance to 13.1. Through ablation studies, comparative experiments, and result analysis, the algorithm's effectiveness and superiority were validated. Significant differences (p < 0.05) were observed between the fracture and fracture non-union groups during the inflammatory and repair phases. Key indices, such as the average CT values of hematoma and cartilage tissues, BS/TS and BS/TV of mineralized cartilage, BS/TV of osteogenic tissue, and BV/TV of osteogenic tissue, align with clinical methods for diagnosing fracture non-union by assessing callus presence and local soft tissue swelling. On day 14, the early diagnosis model achieved an AUC of 0.995, demonstrating its ability to diagnose fracture non-union during the soft-callus phase.

CONCLUSION: This study proposed the VM-TE-UNet for fracture areas segmentation, extracted micro-CT indices, and established an early diagnostic model for fracture non-union. We believe that the prediction model can effectively screen out samples of poor fracture rehabilitation caused by blood supply limitations in rats 14 days after fracture, rather than the widely accepted 35 or 40 days. This provides important reference for the clinical prediction of fracture non-union and early intervention treatment.},
}

@article {pmid40196232,
year = {2025},
author = {Yang, Y and Zhao, H and Hao, Z and Shi, C and Zhou, L and Yao, X},
title = {Recognition of brain activities via graph-based long short-term memory-convolutional neural network.},
journal = {Frontiers in neuroscience},
volume = {19},
number = {},
pages = {1546559},
pmid = {40196232},
issn = {1662-4548},
abstract = {INTRODUCTION: Human brain activities are always difficult to recognize due to its diversity and susceptibility to disturbance. With its unique capability of measuring brain activities, magnetoencephalography (MEG), as a high temporal and spatial resolution neuroimaging technique, has been used to identify multi-task brain activities. Accurately and robustly classifying motor imagery (MI) and cognitive imagery (CI) from MEG signals is a significant challenge in the field of brain-computer interface (BCI).

METHODS: In this study, a graph-based long short-term memory-convolutional neural network (GLCNet) is proposed to classify the brain activities in MI and CI tasks. It was characterized by implementing three modules of graph convolutional network (GCN), spatial convolution and long short-term memory (LSTM) to effectively extract time-frequency-spatial features simultaneously. For performance evaluation, our method was compared with six benchmark algorithms of FBCSP, FBCNet, EEGNet, DeepConvNets, Shallow ConvNet and MEGNet on two public datasets of MEG-BCI and BCI competition IV dataset 3.

RESULTS: The results demonstrated that the proposed GLCNet outperformed other models with the average accuracies of 78.65% and 65.8% for two classification and four classification on the MEG-BCI dataset, respectively.

DISCUSSION: It was concluded that the GLCNet enhanced the model's adaptability in handling individual variability with robust performance. This would contribute to the exploration of brain activates in neuroscience.},
}

@article {pmid40195935,
year = {2025},
author = {Hasegawa, R and Poulin, R},
title = {Cause or consequence? Exploring authors' interpretations of correlations between fish body condition and parasite infection.},
journal = {Journal of fish biology},
volume = {},
number = {},
pages = {},
doi = {10.1111/jfb.70048},
pmid = {40195935},
issn = {1095-8649},
support = {202460294//Japan Society for the Promotion of Science/ ; JP22KJ0086//Japan Society for the Promotion of Science/ ; },
abstract = {We reviewed 194 publications that reported relationships between fish body condition indices (BCIs) and parasite infections, and examined the authors' intention behind this cross-sectional analysis, that is, whether authors interpreted the negative correlations as the negative effects of parasites or as fish with poor BCIs being more susceptible to infections. While 89% of studies only considered parasite infections as causes of poor BCI, studies acknowledging the opposite or bidirectional causal links were rare. We recommend considering both possibilities in any given fish host and parasite association.},
}

@article {pmid40195900,
year = {2025},
author = {Shin, H and Kim, K and Lee, J and Nam, J and Baeg, E and You, C and Choi, H and Kim, M and Chung, CK and Kim, JG and Ahn, JH and Han, M and Kim, J and Yang, S and Lee, SQ and Yang, S},
title = {A Wireless Cortical Surface Implant for Diagnosing and Alleviating Parkinson's Disease Symptoms in Freely Moving Animals.},
journal = {Advanced healthcare materials},
volume = {},
number = {},
pages = {e2405179},
doi = {10.1002/adhm.202405179},
pmid = {40195900},
issn = {2192-2659},
support = {//High Risk, High Return Research Program/ ; //ETRI grant (23YB1210, Collective Behavioral Modelling in Socially Interacting Group)/ ; },
abstract = {Parkinson's disease (PD), one of the most common neurodegenerative diseases, is involved in motor abnormality, primarily arising from the degeneration of dopaminergic neurons. Previous studies have examined the electrotherapeutic effects of PD using various methodological contexts, including live conditions, wireless control, diagnostic/therapeutic aspects, removable interfaces, or biocompatible materials, each of which is separately utilized for testing the diagnosis or alleviation of various brain diseases. Here, a cortical surface implant designed to improve motor function in freely moving PD animals is presented. This implant, a minimally invasive system equipped with a graphene electrode array, is the first integrated system to exhibit biocompatibility, wearability, removability, target specificity, and wireless control. The implant positioned at the motor cortical surface activates the motor cortex to maximize therapeutic effects and minimize off-target effects while monitoring motor activities. In PD animals, cortical motor surface stimulation restores motor function and brain waves, which corresponds to potentiated synaptic responses. Furthermore, these changes are associated with the upregulation of metabotropic glutamate receptor 5 (mGluR5, Grm5) and D5 dopamine receptor (D5R, Drd5) genes in the glutamatergic synapse. The newly designed wireless neural implant demonstrates capabilities in both real-time diagnostics and targeted therapeutics, suggesting its potential as a wireless system for biomedical devices for patients with PD and other neurodegenerative diseases.},
}

@article {pmid40195429,
year = {2025},
author = {Ming, Z and Yu, W and Fan, J and Ling, G and Fengming, C and Wei, T},
title = {Efficacy of kinesthetic motor imagery based brain computer interface combined with tDCS on upper limb function in subacute stroke.},
journal = {Scientific reports},
volume = {15},
number = {1},
pages = {11829},
pmid = {40195429},
issn = {2045-2322},
support = {XWRCHT20220045//the Xuzhou Key Medical Talents Project/ ; No.52375224//National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Transcranial Direct Current Stimulation/methods ; Male ; Female ; *Upper Extremity/physiopathology ; *Brain-Computer Interfaces ; Middle Aged ; *Stroke Rehabilitation/methods ; *Stroke/physiopathology/therapy ; Aged ; Electroencephalography ; *Kinesthesis/physiology ; Treatment Outcome ; Adult ; },
abstract = {This study investigates whether the combined effect of kinesthetic motor imagery-based brain computer interface (KI-BCI) and transcranial direct current stimulation (tDCS) on upper limb function in subacute stroke patients is more effective than using KI-BCI or tDCS alone. Forty-eight subacute stroke survivors were randomized to the KI-BCI, tDCS, or BCI-tDCS group. The KI-BCI group performed 30 min of KI-BCI training. Patients in tDCS group received 30 min of tDCS. Patients in BCI-tDCS group received 15 min of tDCS and 15 min of KI-BCI. The treatment cycle was five times a week, for four weeks. After all intervention, the Fugl-Meyer Assessment-Upper Extremity, Motor Status Scale, and the Modified Barthel Index scores of the KI-BCI group were superior to those of the tDCS group. The BCI-tDCS group was superior to the tDCS group in terms of the Motor Status Scale. Although quantitative EEG showed no significant group differences, the quantitative EEG indices in the tDCS group were significantly lower than before treatment. In conclusion, after treatment, although all intervention strategies improved upper limb motor function and daily living abilities in subacute stroke patients, KI-BCI demonstrated significantly better efficacy than tDCS. Under the same total treatment duration, the combined use of tDCS and KI-BCI did not achieve the hypothesized optimal outcome. Notably, tDCS reduced QEEG indices, possibly indicating favorable future outcomes in future.Trial registry number: ChiCTR2000034730.},
}

Humans
*Transcranial Direct Current Stimulation/methods
Male
Female
*Upper Extremity/physiopathology
*Brain-Computer Interfaces
Middle Aged
*Stroke Rehabilitation/methods
*Stroke/physiopathology/therapy
Aged
Electroencephalography
*Kinesthesis/physiology
Treatment Outcome
Adult

@article {pmid40194524,
year = {2025},
author = {Johnson, TR and Haddix, CA and Ajiboye, AB and Taylor, DM},
title = {Simplified control of neuromuscular stimulation systems for restoration of reach with limb stiffness as a modifiable degree of freedom.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/adc9e3},
pmid = {40194524},
issn = {1741-2552},
abstract = {Brain-controlled functional electrical stimulation (FES) of the upper limb has been used to restore arm function to paralyzed individuals in the lab. Able-bodied individuals naturally modulate limb stiffness throughout movements and in anticipation of perturbations. Our goal is to develop, via simulation, a framework for incorporating stiffness modulation into the currently-used 'lookup-table-based' FES control systems while addressing several practical issues: 1) optimizing stimulation across muscles with overlap in function, 2) coordinating stimulation across joints, and 3) minimizing errors due to fatigue. Our calibration process also needs to account for when current spread causes additional muscles to become activated. Approach: We developed an analytical framework for building a lookup-table-based FES controller and simulated the clinical process of calibrating and using the arm. A computational biomechanical model of a human paralyzed arm responding to stimulation was used for simulations with six muscles controlling the shoulder and elbow in the horizontal plane. Both joints had multiple muscles with overlapping functional effects, as well as biarticular muscles to reflect complex interactions between joints. Performance metrics were collected in silico, and real-time use was demonstrated with a Rhesus macaque using its cortical signals to control the computational arm model in real time. Main Results: By explicitly including stiffness as a definable degree of freedom in the lookup table, our analytical approach was able to achieve all our performance criteria. While using more empirical data during controller parameterization produced more accurate lookup tables, interpolation between sparsely sampled points (e.g., 20 degree angular intervals) still produced good results with median endpoint position errors of less than 1 cm-a range that should be easy to correct for with real-time visual feedback. Significance: Our simplified process for generating an effective FES controller now makes translating upper limb FES systems into mainstream clinical practice closer to reality. .},
}

@article {pmid40193612,
year = {2025},
author = {Kim, H and Kim, JH and Lee, YJ and Lee, J and Han, H and Yi, H and Kim, H and Kim, H and Kang, TW and Chung, S and Ban, S and Lee, B and Lee, H and Im, CH and Cho, SJ and Sohn, JW and Yu, KJ and Kang, TJ and Yeo, WH},
title = {Motion artifact-controlled micro-brain sensors between hair follicles for persistent augmented reality brain-computer interfaces.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {122},
number = {15},
pages = {e2419304122},
doi = {10.1073/pnas.2419304122},
pmid = {40193612},
issn = {1091-6490},
support = {ECCS-2025462//NSF (NSF)/ ; P0017303//Korea Institute for Advancement of Technology (KIAT)/ ; },
mesh = {*Brain-Computer Interfaces ; Humans ; *Hair Follicle/physiology ; Electroencephalography/methods/instrumentation ; *Augmented Reality ; Artifacts ; *Brain/physiology ; Motion ; Algorithms ; Electrodes ; Evoked Potentials, Visual/physiology ; },
abstract = {Modern brain-computer interfaces (BCI), utilizing electroencephalograms for bidirectional human-machine communication, face significant limitations from movement-vulnerable rigid sensors, inconsistent skin-electrode impedance, and bulky electronics, diminishing the system's continuous use and portability. Here, we introduce motion artifact-controlled micro-brain sensors between hair strands, enabling ultralow impedance density on skin contact for long-term usable, persistent BCI with augmented reality (AR). An array of low-profile microstructured electrodes with a highly conductive polymer is seamlessly inserted into the space between hair follicles, offering high-fidelity neural signal capture for up to 12 h while maintaining the lowest contact impedance density (0.03 kΩ·cm[-2]) among reported articles. Implemented wireless BCI, detecting steady-state visually evoked potentials, offers 96.4% accuracy in signal classification with a train-free algorithm even during the subject's excessive motions, including standing, walking, and running. A demonstration captures this system's capability, showing AR-based video calling with hands-free controls using brain signals, transforming digital communication. Collectively, this research highlights the pivotal role of integrated sensors and flexible electronics technology in advancing BCI's applications for interactive digital environments.},
}

*Brain-Computer Interfaces
Humans
*Hair Follicle/physiology
Electroencephalography/methods/instrumentation
*Augmented Reality
Artifacts
*Brain/physiology
Motion
Algorithms
Electrodes
Evoked Potentials, Visual/physiology

@article {pmid40193313,
year = {2025},
author = {Estivalet, KM and Pettenuzzo, TSA and Mazzilli, NL and Ferreira, LF and Cechetti, F},
title = {The use of brain-machine interface, motor imagery, and action observation in the rehabilitation of individuals with Parkinson's disease: A protocol study for a randomized clinical trial.},
journal = {PloS one},
volume = {20},
number = {4},
pages = {e0315148},
pmid = {40193313},
issn = {1932-6203},
mesh = {Humans ; *Parkinson Disease/rehabilitation/physiopathology ; *Brain-Computer Interfaces ; Male ; Female ; *Imagery, Psychotherapy/methods ; Single-Blind Method ; Middle Aged ; Aged ; Upper Extremity/physiopathology ; Cognition ; },
abstract = {BACKGROUND: Parkinson's disease (PD) is a neurodegenerative condition that impacts motor planning and control of the upper limbs (UL) and leads to cognitive impairments. Rehabilitation approaches, including motor imagery (MI) and action observation (AO), along with the use of brain-machine interfaces (BMI), are essential in the PD population to enhance neuroplasticity and mitigate symptoms.

OBJECTIVE: To provide a description of a rehabilitation protocol for evaluating the effects of isolated and combined applications of MI and action observation (AO), along with BMI, on upper limb (UL) motor changes and cognitive function in PD.

METHODS: This study provides a detailed protocol for a single-blinded, randomized clinical trial. After selection, participants will be randomly assigned to one of five experimental groups. Each participant will be assessed at three points: pre-intervention, post-intervention, and at a follow-up four weeks after the intervention ends. The intervention consists of 10 sessions, each lasting approximately 60 minutes.

EXPECTED RESULTS: The primary outcome expected is an improvement in the Test d'Évaluation des Membres Supérieurs de Personnes Âgées score, accompanied by a reduction in task execution time. Secondary outcomes include motor symptoms in the upper limbs, assessed via the Unified Parkinson's Disease Rating Scale - Part III and the 9-Hole Peg Test; cognitive function, assessed with the PD Cognitive Rating Scale; and occupational performance, assessed with the Canadian Occupational Performance Measure.

DISCUSSION: This study protocol is notable for its intensive daily sessions. Both MI and AO are low-cost, enabling personalized interventions that physiotherapists and occupational therapists can readily replicate in practice. While BMI use does require professionals to acquire an exoskeleton, the protocol ensures the distinctiveness of the interventions and, to our knowledge, is the first to involve individuals with PD.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05696925.},
}

Humans
*Parkinson Disease/rehabilitation/physiopathology
*Brain-Computer Interfaces
Male
Female
*Imagery, Psychotherapy/methods
Single-Blind Method
Middle Aged
Aged
Upper Extremity/physiopathology
Cognition

@article {pmid40191683,
year = {2025},
author = {Miri, M and Abootalebi, V and Saeedi-Sourck, H and Van De Ville, D and Behjat, H},
title = {Graphs Constructed from Instantaneous Amplitude and Phase of Electroencephalogram Successfully Differentiate Motor Imagery Tasks.},
journal = {Journal of medical signals and sensors},
volume = {15},
number = {},
pages = {7},
pmid = {40191683},
issn = {2228-7477},
abstract = {BACKGROUND: Accurate classification of electroencephalogram (EEG) signals is challenging given the nonlinear and nonstationary nature of the data as well as subject-dependent variations. Graph signal processing (GSP) has shown promising results in the analysis of brain imaging data.

METHODS: In this article, a GSP-based approach is presented that exploits instantaneous amplitude and phase coupling between EEG time series to decode motor imagery (MI) tasks. A graph spectral representation of the Hilbert-transformed EEG signals is obtained, in which simultaneous diagonalization of covariance matrices provides the basis of a subspace that differentiates two classes of right hand and right foot MI tasks. To determine the most discriminative subspace, an exploratory analysis was conducted in the spectral domain of the graphs by ranking the graph frequency components using a feature selection method. The selected features are fed into a binary support vector machine that predicts the label of the test trials.

RESULTS: The performance of the proposed approach was evaluated on brain-computer interface competition III (IVa) dataset.

CONCLUSIONS: Experimental results reflect that brain functional connectivity graphs derived using the instantaneous amplitude and phase of the EEG signals show comparable performance with the best results reported on these data in the literature, indicating the efficiency of the proposed method compared to the state-of-the-art methods.},
}

@article {pmid40164740,
year = {2025},
author = {Littlejohn, KT and Cho, CJ and Liu, JR and Silva, AB and Yu, B and Anderson, VR and Kurtz-Miott, CM and Brosler, S and Kashyap, AP and Hallinan, IP and Shah, A and Tu-Chan, A and Ganguly, K and Moses, DA and Chang, EF and Anumanchipalli, GK},
title = {A streaming brain-to-voice neuroprosthesis to restore naturalistic communication.},
journal = {Nature neuroscience},
volume = {28},
number = {4},
pages = {902-912},
pmid = {40164740},
issn = {1546-1726},
support = {5U01DC018671//U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)/ ; F30DC021872//U.S. Department of Health & Human Services | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)/ ; },
mesh = {Humans ; *Brain-Computer Interfaces ; Male ; *Speech/physiology ; *Voice/physiology ; Adult ; Female ; Communication Devices for People with Disabilities ; *Sensorimotor Cortex/physiology ; Communication ; Paralysis/physiopathology/rehabilitation ; },
abstract = {Natural spoken communication happens instantaneously. Speech delays longer than a few seconds can disrupt the natural flow of conversation. This makes it difficult for individuals with paralysis to participate in meaningful dialogue, potentially leading to feelings of isolation and frustration. Here we used high-density surface recordings of the speech sensorimotor cortex in a clinical trial participant with severe paralysis and anarthria to drive a continuously streaming naturalistic speech synthesizer. We designed and used deep learning recurrent neural network transducer models to achieve online large-vocabulary intelligible fluent speech synthesis personalized to the participant's preinjury voice with neural decoding in 80-ms increments. Offline, the models demonstrated implicit speech detection capabilities and could continuously decode speech indefinitely, enabling uninterrupted use of the decoder and further increasing speed. Our framework also successfully generalized to other silent-speech interfaces, including single-unit recordings and electromyography. Our findings introduce a speech-neuroprosthetic paradigm to restore naturalistic spoken communication to people with paralysis.},
}

Humans
*Brain-Computer Interfaces
Male
*Speech/physiology
*Voice/physiology
Adult
Female
Communication Devices for People with Disabilities
*Sensorimotor Cortex/physiology
Communication
Paralysis/physiopathology/rehabilitation

@article {pmid39935067,
year = {2025},
author = {Yao, Y and Ahnood, A and Chambers, A and Tong, W and Prawer, S},
title = {Nitrogen-Doped Ultrananocrystalline Diamond - Optoelectronic Biointerface for Wireless Neuronal Stimulation.},
journal = {Advanced healthcare materials},
volume = {14},
number = {9},
pages = {e2403901},
pmid = {39935067},
issn = {2192-2659},
support = {2029454//National Health and Medical Research Council/ ; DE220100302//Australian Research Council/ ; DE210102750//Australian Research Council/ ; },
mesh = {Animals ; *Diamond/chemistry ; *Nitrogen/chemistry ; Rats ; *Neurons/physiology ; Retina ; *Wireless Technology ; Semiconductors ; Light ; },
abstract = {This study presents a semiconducting optoelectronic system for light-controlled non-genetic neuronal stimulation using visible light. The system architecture is entirely wireless, comprising a thin film of nitrogen-doped ultrananocrystalline diamond directly grown on a semiconducting silicon substrate. When immersed in a physiological medium and subjected to pulsed illumination in the visible (595 nm) or near-infrared wavelength (808 nm) range, charge accumulation at the device-medium interface induces a transient ionic displacement current capable of electrically stimulating neurons with high temporal resolution. With a measured photoresponsivity of 7.5 mA W[-1], the efficacy of this biointerface is demonstrated through optoelectronic stimulation of degenerate rat retinas using 595 nm irradiation, pulse durations of 50-500 ms, and irradiance levels of 1.1-4.3 mW mm[-2], all below the safe ocular threshold. This work presents the pioneering utilization of a diamond-based optoelectronic platform, capable of generating sufficiently large photocurrents for neuronal stimulation in the retina.},
}

Animals
*Diamond/chemistry
*Nitrogen/chemistry
Rats
*Neurons/physiology
Retina
*Wireless Technology
Semiconductors
Light

@article {pmid40189874,
year = {2025},
author = {Li, X and Zhang, J and Shi, B and Li, Y and Wang, Y and Shuai, K and Li, Y and Ming, G and Song, T and Pei, W and Sun, B},
title = {Freestanding Transparent Organic-Inorganic Mesh E-Tattoo for Breathable Bioelectrical Membranes with Enhanced Capillary-Driven Adhesion.},
journal = {ACS applied materials & interfaces},
volume = {},
number = {},
pages = {},
doi = {10.1021/acsami.5c00565},
pmid = {40189874},
issn = {1944-8252},
abstract = {The electronic tattoo (e-tattoo), a cutting-edge wearable sensor technology adhered to human skin, has garnered significant attention for its potential in brain-computer interfaces (BCIs) and routine health monitoring. Conventionally, flexible substrates with adhesion force on dewy surfaces pursue seamless contact with skin, employing compact airtight substrates, hindering air circulation between skin and the surrounding environment, and compromising long-term wearing comfort. To address these challenges, we have developed a freestanding transparent e-tattoo featuring flexible serpentine mesh bridges with a unique full-breathable multilayer structure. The mesh e-tattoo demonstrates remarkable ductility and air permeability while maintaining robust electronic properties, even after significant mechanical deformation. Furthermore, it exhibits an impressive visible-light transmittance of up to 95%, coupled with a low sheet resistance of 0.268 Ω sq[-1], ensuring both optical clarity and electrical efficiency. By increasing the number of menisci between the mesh e-tattoo and the skin, the total adhesion force increases due to the cumulative capillary-driven effect. We also successfully demonstrated high-quality bioelectric signal collections. In particular, the controlling virtual reality (VR) objects using electrooculogram (EOG) signals collected by mesh e-tattoos were achieved to demonstrate their potential for human-computer interactions (HCIs). This freestanding transparent e-tattoo with a fully breathable mesh structure represents a significant advancement in flexible electrodes for bioelectrical signal monitoring applications.},
}

@article {pmid40189123,
year = {2025},
author = {Wang, F and Ren, J and Cai, Q and Liang, R and Wang, L and Yang, Q and Tian, Y and Zheng, C and Yang, J and Ming, D},
title = {Theta-gamma phase-amplitude coupling as a promising neurophysiological biomarker for evaluating the efficacy of low-intensity focused ultrasound stimulation on vascular dementia treatment.},
journal = {Experimental neurology},
volume = {},
number = {},
pages = {115237},
doi = {10.1016/j.expneurol.2025.115237},
pmid = {40189123},
issn = {1090-2430},
abstract = {Low-intensity focused ultrasound stimulation (LIFUS) has garnered attention for its potential in vascular dementia (VD) treatment. However, the lack of sufficient data supporting its efficacy and elucidating its mechanisms of action limits its further clinical translation and application. Considerable researches support the idea that LIFUS can improve the disturbance of neural oscillation modes caused by a variety of neurological diseases. However, the effect of LIFUS on neural oscillation modes in VD remains unclear. Therefore, this study aims to investigate the therapeutic effects of LIFUS on neural oscillation modes in VD. To achieve this purpose, the VD model was established via the bilateral common carotid artery occlusion, followed by two weeks of LIFUS treatment targeting the bilateral hippocampus. The therapeutic effects of LIFUS were evaluated by behavioral tests and cerebral blood flow measurement. Electrophysiological signals were recorded from the hippocampal CA1 and CA3 and medial prefrontal cortex (mPFC). The results indicated LIFUS could effectively improve cognitive dysfunction in VD rats. The underlying electrophysiological mechanisms involved the restoration of phase-amplitude coupling (PAC) of theta-gamma oscillations within both the CA3-CA1 local circuit and the hippocampus-mPFC cross-brain circuit. Classification results based on PAC characteristics suggested that PAC metrics are effective for evaluating the efficacy of LIFUS in treating VD, with optimal recognition performance observed in the hippocampus-mPFC cross-brain circuit. Our findings provide neuroelectrophysiological insights into the mechanisms of LIFUS in VD treatment and propose a promising diagnostic biomarker for evaluating LIFUS efficacy in future applications.},
}

@article {pmid40187178,
year = {2025},
author = {S, P and M, S},
title = {Design of asynchronous low-complexity SSVEP-based brain control interface speller.},
journal = {Computers in biology and medicine},
volume = {190},
number = {},
pages = {110062},
doi = {10.1016/j.compbiomed.2025.110062},
pmid = {40187178},
issn = {1879-0534},
abstract = {BACKGROUND: Brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) provide a transformative solution, addressing communication challenges for individuals with speech impairments or neuromuscular disorders. The real-time wireless asynchronous BCI speller system utilizes electroencephalography (EEG) signals, tapping the brain's electrical activity for effective communication.

METHODS: Users interact with a screen featuring flickering stimuli, each representing cursor movement and character selection. The system includes cursor movements, displays selected characters, and produces an audio output of the complete word. Users generate real-time SSVEP responses captured wirelessly through an EEG acquisition system by directing attention to the stimulus. The single-channel EEG signal is wirelessly transmitted to a Raspberry Pi processing module through Wi-Fi. The EEG signals are decoded using modified power spectral density (PSD) analysis to identify the user's focus, maneuvering the cursor for character selection.

RESULTS: In experiments with ten subjects, the single-channel asynchronous low-complexity BCI speller system achieved 95.2% SSVEP identification accuracy with a detection time of 1.05 s for selecting each character/target and an information transfer rate (ITR) of 119.82 bits/min.

CONCLUSION: This underscores its efficacy in enabling individuals to spell words and communicate efficiently. The proposed real-time wireless BCI speller system is an effective tool for communication-challenged individuals, enhancing communication efficiency through brain signals.},
}

@article {pmid40183071,
year = {2025},
author = {Muthukrishnan, SP and Atyabi, A},
title = {Editorial: Neural mechanisms of motor planning in assisted voluntary movement.},
journal = {Frontiers in human neuroscience},
volume = {19},
number = {},
pages = {1582214},
pmid = {40183071},
issn = {1662-5161},
}

@article {pmid40182217,
year = {2025},
author = {Wirawan, IMA and Paramarta, K},
title = {Acquisition Of Balinese Imagined Spelling using Electroencephalogram (BISE) Dataset.},
journal = {Data in brief},
volume = {60},
number = {},
pages = {111454},
pmid = {40182217},
issn = {2352-3409},
abstract = {One of the main goals of today's technology is to create a connected environment between humans and technological devices to perform daily physical activities. However, users with speech disorders cannot use this application. Loss of verbal communication can be caused by injuries and neurodegenerative diseases that affect motor production, speech articulation, and language comprehension. To overcome this problem, Brain-Computer Interfaces (BCI) use EEG signals as assistive technology to provide a new communication channel for individuals who cannot communicate due to loss of motor control. Of the several BCI studies that use EEG signals, no studies have studied Balinese characters. As a first step, this study examines the acquisition of EEG signal data for Balinese character recognition. There are several stages in obtaining EEG signal data for Balinese character spelling imagination in this study: preparation of research documents, preparation of stimulus media, submission of ethical permits, determination of participants, recording process, data presentation, and publication of datasets. The result datasets from this study are in the form of raw data, and data was analyzed for 18 Balinese and 6 vowel characters, both spelling and imagined.},
}

@article {pmid40095842,
year = {2025},
author = {Tian, B and Zhang, S and Xue, D and Chen, S and Zhang, Y and Peng, K and Wang, D},
title = {Decoding Intrinsic Fluctuations of Engagement From EEG Signals During Fingertip Motor Tasks.},
journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
volume = {33},
number = {},
pages = {1271-1283},
doi = {10.1109/TNSRE.2025.3551819},
pmid = {40095842},
issn = {1558-0210},
mesh = {Humans ; *Electroencephalography/methods ; Male ; *Fingers/physiology ; Adult ; Female ; Young Adult ; Machine Learning ; Algorithms ; Virtual Reality ; Brain-Computer Interfaces ; Psychomotor Performance/physiology ; Reproducibility of Results ; Motor Skills/physiology ; Signal Processing, Computer-Assisted ; Movement/physiology ; },
abstract = {Maintaining a high mental engagement is critical for motor rehabilitation interventions. Achieving a flow experience, often conceptualized as a highly engaged mental state, is an ideal goal for motor rehabilitation tasks. This paper proposes a virtual reality-based fine fingertip motor task in which the difficulty is maintained to match individual abilities. The aim of this study is to decode the intrinsic fluctuations of flow experience from electroencephalogram (EEG) signals during the execution of a motor task, addressing a gap in flow research that overlooks these fluctuations. To resolve the conflict between sparse self-reported flow sampling and the high dimensionality of neural signals, we use motor behavioral measures to represent flow and label the EEG data, thereby increasing the number of samples. A machine learning-based neural decoder is then established to classify each trial into high-flow or low-flow using spectral power and coherence features extracted from the EEG signals. Cross-validation reveals that the classification accuracy of the neural decoder can exceed 80%. Notably, we highlight the contributions of high-frequency bands in EEG activities to flow decoding. Additionally, EEG feature analyses reveal significant increases in the power of parietal-occipital electrodes and global coherence values, specifically in the alpha and beta bands, during high-flow durations. This study validates the feasibility of decoding the intrinsic flow fluctuations during fine motor task execution with a high accuracy. The methodology and findings in this work lay a foundation for future applications in manipulating flow experience and enhancing engagement levels in motor rehabilitation practice.},
}

Humans
*Electroencephalography/methods
Male
*Fingers/physiology
Adult
Female
Young Adult
Machine Learning
Algorithms
Virtual Reality
Brain-Computer Interfaces
Psychomotor Performance/physiology
Reproducibility of Results
Motor Skills/physiology
Signal Processing, Computer-Assisted
Movement/physiology

@article {pmid40182177,
year = {2025},
author = {Paillard, J and Hipp, JF and Engemann, DA},
title = {GREEN: A lightweight architecture using learnable wavelets and Riemannian geometry for biomarker exploration with EEG signals.},
journal = {Patterns (New York, N.Y.)},
volume = {6},
number = {3},
pages = {101182},
pmid = {40182177},
issn = {2666-3899},
abstract = {Spectral analysis using wavelets is widely used for identifying biomarkers in EEG signals. Recently, Riemannian geometry has provided an effective mathematical framework for predicting biomedical outcomes from multichannel electroencephalography (EEG) recordings while showing concord with neuroscientific domain knowledge. However, these methods rely on handcrafted rules and sequential optimization. In contrast, deep learning (DL) offers end-to-end trainable models achieving state-of-the-art performance on various prediction tasks but lacks interpretability and interoperability with established neuroscience concepts. We introduce Gabor Riemann EEGNet (GREEN), a lightweight neural network that integrates wavelet transforms and Riemannian geometry for processing raw EEG data. Benchmarking on six prediction tasks across four datasets with over 5,000 participants, GREEN outperformed non-deep state-of-the-art models and performed favorably against large DL models while using orders-of-magnitude fewer parameters. Computational experiments showed that GREEN facilitates learning sparse representations without compromising performance. By integrating domain knowledge, GREEN combines a desirable complexity-performance trade-off with interpretable representations.},
}

@article {pmid40181137,
year = {2025},
author = {Wang, G and Wang, W and Wang, Z and Huang, S and Liu, Y and Ming, D},
title = {The sixth finger illusion induced by palm outside stroking shows stable ownership and independence.},
journal = {Scientific reports},
volume = {15},
number = {1},
pages = {11447},
pmid = {40181137},
issn = {2045-2322},
support = {2023YFC3603800//National Key Research and Development Program of China/ ; 2023YFC3603800//National Key Research and Development Program of China/ ; 2023YFC3603800//National Key Research and Development Program of China/ ; 2023YFC3603800//National Key Research and Development Program of China/ ; 2023YFC3603800//National Key Research and Development Program of China/ ; 2023YFC3603800//National Key Research and Development Program of China/ ; 62273251//National Natural Science Foundation of China/ ; 62273251//National Natural Science Foundation of China/ ; 62273251//National Natural Science Foundation of China/ ; 62273251//National Natural Science Foundation of China/ ; 62273251//National Natural Science Foundation of China/ ; 62273251//National Natural Science Foundation of China/ ; MSV202418//Research Project of State Key Laboratory of Mechanical System and Vibration/ ; MSV202418//Research Project of State Key Laboratory of Mechanical System and Vibration/ ; MSV202418//Research Project of State Key Laboratory of Mechanical System and Vibration/ ; MSV202418//Research Project of State Key Laboratory of Mechanical System and Vibration/ ; MSV202418//Research Project of State Key Laboratory of Mechanical System and Vibration/ ; MSV202418//Research Project of State Key Laboratory of Mechanical System and Vibration/ ; 21JCYBJC00520//Natural Science Foundation of Tianjin Municipality/ ; 21JCYBJC00520//Natural Science Foundation of Tianjin Municipality/ ; 21JCYBJC00520//Natural Science Foundation of Tianjin Municipality/ ; 21JCYBJC00520//Natural Science Foundation of Tianjin Municipality/ ; 21JCYBJC00520//Natural Science Foundation of Tianjin Municipality/ ; 21JCYBJC00520//Natural Science Foundation of Tianjin Municipality/ ; },
mesh = {Humans ; *Illusions/physiology ; Male ; Female ; *Fingers/physiology ; Adult ; Young Adult ; *Hand/physiology ; *Touch Perception/physiology ; },
abstract = {Recently, the sixth finger illusion has been widely studied for body representation. It remains unclear how the stroking area, visual effects and the number of trials affect the illusion. We recruited 80 participants to conduct five trials by stroking the palm outside or little finger outside in conditions with and without wearing supernumerary rubber finger. The results show the stroking area has a greater impact on the intensity and independence of the illusion. And the palm outside can induce a stronger and more independent illusion. In addition, the sixth finger illusion induced by these four conditions was significantly influenced by the number of trials, and there is a significant enhancement in the intensity of the illusion induced by the palm outside as the number of trials increases. These indicate that stroking the outer lateral side of the palm can induce a relatively stronger and more independent sixth finger illusion, and the intensity of it reaches a steady state after three trials when wearing a supernumerary rubber finger and five trials when not wearing a supernumerary rubber finger. This study adds evidence to the research on multisensory integration and sensory feedback of the supernumerary robotic fingers.},
}

Humans
*Illusions/physiology
Male
Female
*Fingers/physiology
Adult
Young Adult
*Hand/physiology
*Touch Perception/physiology

@article {pmid40181122,
year = {2025},
author = {Rawat, K and Sharma, T},
title = {An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion.},
journal = {Scientific reports},
volume = {15},
number = {1},
pages = {11379},
pmid = {40181122},
issn = {2045-2322},
mesh = {Humans ; Electroencephalography/methods ; Deep Learning ; *Nervous System Diseases/diagnosis/physiopathology ; Electrocardiography ; *Neural Networks, Computer ; *Mental Disorders/diagnosis/physiopathology ; Adult ; Male ; Female ; },
abstract = {Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental health illnesses due to their subjective and complicated nature. In this work, we offer an innovative methodology for predicting mental illnesses such as epilepsy, sleep disorders, bipolar disorder, eating disorders, and depression using a multimodal deep learning framework that integrates neurocardiac data fusion. The proposed framework combines MEG, EEG, and ECG signals to create a more comprehensive understanding of brain and cardiac function in individuals with mental disorders. The multimodal deep learning approach uses an integrated CNN-Bi-Transformer, i.e., CardioNeuroFusionNet, which can process multiple types of inputs simultaneously, allowing for the fusion of various modalities and improving the performance of the predictive representation. The proposed framework has undergone testing on data from the Deep BCI Scalp Database and was further validated on the Kymata Atlas dataset to assess its generalizability. The model achieved promising results with high accuracy (98.54%) and sensitivity (97.77%) in predicting mental problems, including neurological and psychiatric conditions. The neurocardiac data fusion has been found to provide additional insights into the relationship between brain and cardiac function in neurological conditions, which could potentially lead to more accurate diagnosis and personalized treatment options. The suggested method overcomes the shortcomings of earlier studies, which tended to concentrate on single-modality data, lacked thorough neurocardiac data fusion, and made use of less advanced machine learning algorithms. The comprehensive experimental findings, which provide an average improvement in accuracy of 2.72%, demonstrate that the suggested work performs better than other cutting-edge AI techniques and generalizes effectively across diverse datasets.},
}

Humans
Electroencephalography/methods
Deep Learning
*Nervous System Diseases/diagnosis/physiopathology
Electrocardiography
*Neural Networks, Computer
*Mental Disorders/diagnosis/physiopathology
Adult
Male
Female

@article {pmid40180157,
year = {2025},
author = {Liang, W and Xu, R and Wang, X and Cichocki, A and Jin, J},
title = {Enhancing Robustness of Spatial Filters in Motor Imagery based Brain-Computer Interface via Temporal Learning.},
journal = {Journal of neuroscience methods},
volume = {},
number = {},
pages = {110441},
doi = {10.1016/j.jneumeth.2025.110441},
pmid = {40180157},
issn = {1872-678X},
abstract = {BACKGROUND: In motor imagery-based brain-computer interface (MI-BCI) EEG decoding, spatial filtering play a crucial role in feature extraction. Recent studies have emphasized the importance of temporal filtering for extracting discriminative features in MI tasks. While many efforts have been made to optimize feature extraction externally, stabilizing features from spatial filtering remains underexplored.

NEW METHOD: To address this problem, we propose an approach to improve the robustness of temporal features by minimizing instability in the temporal domain. Specifically, we utilize Jensen-Shannon divergence to quantify temporal instability and integrate decision variables to construct an objective function that minimizes this instability. Our method enhances the stability of variance and mean values in the extracted features, improving the identification of discriminative features and reducing the effects of instability.

RESULTS: The proposed method was applied to spatial filtering models, and tested on two publicly datasets as well as a self-collected dataset. Results demonstrate that the proposed method significantly boosts classification accuracy, confirming its effectiveness in enhancing temporal feature stability.

We compared our method with spatial filtering methods, and the-state-of-the-art models. The proposed approach achieves the highest accuracy, with 92.43% on BCI competition III IVa dataset, 84.45% on BCI competition IV 2a dataset, and 73.18% on self-collected dataset.

CONCLUSIONS: Enhancing the instability of temporal features contributes to improved MI-BCI performance. This not only improves classification performance but also provides a stable foundation for future advancements. The proposed method shows great potential for EEG decoding.},
}

@article {pmid39466869,
year = {2025},
author = {Ke, Y and Du, J and Liu, S and Ming, D},
title = {Corrections to "Enhancing Detection of Control State for High-Speed Asynchronous SSVEP-BCIs Using Frequency-Specific Framework".},
journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
volume = {33},
number = {},
pages = {1169},
doi = {10.1109/TNSRE.2024.3487206},
pmid = {39466869},
issn = {1558-0210},
mesh = {Humans ; Algorithms ; *Brain-Computer Interfaces ; *Electroencephalography/methods ; *Evoked Potentials, Visual/physiology ; Reproducibility of Results ; },
abstract = {In the above article [1], we found the formula (1) is presented incorrectly because of an error in the formula editing process. The correction is as follows.},
}

Humans
Algorithms
*Brain-Computer Interfaces
*Electroencephalography/methods
*Evoked Potentials, Visual/physiology
Reproducibility of Results

@article {pmid40179638,
year = {2025},
author = {Thielen, J and Tangermann, M and Aarnoutse, EJ and Ramsey, NF and Vansteensel, MJ},
title = {Towards an sEEG-based BCI using code-modulated VEP: A case study showing the influence of electrode location on decoding efficiency.},
journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology},
volume = {173},
number = {},
pages = {213-215},
doi = {10.1016/j.clinph.2025.03.034},
pmid = {40179638},
issn = {1872-8952},
}

@article {pmid40177878,
year = {2025},
author = {Bhamidipaty, V and Botchu, B and Bhamidipaty, DL and Guntoory, I and Iyengar, KP},
title = {ChatGPT for speech-impaired assistance.},
journal = {Disability and rehabilitation. Assistive technology},
volume = {},
number = {},
pages = {1-3},
doi = {10.1080/17483107.2025.2483300},
pmid = {40177878},
issn = {1748-3115},
abstract = {Background: Speech and language impairments, though often used interchangeably, are two very distinct types of challenges. A speech impairment may lead to impaired ability to produce speech sounds whilst communication may be affected due to lack of fluency or articulation of words. Consequently this may affect a person's ability to articulate may affect academic achievement, social development and progress in life. ChatGPT (Generative Pretrained Transformer) is an open access AI (Artificial Intelligence) tool developed by Open AI® based on Large language models (LLMs) with the ability to respond to human prompts to generate texts using Supervised and Unsupervised Machine Learning (ML) Algorithms. This article explores the current role and future perspectives of ChatGPT AI Tool for Speech-Impaired Assistance. Methods: A cumulative search strategy using databases of PubMed, Google Scholar, Scopus and grey literature was conducted to generate this narrative review. Results: A spectrum of Enabling Technologies for Speech & Language Impairment have been explored. Augmentative and Alternative Communication technology (AAC), Integration with Neuroprosthesis technology and Speech therapy applications offer considerable potential to aid speech and language impaired individuals. Conclusion: Current applications of AI, ChatGPT and other LLM's offer promising solutions in enhancing communication in people affected by Speech and Language impairment. However, further research and development is required to ensure affordability, accessibility and authenticity of these AI Tools in clinical Practice.},
}

@article {pmid40175961,
year = {2025},
author = {Guo, X and Deng, R and Lai, J and Hu, S},
title = {Is muscarinic receptor agonist effective and tolerant for schizophrenia?.},
journal = {BMC psychiatry},
volume = {25},
number = {1},
pages = {323},
pmid = {40175961},
issn = {1471-244X},
mesh = {Humans ; *Schizophrenia/drug therapy ; *Muscarinic Agonists/adverse effects/therapeutic use ; Randomized Controlled Trials as Topic ; *Antipsychotic Agents/therapeutic use/adverse effects ; },
abstract = {BACKGROUND: Several randomized clinical trials (RCTs) have recently examined the efficacy and tolerability of muscarinic receptor agonists in schizophrenia. However, whether therapeutics targeting muscarinic receptors improve symptom management and reduce side effects remains systemically unexplored.

METHODS: Embase, PubMed, and Web of Science were searched from inception until Jan 9, 2025. Altogether, the efficacy and safety outcomes of four RCTs (397 individuals in the muscarinic receptor agonists group, and 374 in the placebo control group) were meta-analyzed. To compare scores of positive and negative syndrome scale (PANSS), response rate, discontinuation rate, and adverse events with muscarinic receptor agonists vs. placebo in patients with schizophrenia, scale changes were pooled as mean difference (MD) for continuous outcomes and risk ratio (RR) for categorical outcomes.

RESULTS: It revealed that muscarinic receptor agonists were superior to placebo in terms of decrease in the total PANSS score (MD, - 9.92; 95% CI, -12.46 to -7.37; I[2] = 0%), PANSS positive symptom subscore (MD, - 3.21; 95% CI, -4.02 to -2.40; I[2] = 0%), and PANSS negative symptom subscore (MD, -1.79; 95% CI, -2.47 to -1.11; I[2] = 48%). According to the study-defined response rate, the pooled muscarinic receptor agonists vs. placebo RR was 2.08 (95% CI, 1.59 to 2.72; I[2] = 0%). No significance was found in the discontinuation rate. Muscarinic receptor agonists were associated with a higher risk of nausea (RR = 4.61, 95% CI, 2.65 to 8.02; I[2] = 3%), and in particular, xanomeline-trospium was associated with risks of dyspepsia, vomiting, and constipation.

CONCLUSIONS: The findings highlighted an efficacy advantage with tolerated adverse event profiles for muscarinic receptor agonists in schizophrenia.},
}

Humans
*Schizophrenia/drug therapy
*Muscarinic Agonists/adverse effects/therapeutic use
Randomized Controlled Trials as Topic
*Antipsychotic Agents/therapeutic use/adverse effects

@article {pmid40175631,
year = {2025},
author = {Qi, Y and Zhu, X and Xiong, X and Yang, X and Ding, N and Wu, H and Xu, K and Zhu, J and Zhang, J and Wang, Y},
title = {Human motor cortex encodes complex handwriting through a sequence of stable neural states.},
journal = {Nature human behaviour},
volume = {},
number = {},
pages = {},
pmid = {40175631},
issn = {2397-3374},
support = {62276228//National Natural Science Foundation of China (National Science Foundation of China)/ ; 62336007//National Natural Science Foundation of China (National Science Foundation of China)/ ; LR24F020002//Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation)/ ; },
abstract = {How the human motor cortex (MC) orchestrates sophisticated sequences of fine movements such as handwriting remains a puzzle. Here we investigate this question through Utah array recordings from human MC during attempted handwriting of Chinese characters (n = 306, each consisting of 6.3 ± 2.0 strokes). We find that MC activity evolves through a sequence of states corresponding to the writing of stroke fragments during complicated handwriting. The directional tuning curve of MC neurons remains stable within states, but its gain or preferred direction strongly varies across states. By building models that can automatically infer the neural states and implement state-dependent directional tuning, we can significantly better explain the firing pattern of individual neurons and reconstruct recognizable handwriting trajectories with 69% improvement compared with baseline models. Our findings unveil that skilled and sophisticated movements are encoded through state-specific neural configurations.},
}

@article {pmid40175376,
year = {2025},
author = {Dong, L and Ke, Y and Zhu, X and Liu, S and Ming, D},
title = {Long-term cognitive and neurophysiological effects of mental rotation training.},
journal = {NPJ science of learning},
volume = {10},
number = {1},
pages = {16},
pmid = {40175376},
issn = {2056-7936},
support = {81741139//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
abstract = {Mental rotation, a crucial aspect of spatial cognition, can be improved through repeated practice. However, the long-term effects of combining training with non-invasive brain stimulation and its neurophysiological correlates are not well understood. This study examined the lasting effects of a 10-day mental rotation training with high-definition transcranial direct current stimulation (HD-tDCS) on behavioral and neural outcomes in 34 healthy participants. Participants were randomly assigned to the Active and Shan groups, with equal group sizes. Mental rotation tests and EEG recordings were conducted at baseline, 1 day, 20 days, and 90 days post-training. Although HD-tDCS showed no significant effect, training led to improved accuracy, faster response times, and enhanced task-evoked EEG responses, with benefits lasting up to 90 days. Notably, task-evoked EEG responses remained elevated 20 days post-training. Individual differences, such as gender and baseline performance, influenced the outcomes. These results emphasize the potential of mental rotation training for cognitive enhancement and suggest a need for further investigation into cognition-related neuroplasticity.},
}

@article {pmid40174604,
year = {2025},
author = {Kojima, S and Kortenbach, BE and Aalberts, C and Miloševska, S and de Wit, K and Zheng, R and Kanoh, S and Musso, M and Tangermann, M},
title = {Influence of pitch modulation on event-related potentials elicited by Dutch word stimuli in a brain-computer interface language rehabilitation task.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/adc83d},
pmid = {40174604},
issn = {1741-2552},
abstract = {OBJECTIVE: Recently, a novel language training using an auditory brain-computer interface (BCI) based on electroencephalogram recordings has been proposed for chronic stroke patients with aphasia. Tested with native German patients, it has shown significant and medium to large effect sizes in improving multiple aspects of language. During the training, the auditory BCI system delivers word stimuli using six spatially arranged loudspeakers. As delivering the word stimuli via headphones reduces spatial cues and makes the attention to target words more difficult, we investigate the influence of added pitch information. While pitch modulations have shown benefits for tone stimuli, they have not yet been investigated in the context of language stimuli.

APPROACH: The study translated the German experimental setup into Dutch. Seventeen native Dutch speakers participated in a single session of an exploratory study. An incomplete Dutch sentence cued them to listen to a target word embedded into a sequence of comparable non-target words while an electroencephalogram was recorded. Four conditions were compared within-subject to investigate the influence of pitch modulation: presenting the words spatially from six loudspeakers without (6D) and with pitch modulation (6D-Pitch), via stereo headphones with simulated spatial cues and pitch modulation (Stereo-Pitch), and via headphones without spatial cues or pitch modulation (Mono).

MAIN RESULTS: Comparing the 6D conditions of both language setups, the Dutch setup could be validated. For the Dutch setup, the binary AUC classification score in the 6D and the 6D-Pitch condition were 0.75 and 0.76, respectively, and adding pitch information did not significantly alter the binary classification accuracy of the event-related potential responses. The classification scores in the 6D condition and the Stereo-Pitch condition were on the same level.

SIGNIFICANCE: The competitive performance of pitch-modulated word stimuli suggests that the complex hardware setup of the 6D condition could be replaced by a headphone condition. If future studies with aphasia patients confirm the effectiveness and higher usability of a headphone-based language rehabilitation training, a simplified setup could be implemented more easily outside of clinics to deliver frequent training sessions to patients in need.},
}

@article {pmid40174326,
year = {2025},
author = {Wan, P and Xue, H and Zhang, S and Kong, W and Shao, W and Wen, B and Zhang, D},
title = {Image by co-reasoning: A collaborative reasoning-based implicit data augmentation method for dual-view CEUS classification.},
journal = {Medical image analysis},
volume = {102},
number = {},
pages = {103557},
doi = {10.1016/j.media.2025.103557},
pmid = {40174326},
issn = {1361-8423},
abstract = {Dual-view contrast-enhanced ultrasound (CEUS) data are often insufficient to train reliable machine learning models in typical clinical scenarios. A key issue is that limited clinical CEUS data fail to cover the underlying texture variations for specific diseases. Implicit data augmentation offers a flexible way to enrich sample diversity, however, inter-view semantic consistency has not been considered in previous studies. To address this issue, we propose a novel implicit data augmentation method for dual-view CEUS classification, which performs a sample-adaptive data augmentation with collaborative semantic reasoning across views. Specifically, the method constructs a feature augmentation distribution for each ultrasound view of an individual sample, accounting for intra-class variance. To maintain semantic consistency between the augmented views, plausible semantic changes in one view are transferred from similar instances in the other view. In this retrospective study, we validate the proposed method on the dual-view CEUS datasets of breast cancer and liver cancer, obtaining the superior mean diagnostic accuracy of 89.25% and 95.57%, respectively. Experimental results demonstrate its effectiveness in improving model performance with limited clinical CEUS data. Code: https://github.com/wanpeng16/CRIDA.},
}

@article {pmid40173067,
year = {2025},
author = {Tian, M and Li, S and Xu, R and Cichocki, A and Jin, J},
title = {An Interpretable Regression Method for Upper Limb Motion Trajectories Detection with EEG Signals.},
journal = {IEEE transactions on bio-medical engineering},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TBME.2025.3557255},
pmid = {40173067},
issn = {1558-2531},
abstract = {OBJECTIVE: The motion trajectory prediction (MTP) based brain-computer interface (BCI) leverages electroencephalography (EEG) signals to reconstruct the three-dimensional trajectory of upper limb motion, which is pivotal for the advancement of prosthetic devices that can assist motor-disabled individuals. Most research focused on improving the performance of regression models while neglecting the correlation between the implicit information extracted from EEG features across various frequency bands with limb kinematics. Current work aims to identify key channels that capture information related to various motion execution movements from different frequency bands and reconstruct three-dimensional motion trajectories based on EEG features.

METHODS: We propose an interpretable motion trajectory regression framework that extracts bandpower features from different frequency bands and concatenates them into multi-band fusion features. The extreme gradient boosting regression model with Bayesian optimization and Shapley additive explanation methods are introduced to provide further explanation.

RESULTS: The experimental results demonstrate that the proposed method achieves a mean Pearson correlation coefficient (PCC) value of 0.452, outperforming traditional regression models.

CONCLUSION: Our findings reveal that the contralateral side contributes the most to motion trajectory regression than the ipsilateral side which improves the clarity and interpretability of the motion trajectory regression model. Specifically, the feature from channel C5 in the Mu band is crucial for the movement of the right hand, while the feature from channel C3 in the Beta band plays a vital role.

SIGNIFICANCE: This work provides a novel perspective on the comprehensive study of movement disorders.},
}

@article {pmid40172963,
year = {2025},
author = {Yang, Z and Zheng, Y and Ma, D and Wang, L and Zhang, J and Song, T and Wang, Y and Zhang, Y and Nan, F and Su, N and Gao, Z and Guo, J},
title = {Phosphatidylinositol 4,5-bisphosphate activation mechanism of human KCNQ5.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {122},
number = {14},
pages = {e2416738122},
doi = {10.1073/pnas.2416738122},
pmid = {40172963},
issn = {1091-6490},
support = {2020YFA0908501//MOST | National Key Research and Development Program of China (NKPs)/ ; 32371204//MOST | National Natural Science Foundation of China (NSFC)/ ; },
mesh = {Humans ; *Phosphatidylinositol 4,5-Diphosphate/metabolism ; *KCNQ Potassium Channels/metabolism/chemistry/genetics ; *Cryoelectron Microscopy ; Calmodulin/metabolism/chemistry ; Protein Binding ; Ion Channel Gating ; Models, Molecular ; Protein Conformation ; },
abstract = {The human voltage-gated potassium channels KCNQ2, KCNQ3, and KCNQ5 can form homo- and heterotetrameric channels that are responsible for generating the neuronal M current and maintaining the membrane potential stable. Activation of KCNQ channels requires both the depolarization of membrane potential and phosphatidylinositol 4,5-bisphosphate (PIP2). Here, we report cryoelectron microscopy structures of the human KCNQ5-calmodulin (CaM) complex in the apo, PIP2-bound, and both PIP2- and the activator HN37-bound states in either a closed or an open conformation. In the closed conformation, a PIP2 molecule binds in the middle of the groove between two adjacent voltage-sensing domains (VSDs), whereas in the open conformation, one additional PIP2 binds to the interface of VSD and the pore domain, accompanying structural rearrangement of the cytosolic domain of KCNQ and CaM. The structures, along with electrophysiology analyses, reveal the two different binding modes of PIP2 and elucidate the PIP2 activation mechanism of KCNQ5.},
}

Humans
*Phosphatidylinositol 4,5-Diphosphate/metabolism
*KCNQ Potassium Channels/metabolism/chemistry/genetics
*Cryoelectron Microscopy
Calmodulin/metabolism/chemistry
Protein Binding
Ion Channel Gating
Models, Molecular
Protein Conformation

@article {pmid40172828,
year = {2025},
author = {Li, M and Zhao, Q and Zhang, T and Ge, J and Wang, J and Xu, G},
title = {A Personalized Predictor of Motor Imagery Ability Based on Multi-frequency EEG Features.},
journal = {Neuroscience bulletin},
volume = {},
number = {},
pages = {},
pmid = {40172828},
issn = {1995-8218},
abstract = {A brain-computer interface (BCI) based on motor imagery (MI) provides additional control pathways by decoding the intentions of the brain. MI ability has great intra-individual variability, and the majority of MI-BCI systems are unable to adapt to this variability, leading to poor training effects. Therefore, prediction of MI ability is needed. In this study, we propose an MI ability predictor based on multi-frequency EEG features. To validate the performance of the predictor, a video-guided paradigm and a traditional MI paradigm are designed, and the predictor is applied to both paradigms. The results demonstrate that all subjects achieved > 85% prediction precision in both applications, with a maximum of 96%. This study indicates that the predictor can accurately predict the individuals' MI ability in different states, provide the scientific basis for personalized training, and enhance the effect of MI-BCI training.},
}

@article {pmid40172544,
year = {2025},
author = {Li, H and Li, C and Zhao, H and Li, Q and Zhao, Y and Gong, J and Li, G and Yu, H and Tian, Q and Liu, Z and Han, F},
title = {Flexible fibrous electrodes for implantable biosensing.},
journal = {Nanoscale},
volume = {},
number = {},
pages = {},
doi = {10.1039/d4nr04542d},
pmid = {40172544},
issn = {2040-3372},
abstract = {Flexible fibrous electrodes have emerged as a promising technology for implantable biosensing applications, offering significant advancements in the monitoring and manipulation of biological signals. This review systematically explores the key aspects of flexible fibrous electrodes, including the materials, structural designs, and fabrication methods. A detailed discussion of electrode performance metrics is provided, covering factors such as conductivity, stretchability, axial channel count, and implantation duration. The diverse applications of these electrodes in electrophysiological signal monitoring, electrochemical sensing, tissue strain monitoring, and in vivo electrical stimulation are reviewed, highlighting their potential in biomedical settings. Finally, the review discusses the eight major challenges currently faced by implantable fibrous electrodes and explores future development directions, providing critical technical analysis and potential solutions for the advancement of next-generation flexible implantable fiber-based biosensors.},
}

@article {pmid40172075,
year = {2025},
author = {Wu, X and Liang, C and Bustillo, J and Kochunov, P and Wen, X and Sui, J and Jiang, R and Yang, X and Fu, Z and Zhang, D and Calhoun, VD and Qi, S},
title = {The Impact of Atlas Parcellation on Functional Connectivity Analysis Across Six Psychiatric Disorders.},
journal = {Human brain mapping},
volume = {46},
number = {5},
pages = {e70206},
doi = {10.1002/hbm.70206},
pmid = {40172075},
issn = {1097-0193},
support = {BE2023668//Jiangsu Provincial Key Research and Development Program/ ; BK20220889//Natural Science Foundation of Jiangsu Province/ ; 62376124//National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Magnetic Resonance Imaging/methods ; Adult ; *Atlases as Topic ; Male ; Female ; *Connectome/methods ; *Bipolar Disorder/diagnostic imaging/physiopathology/pathology ; *Schizophrenia/diagnostic imaging/physiopathology/pathology ; *Depressive Disorder, Major/diagnostic imaging/physiopathology ; *Mental Disorders/diagnostic imaging/physiopathology ; Autism Spectrum Disorder/diagnostic imaging/physiopathology ; Young Adult ; Nerve Net/diagnostic imaging/physiopathology ; Attention Deficit Disorder with Hyperactivity/diagnostic imaging/physiopathology ; Psychotic Disorders/diagnostic imaging/physiopathology/pathology ; Middle Aged ; Adolescent ; },
abstract = {Neuropsychiatric disorders are associated with altered functional connectivity (FC); however, the reported regional patterns of functional alterations suffered from low replicability and high variability. This is partly because of differences in the atlas and delineation techniques used to measure FC-related deficits within/across disorders. We systematically investigated the impact of the brain parcellation approach on the FC-based brain network analysis. We focused on identifying the replicable FCs using three structural brain atlases, including Automated Anatomical Labeling (AAL), Brainnetome atlas (BNA) and HCP_MMP_1.0, and four functional brain parcellation approaches: Yeo-Networks (Yeo), Gordon parcel (Gordon) and two Schaefer parcelletions, among correlation, group difference, and classification tasks in six neuropsychiatric disorders: attention deficit and hyperactivity disorder (ADHD, n = 340), autism spectrum disorder (ASD, n = 513), schizophrenia (SZ, n = 200), schizoaffective disorder (SAD, n = 142), bipolar disorder (BP, n = 172), and major depression disorder (MDD, n = 282). Our cross-atlas/disorder analyses demonstrated that frontal-related FC deficits were reproducible in all disorders, independent of the atlasing approach; however, replicable FC extraction in other areas and the classification accuracy were affected by the parcellation schema. Overall, functional atlases with finer granularity performed better in classification tasks. Specifically, the Schaefer atlases generated the most repeatable FC deficit patterns across six illnesses. These results indicate that frontal-related FCs may serve as potential common and robust neuro-abnormalities across 6 psychiatric disorders. Furthermore, in order to improve the replicability of rsfMRI-based FC analyses, this study suggests the use of functional templates at larger granularity.},
}

Humans
*Magnetic Resonance Imaging/methods
Adult
*Atlases as Topic
Male
Female
*Connectome/methods
*Bipolar Disorder/diagnostic imaging/physiopathology/pathology
*Schizophrenia/diagnostic imaging/physiopathology/pathology
*Depressive Disorder, Major/diagnostic imaging/physiopathology
*Mental Disorders/diagnostic imaging/physiopathology
Autism Spectrum Disorder/diagnostic imaging/physiopathology
Young Adult
Nerve Net/diagnostic imaging/physiopathology
Attention Deficit Disorder with Hyperactivity/diagnostic imaging/physiopathology
Psychotic Disorders/diagnostic imaging/physiopathology/pathology
Middle Aged
Adolescent