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• Protocol for state-based decoding of hand movement parameters using neural signals.
  We present a protocol for decoding kinematic and kinetic parameters from the primary somatosensory cortex during active and passive hand movements in a center-out reaching task using state-based and conventional decoders. We describe steps for preparing data a…
  pubmed Ghodrati MT, Aghababaei S, Mirfathollahi A, Shalchyan V 等 2024 Dec 20 置信度 0.82
• Unsupervised method for representation transfer from one brain to another.
  Although the anatomical arrangement of brain regions and the functional structures within them are similar across individuals, the representation of neural information, such as recorded brain activity, varies among individuals owing to various factors. Therefo…
  pubmed Nakamura D, Kaji S, Kanai R, Hayashi R 2024 置信度 0.82
• Delayed knowledge transfer: Cross-modal knowledge transfer from delayed stimulus to EEG for continuous attention detection based on spike-represented EEG signals.
  Decoding visual and auditory stimuli from brain activities, such as electroencephalography (EEG), offers promising advancements for enhancing machine-to-human interaction. However, effectively representing EEG signals remains a significant challenge. In this p…
  pubmed Sun P, De Winne J, Zhang M, Devos P 等 2025 Mar 置信度 0.82
• Low-power and lightweight spiking transformer for EEG-based auditory attention detection.
  EEG signal analysis can be used to study brain activity and the function and structure of neural networks, helping to understand neural mechanisms such as cognition, emotion, and behavior. EEG-based auditory attention detection is using EEG signals to determin…
  pubmed Lan Y, Wang Y, Zhang Y, Zhu H 2025 Mar 置信度 0.82
• Single-Nucleus RNA Sequencing Reveals the Spatiotemporal Dynamics of Disease-Associated Microglia in Amyotrophic Lateral Sclerosis.
  Disease-associated microglia (DAM) are observed in neurodegenerative diseases, demyelinating disorders, and aging. However, the spatiotemporal dynamics and evolutionary trajectory of DAM during the progression of amyotrophic lateral sclerosis (ALS) remain uncl…
  pubmed Chen LX, Zhang MD, Xu HF, Ye HQ 等 2024 置信度 0.82
• Amylopectin-based Hydrogel Probes for Brain-machine Interfaces.
  Implantable neural probes hold promise for acquiring brain data, modulating neural circuits, and treating various brain disorders. However, traditional implantable probes face significant challenges in practical applications, such as balancing sensitivity with…
  pubmed Qin Y, Zhao H, Chang Q, Liu Y 等 2025 Feb 置信度 0.82
• Deconstructing the neural circuit underlying social hierarchy in mice.
  Social competition determines hierarchical social status, which profoundly influences animals' behavior and health. The dorsomedial prefrontal cortex (dmPFC) plays a fundamental role in regulating social competitions, but it was unclear how the dmPFC orchestra…
  pubmed Xin Q, Zheng D, Zhou T, Xu J 等 2025 Feb 5 置信度 0.82
• Adiponectin receptor 1-mediated basolateral amygdala-prelimbic cortex circuit regulates methamphetamine-associated memory.
  The association between drug-induced rewards and environmental cues represents a promising strategy to address addiction. However, the neural networks and molecular mechanisms orchestrating methamphetamine (MA)-associated memories remain incompletely character…
  pubmed Chen Z, Tang S, Xiao X, Hong Y 等 2024 Dec 24 置信度 0.82
• Four-class ASME BCI: investigation of the feasibility and comparison of two strategies for multiclassing.
  The ASME (stands for Auditory Stream segregation Multiclass ERP) paradigm is proposed and used for an auditory brain-computer interface (BCI). In this paradigm, a sequence of sounds that are perceived as multiple auditory streams are presented simultaneously, …
  pubmed Kojima S, Kanoh S 2024 置信度 0.82
• Decoding continuous motion trajectories of upper limb from EEG signals based on feature selection and nonlinear methods.
  Objective. Brain-computer interface (BCI) system has emerged as a promising technology that provides direct communication and control between the human brain and external devices. Among the various applications of BCI, limb motion decoding has gained significa…
  pubmed Li S, Tian M, Xu R, Cichocki A 等 2024 Dec 27 置信度 0.82
• Efficacy of bright light therapy improves outcomes of perinatal depression: A systematic review and meta-analysis of randomized controlled trials.
  The efficacy of bright light therapy (BLT) in the context of perinatal depression remains underexplored. This meta-analysis aimed to systematically assess the effectiveness of BLT among perinatal depression. A comprehensive literature search was performed acro…
  pubmed Du L, Zeng J, Yu H, Chen B 等 2025 Feb 置信度 0.82
• A passive brain-computer interface for operator mental fatigue estimation in monotonous surveillance operations: time-on-task and performance labeling issues.
  Objective : A central component of search and rescue missions is the visual search of survivors. In large parts, this depends on human operators and is, therefore, subject to the constraints of human cognition, such as mental fatigue (MF). This makes detecting…
  pubmed Hinss MF, Jahanpour ES, Brock AM, Roy RN 2024 Dec 18 置信度 0.82
• VME-EFD : A novel framework to eliminate the Electrooculogram artifact from single-channel EEGs.
  The diagnosis of neurological disorders often involves analyzing EEG data, which can be contaminated by artifacts from eye movements or blinking (EOG). To improve the accuracy of EEG-based analysis, we propose a novel framework, VME-EFD, which combines Variati…
  pubmed Noorbasha SK, Kumar A 2024 Dec 20 置信度 0.82
• A reinforcement learning based software simulator for motor brain-computer interfaces.
  Intracortical motor brain-computer interfaces (BCIs) are expensive and time-consuming to design because accurate evaluation traditionally requires real-time experiments. In a BCI system, a user interacts with an imperfect decoder and continuously changes motor…
  pubmed Liang KF, Kao JC 2024 Nov 26 置信度 0.82
• A brief history of the development of transcranial tissue Doppler ultrasound.
  This article documents the early development of the first transcranial Doppler (TCD)-based ultrasound system for continuous monitoring of brain tissue pulsations (BTPs). Transcranial tissue Doppler (TCTD) uses a lightweight, wearable single-element ultrasound …
  pubmed Nicholls JK, Lecchini-Visintini A, Ince J, Pallett E 等 2024 Dec 6 置信度 0.82
• A visually-induced optogenetically-engineered system enables autonomous glucose homeostasis in mice.
  With the global population increasing and the demographic shifting toward an aging society, the number of patients diagnosed with conditions such as peripheral neuropathies resulting from diabetes is expected to rise significantly. This growing health burden h…
  pubmed Li S, Zhou Y, Kong D, Miao Y 等 2025 Feb 10 置信度 0.82
• Role of the Thalamic Reticular Nucleus in Social Memory.
  pubmed Liu X, Zhu J, Zheng J, Xu H 2025 Feb 置信度 0.82
• Enhanced control of a brain-computer interface by tetraplegic participants via neural-network-mediated feature extraction.
  To infer intent, brain-computer interfaces must extract features that accurately estimate neural activity. However, the degradation of signal quality over time hinders the use of feature-engineering techniques to recover functional information. By using neural…
  pubmed Haghi B, Aflalo T, Kellis S, Guan C 等 2025 Jun 置信度 0.82
• Laser-induced adhesives with excellent adhesion enhancement and reduction capabilities for transfer printing of microchips.
  Transfer printing based on tunable and reversible adhesive that enables the heterogeneous integration of materials is essential for developing envisioned electronic systems. An adhesive with both adhesion enhancement and reduction capabilities in a rapid and s…
  pubmed Li C, Zhang S, Jiang J, Wang S 等 2024 Dec 6 置信度 0.82
• Mixed reality alters motor planning and control.
  Compared to physical unmediated reality (UR), mixed reality technologies, such as Virtual (VR) and Augmented (AR) Reality, entail perturbations across multiple sensory modalities (visual, haptic, etc.) that could alter how actors move within the different envi…
  pubmed Wang XM, Nitsche M, Resch G, Mazalek A 等 2025 Mar 5 置信度 0.82
• Counting on AR: EEG responses to incongruent information with real-world context.
  Augmented Reality (AR) technologies enhance the real world by integrating contextual digital information about physical entities. However, inconsistencies between physical reality and digital augmentations, which may arise from errors in the visualized informa…
  pubmed Wimmer M, Pepicelli A, Volmer B, ElSayed N 等 2025 Feb 置信度 0.82
• Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study.
  Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical…
  pubmed Rezaeitaleshmahalleh M, Mu N, Lyu Z, Gemmete J 等 2024 Dec 4 置信度 0.82
• Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques.
  In the domain of passive brain-computer interface applications, the identification of emotions is both essential and formidable. Significant research has recently been undertaken on emotion identification with electroencephalogram (EEG) data. The aim of this p…
  pubmed Karthiga M, Suganya E, Sountharrajan S, Balusamy B 等 2024 Dec 4 置信度 0.82
• Online assessment in young children: Challenges and considerations.
  In the years following the COVID-19 pandemic, online assessment has emerged as an increasingly popular method for testing children. This review aims to review key advantages and disadvantages of online assessment in young children, specifically in the area of …
  pubmed McBride C, Ho JC, McQuade M, Ngan VSH 等 2025 Feb 置信度 0.82
• Predicting proprioceptive cortical anatomy and neural coding with topographic autoencoders.
  Proprioception is one of the least understood senses, yet fundamental for the control of movement. Even basic questions of how limb pose is represented in the somatosensory cortex are unclear. We developed a topographic variational autoencoder with lateral con…
  pubmed Grogan M, Blum KP, Wu Y, Harston JA 等 2024 Dec 置信度 0.82
• Editorial: Application of neuroscience in information systems and software engineering.
  pubmed Pryss R, Vom Brocke J, Reichert M, Rukzio E 等 2024 置信度 0.82
• Wounds and Vulnerabilities. The Participation of Special Operations Forces in Experimental Brain-Computer Interface Research.
  Brain-computer interfaces (BCIs) exemplify a dual-use neurotechnology with significant potential in both civilian and military contexts. While BCIs hold promise for treating neurological conditions such as spinal cord injuries and amyotrophic lateral sclerosis…
  pubmed Gielas AM 2024 Dec 4 置信度 0.82
• On the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training: an eye-tracking and HD-EEG study.
  Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor training to help the patient achieve a physiological gait pattern, reducing the physical effort required by therapist. By introducing the robot as a third agent to the tra…
  pubmed Patarini F, Tamburella F, Pichiorri F, Mohebban S 等 2024 Dec 3 置信度 0.82
• Different responses of MVL neurons when pigeons attend to local versus global information during object classification.
  Most prior studies have indicated that pigeons have a tendency to rely on local information for target categorization, yet there is a lack of electrophysiological evidence to support this claim. The mesopallium ventrolaterale (MVL) is believed to play a role i…
  pubmed Zhu M, Yang Y, Niu X, Peng Y 等 2025 Mar 5 置信度 0.82
• Multi-layer transfer learning algorithm based on improved common spatial pattern for brain-computer interfaces.
  In the application of brain-computer interface, the differences in imaging methods and brain structure between subjects hinder the effectiveness of decoding algorithms when applied on different subjects. Transfer learning has been designed to solve this proble…
  pubmed Cai Z, Gao Y, Fang F, Zhang Y 等 2025 Mar 置信度 0.82
• An adaptive session-incremental broad learning system for continuous motor imagery EEG classification.
  Motor imagery electroencephalography (MI-EEG) is usually used as a driving signal in neuro-rehabilitation systems, and its feature space varies with the recovery progress. It is required to endow the recognition model with continuous learning and self-updating…
  pubmed Yang Y, Li M, Wang L 2025 Apr 置信度 0.82
• Automated hippocampal sparing whole brain radiotherapy with simultaneous integrated boost for multiple brain metastases: Halcyon, HyperArc on TrueBeam, and coplanar TrueBeam.
  To demonstrate the ease and feasibility that hippocampal sparing whole brain (WB) simultaneous integrated boost (HSWB-SIB) plans can be generated using knowledge-based planning and Eclipse Scripting Application Programming Interface (ESAPI) for three different…
  pubmed McCarthy S, Clark R, Magliari A, St Clair W 等 2025 Feb 置信度 0.82
• Spatial and spectral changes in cortical surface potentials during pinching versusthumb and index finger flexion.
  Electrocorticographic (ECoG) signals provide high-fidelity representations of sensorimotor cortex activation during contralateral hand movements. Understanding the relationship between independent and coordinated finger movements along with their corresponding…
  pubmed Kerezoudis P, Jensen MA, Huang H, Ojemann JG 等 2025 Jan 10 置信度 0.82
• [The role of EEG in tomorrow's medicine].
  There is a breathtakingly rapid development in various areas that take advantage of the ever-improving possibilities to record and analyze the electrical activity generated in the brain. In this article, we attempt to briefly describe some of these areas, incl…
  pubmed Amandusson Å, Nilsson J, Pequito S 2024 Nov 13 置信度 0.82
• Engineering and Technological Advancements in Repetitive Transcranial Magnetic Stimulation (rTMS): A Five-Year Review.
  In the past five years, repetitive transcranial magnetic stimulation (rTMS) has evolved significantly, driven by advancements in device design, treatment protocols, software integration, and brain-computer interfaces (BCIs). This review evaluates how these inn…
  pubmed Tubbs A, Vazquez EA, Abigail Tubbs, Enrique Alvarez Vazquez 2024 Oct 30 置信度 0.82 Transcranial magnetic stimulationPhysical medicine and rehabilitationNeuroscienceMedicineStimulation
• Improving EEG Forward Modeling Using High-Resolution Five-Layer BEM-FMM Head Models: Effect on Source Reconstruction Accuracy.
  Electroencephalographic (EEG) source localization is a fundamental tool for clinical diagnoses and brain-computer interfaces. We investigate the impact of model complexity on reconstruction accuracy by comparing the widely used three-layer boundary element met…
  pubmed Nuñez Ponasso G, Wartman WA, McSweeney RC, Lai P 等 2024 Oct 26 置信度 0.82
• IMPDH inhibitors upregulate PD-L1 in cancer cells without impairing immune checkpoint inhibitor efficacy.
  Tumor cells are characterized by rapid proliferation. In order to provide purines for DNA and RNA synthesis, inosine 5'-monophosphate dehydrogenase (IMPDH), a key enzyme in the de novo guanosine biosynthesis, is highly expressed in tumor cells. In this study w…
  pubmed Zheng MM, Li JY, Guo HJ, Zhang J 等 2025 Apr 置信度 0.82
• Exploring neurofeedback as a therapeutic intervention for subjective cognitive decline.
  This study addresses the pressing issue of subjective cognitive decline in aging populations by investigating neurofeedback (NFB) as a potential early therapeutic intervention. By evaluating the efficacy of individualised NFB training compared to standard prot…
  pubmed Paban V, Feraud L, Weills A, Duplan F 2024 Dec 置信度 0.82
• Multi-layer ear-scalp distillation framework for ear-EEG classification enhancement.
  Ear-electroencephalography (ear-EEG) holds significant promise as a practical tool in brain-computer interfaces (BCIs) due to its enhanced unobtrusiveness, comfort, and mobility compared to traditional steady-state visual evoked potential (SSVEP)-based BCI sys…
  pubmed Sun Y, Zhang F, Li Z, Liu X 等 2024 Dec 6 置信度 0.82
• Improving subject transfer in EEG classification with divergence estimation.
  Objective . Classification models for electroencephalogram (EEG) data show a large decrease in performance when evaluated on unseen test subjects. We improve performance using new regularization techniques during model training. Approach . We propose several g…
  pubmed Smedemark-Margulies N, Wang Y, Koike-Akino T, Liu J 等 2024 Dec 16 置信度 0.82
• Hybrid Functional Near-Infrared Spectroscopy System and Electromyography for Prosthetic Knee Control.
  The increasing number of individuals with limb loss worldwide highlights the need for advancements in prosthetic knee technology. To improve control and quality of life, integrating brain-computer communication with motor imagery offers a promising solution. T…
  pubmed AlQahtani NJ, Al-Naib I, Ateeq IS, Althobaiti M 2024 Nov 13 置信度 0.82
• Flexible bioelectronic systems with large-scale temperature sensor arrays for monitoring and treatments of localized wound inflammation.
  Continuous monitoring and closed-loop therapy of soft wound tissues is of particular interest in biomedical research and clinical practices. An important focus is on the development of implantable bioelectronics that can measure time-dependent temperature dist…
  pubmed Liu J, Li Z, Sun M, Zhou L 等 2024 Dec 3 置信度 0.82
• Opportunities for System Neuroscience.
  Systems neuroscience explores the intricate organization and dynamic function of neural circuits and networks within the brain. By elucidating how these complex networks integrate to execute mental operations, this field aims to deepen our understanding of the…
  pubmed Chan RW, Edelman BJ, Tsang SY, Gao K 等 2024 置信度 0.82
• Toward Foundation Models in Radiology? Quantitative Assessment of GPT-4V's Multimodal and Multianatomic Region Capabilities.
  Background Large language models have already demonstrated potential in medical text processing. GPT-4V, a large vision-language model from OpenAI, has shown potential for medical imaging, yet a quantitative analysis is lacking. Purpose To quantitatively asses…
  pubmed Strotzer QD, Nieberle F, Kupke LS, Napodano G 等 2024 Nov 置信度 0.82
• Classification of motor imagery EEG with ensemble RNCA model.
  Motor Imagery (MI) based brain-computer interface (BCI) systems are used for regaining the motor functions of neurophysiologically affected persons. But the performance of MI tasks is degraded due to the presence of redundant EEG channels. Hence, a novel ensem…
  pubmed Thenmozhi T, Helen R, Mythili S 2025 Feb 28 置信度 0.82
• Single-channel electroencephalography decomposition by detector-atom network and its pre-trained model.
  Signal decomposition techniques utilizing multi-channel spatial features are critical for analyzing, denoising, and classifying electroencephalography (EEG) signals. To facilitate the decomposition of signals recorded with limited channels, this paper presents…
  pubmed Higashi H 2025 Feb 置信度 0.82
• Robust Sodium Carboxymethyl Cellulose-Based Neuromorphic Device with High Biocompatibility Engineered through Molecular Polarization for the Emulation of Learning Behaviors in the Human Brain.
  Sodium carboxymethyl cellulose (CMC-Na), derived from natural cellulose and frequently employed as a biocompatible coating, thus renders it an ideal component for the construction of highly biocompatible neuromorphic devices aimed at biomachine interfaces. Her…
  pubmed Liu Y, Wang M, Liu Z, Li L 等 2024 Dec 11 置信度 0.82
• Auditory evoked potential electroencephalography-biometric dataset.
  This work aims to assess the use of electroencephalographic (EEG) signals as a means of biometric authentication. More than 240 recordings, each lasting 2 min, were gathered from 20 subjects involved in the data collection. Data include the results of experime…
  pubmed Abo Alzahab N, Iorio AD, Apollonio L, Alshalak M 等 2024 Dec 置信度 0.82
• Enhancing detection of SSVEP-based BCIs via a novel temporally local canonical correlation analysis.
  In recent years, spatial filter-based frequency recognition methods have become popular in steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems. However, these methods are ineffective in suppressing local noise, and they re…
  pubmed Xia G, Wang L, Xiong S, Deng J 2025 Feb 置信度 0.82
• CVR-BBI: an open-source VR platform for multi-user collaborative brain to brain interfaces.
  As brain imaging and neurofeedback technologies advance, the brain-to-brain interface (BBI) has emerged as an innovative field, enabling in-depth exploration of cross-brain information exchange and enhancing our understanding of collaborative intelligence. How…
  pubmed Liu D, Wei Y 2024 Nov 28 置信度 0.82
• Chisco: An EEG-based BCI dataset for decoding of imagined speech.
  The rapid advancement of deep learning has enabled Brain-Computer Interfaces (BCIs) technology, particularly neural decoding techniques, to achieve higher accuracy and deeper levels of interpretation. Interest in decoding imagined speech has significantly incr…
  pubmed Zhang Z, Ding X, Bao Y, Zhao Y 等 2024 Nov 21 置信度 0.82
• Investigating unilateral and bilateral motor imagery control using electrocorticography and fMRI in awake craniotomy.
  The rapid development of neurosurgical techniques, such as awake craniotomy, has increased opportunities to explore the mysteries of the brain. This is crucial for deepening our understanding of motor control and imagination processes, especially in developing…
  pubmed Ma J, Li Z, Zheng Q, Li S 等 2024 Dec 1 置信度 0.82
• Sparse Bayesian correntropy learning for robust muscle activity reconstruction from noisy brain recordings.
  Sparse Bayesian learning has promoted many effective frameworks of brain activity decoding for the brain-computer interface, including the direct reconstruction of muscle activity using brain recordings. However, existing sparse Bayesian learning algorithms ma…
  pubmed Li Y, Chen B, Yoshimura N, Koike Y 等 2025 Feb 置信度 0.82
• FDCN-C: A deep learning model based on frequency enhancement, deformable convolution network, and crop module for electroencephalography motor imagery classification.
  Motor imagery (MI)-electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with external world via manipulating smart equipment. Currently, deep learning (DL)-based m…
  pubmed Liang HJ, Li LL, Cao GZ 2024 置信度 0.82
• Boosted Harris Hawks Shuffled Shepherd Optimization Augmented Deep Learning based motor imagery classification for brain computer interface.
  Motor imagery (MI) classification has been commonly employed in making brain-computer interfaces (BCI) to manage the outside tools as a substitute neural muscular path. Effectual MI classification in BCI improves communication and mobility for people with a br…
  pubmed Assiri FY, Ragab M 2024 置信度 0.82
• Brain-computer interfaces patient preferences: a systematic review.
  Abstract Objective. Brain–computer interfaces (BCIs) have the potential to restore motor capabilities and functional independence in individuals with motor impairments. Despite accelerating advances in the performance of implanted devices, few studies have ide…
  pubmed Brannigan JFM, Liyanage K, Horsfall HL, Bashford L 等 2024 Dec 10 置信度 0.82 CINAHLBrain–computer interfacePreferenceMEDLINEPhysical medicine and rehabilitation
• SSVEP modulation via non-volitional neurofeedback: anin silicoproof of concept.
  Objective. Neuronal oscillatory patterns are believed to underpin multiple cognitive mechanisms. Accordingly, compromised oscillatory dynamics were shown to be associated with neuropsychiatric conditions. Therefore, the possibility of modulating, or controllin…
  pubmed Estiveira J, Soares E, Pires G, Nunes UJ 等 2024 Dec 5 置信度 0.82
• Enhancing neuroprosthesis calibration: the advantage of integrating prior training over exclusive use of new data.
  Objective. Neuroprostheses typically operate under supervised learning, in which a machine-learning algorithm is trained to correlate neural or myoelectric activity with an individual's motor intent. Due to the stochastic nature of neuromyoelectric signals, al…
  pubmed Thomson CJ, Tully TN, Stone ES, Morrell CB 等 2024 Nov 29 置信度 0.82
• An integrated transcriptomic cell atlas of human neural organoids.
  Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult…
  pubmed He Z, Dony L, Fleck JS, Szałata A 等 2024 Nov 置信度 0.82
• A continuous pursuit dataset for online deep learning-based EEG brain-computer interface.
  This dataset is from an EEG brain-computer interface (BCI) study investigating the use of deep learning (DL) for online continuous pursuit (CP) BCI. In this task, subjects use Motor Imagery (MI) to control a cursor to follow a randomly moving target, instead o…
  pubmed Forenzo D, Zhu H, He B, Dylan Forenzo 等 2024 Nov 20 置信度 0.82 Brain–computer interfaceMotor imageryComputer scienceElectroencephalographyInterface (matter)
• A Method for Detecting Depression in Adolescence Based on an Affective Brain-Computer Interface and Resting-State Electroencephalogram Signals.
  Depression is increasingly prevalent among adolescents and can profoundly impact their lives. However, the early detection of depression is often hindered by the time-consuming diagnostic process and the absence of objective biomarkers. In this study, we propo…
  pubmed Guan Z, Zhang X, Huang W, Li K 等 2025 Mar 置信度 0.82
• Wearable EEG Neurofeedback Based-on Machine Learning Algorithms for Children with Autism: A Randomized, Placebo-controlled Study.
  Behavioral interventions have been shown to ameliorate the electroencephalogram (EEG) dynamics underlying the behavioral symptoms of autism spectrum disorder (ASD), while studies have also demonstrated that mirror neuron mu rhythm-based EEG neurofeedback train…
  pubmed Wang XN, Zhang T, Han BC, Luo WW 等 2024 Dec 置信度 0.82
• Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.
  Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain-computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals from stroke…
  pubmed Xu F, Shi W, Lv C, Sun Y 等 2025 Jan 置信度 0.82
• Hopeful progress in artificial vision.
  Visual impairment has been augmented by glasses for centuries. With the advent of newer technologies, correction of more severe visual impairment may be possible with brain-computer interface and eye implants.
  pubmed Shah AM 2025 Jan 置信度 0.82
• Decoding sensorimotor information from somatosensory cortex by flexible epicorticalμECoG arrays in unrestrained behaving rats.
  Objective. Brain-computer interfaces (BCI) are promising for severe neurological conditions and there are ongoing efforts to develop state-of-the-art neural interfaces, hardware, and software tools. We tested the potential of novel reduced graphene oxide (rGO)…
  pubmed Kılınç Bülbül D, Walston ST, Duvan FT, Garrido JA 等 2024 Nov 27 置信度 0.82
• A multi-feature fusion graph attention network for decoding motor imagery intention in spinal cord injury patients.
  Objective. Electroencephalogram (EEG) signals exhibit temporal-frequency-spatial multi-domain feature, and due to the nonplanar nature of the brain surface, the electrode distributions follow non-Euclidean topology. To fully resolve the EEG signals, this study…
  pubmed Leng J, Gao L, Jiang X, Lou Y 等 2024 Dec 27 置信度 0.82
• Simplified internal models in human control of complex objects.
  Humans are skillful at manipulating objects that possess nonlinear underactuated dynamics, such as clothes or containers filled with liquids. Several studies suggested that humans implement a predictive model-based strategy to control such objects. However, th…
  pubmed Bazzi S, Stansfield S, Hogan N, Sternad D 2024 Nov 置信度 0.82
• An effective classification approach for EEG-based motor imagery tasks combined with attention mechanisms.
  Currently, electroencephalogram (EEG)-based motor imagery (MI) signals have been received extensive attention, which can assist disabled subjects to control wheelchair, automatic driving and other activities. However, EEG signals are easily affected by some fa…
  pubmed Li J, Shi W, Li Y 2024 Oct 置信度 0.82
• Functional connectivity of EEG motor rhythms after spinal cord injury.
  Spinal cord injury (SCI), which is the injury of the spinal cord site resulting in motor dysfunction, has prompted the use of motor imagery (MI)-based brain computer interface (BCI) systems for motor function reconstruction. However, analyzing electroencephalo…
  pubmed Leng J, Yu X, Wang C, Zhao J 等 2024 Oct 置信度 0.82
• Development of a humanoid robot control system based on AR-BCI and SLAM navigation.
  Brain-computer interface (BCI)-based robot combines BCI and robotics technology to realize the brain's intention to control the robot, which not only opens up a new way for the daily care of the disabled individuals, but also provides a new way of communicatio…
  pubmed Wang Y, Zhang M, Li M, Cui H 等 2024 Oct 置信度 0.82
• Classification algorithm for motor imagery fusing CNN and attentional mechanisms based on functional near-infrared spectroscopy brain image.
  With the continuing development of brain-computer interface technology, the analysis and interpretation of brain signals are becoming increasingly important. In the field of brain-computer interfaces, motor imagery (MI) is an important paradigm for generating …
  pubmed Shi X, Li B, Wang W, Qin Y 等 2024 Oct 置信度 0.82
• Short-length SSVEP data extension by a novel generative adversarial networks based framework.
  Steady-state visual evoked potentials (SSVEPs) based brain-computer interface (BCI) has received considerable attention due to its high information transfer rate (ITR) and available quantity of targets. However, the performance of frequency identification meth…
  pubmed Pan Y, Li N, Zhang Y, Xu P 等 2024 Oct 置信度 0.82
• Discriminative possibilistic clustering promoting cross-domain emotion recognition.
  The affective Brain-Computer Interface (aBCI) systems strive to enhance prediction accuracy for individual subjects by leveraging data from multiple subjects. However, significant differences in EEG (Electroencephalogram) feature patterns among subjects often …
  pubmed Dan Y, Zhou D, Wang Z 2024 置信度 0.82
• Cortico-muscular coherence of time-frequency and spatial characteristics under movement observation, movement execution, and movement imagery.
  Studies show that movement observation (MO), movement imagery (MI), or movement execution (ME) based brain-computer interface systems are promising in promoting the rehabilitation and reorganization of damaged motor function. This study was aimed to explore an…
  pubmed Zhou L, Wu B, Qin B, Gao F 等 2024 Jun 置信度 0.82
• Survey of real-time brainmedia in artistic exploration.
  This survey examines the evolution and impact of real-time brainmedia on artistic exploration, contextualizing developments within a historical framework. To enhance knowledge on the entanglement between the brain, mind, and body in an increasingly mediated wo…
  pubmed Lin RR, Zhang K 2024 Nov 18 置信度 0.82
• Intermodulation frequency components in steady-state visual evoked potentials: Generation, characteristics and applications.
  The steady-state visual evoked potentials (SSVEPs), evoked by dual-frequency or multi-frequency stimulation, likely contains intermodulation frequency components (IMs). Visual IMs are products of nonlinear integration of neural signals and can be evoked by var…
  pubmed Chen Y, Bai J, Shi N, Jiang Y 等 2024 Dec 1 置信度 0.82
• Enhanced cross-dataset electroencephalogram-based emotion recognition using unsupervised domain adaptation.
  Emotion recognition holds great promise in healthcare and in the development of affect-sensitive systems such as brain-computer interfaces (BCIs). However, the high cost of labeled data and significant differences in electroencephalogram (EEG) signals among in…
  pubmed Imtiaz MN, Khan N 2025 Jan 置信度 0.82
• Interactive mining of neural pathways to preoperative neurosurgical planning.
  Preoperative understanding of white matter anatomy, including its spatial relationship with pathology and superficial landmarks, is vital for effective surgical planning. The ability to interactively synthesize neural pathways from diffusion data and dynamical…
  pubmed Wu ST, Voltoline R, Benites RL, de Campos BM 等 2025 Jan 置信度 0.82
• TSOM: Small object motion detection neural network inspired by avian visual circuit.
  Detecting small moving objects in complex backgrounds from an overhead perspective is a highly challenging task for machine vision systems. As an inspiration from nature, the avian visual system is capable of processing motion information in various complex ae…
  pubmed Hu P, Zhang X, Li M, Zhu Y 等 2025 Feb 置信度 0.82
• A protocol for trustworthy EEG decoding with neural networks.
  Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their high performance, existing solutions do not fully address the challenge posed by the introduction of many hyperp…
  pubmed Borra D, Magosso E, Ravanelli M 2025 Feb 置信度 0.82
• Partial prior transfer learning based on self-attention CNN for EEG decoding in stroke patients.
  The utilization of motor imagery-based brain-computer interfaces (MI-BCI) has been shown to assist stroke patients activate motor regions in the brain. In particular, the brain regions activated by unilateral upper limb multi-task are more extensive, which is …
  pubmed Ma J, Ma W, Zhang J, Li Y 等 2024 Nov 15 置信度 0.82
• Dynamic changes in the structure and function of brain mural cells around chronically implanted microelectrodes.
  Integration of neural interfaces with minimal tissue disruption in the brain is ideal to develop robust tools that can address essential neuroscience questions and combat neurological disorders. However, implantation of intracortical devices provokes severe ti…
  pubmed Wellman SM, Forrest AM, Douglas MM, Subbaraman A 等 2025 Apr 置信度 0.82
• Decoding Continuous Tracking Eye Movements from Cortical Spiking Activity.
  Eye movements are the primary way primates interact with the world. Understanding how the brain controls the eyes is therefore crucial for improving human health and designing visual rehabilitation devices. However, brain activity is challenging to decipher. H…
  pubmed Noneman KK, Patrick Mayo J 2025 Jan 置信度 0.82
• Bridging Three Years of Insights: Examining the Association Between Depression and Gallstone Disease.
  Despite sharing common pathophysiological risk factors, the relationship between gallstones and depression requires further evidence for a clearer understanding. This study combines the National Health and Nutrition Examination Survey 2017 - 2020 observational…
  pubmed Wang HZ, Saeed S, Zhang JY, Hu SH 2024 Oct 置信度 0.82
• Using data from cue presentations results in grossly overestimating semantic BCI performance.
  Neuroimaging studies have reported the possibility of semantic neural decoding to identify specific semantic concepts from neural activity. This offers promise for brain-computer interfaces (BCIs) for communication. However, translating these findings into a B…
  pubmed Rybář M, Poli R, Daly I 2024 Nov 14 置信度 0.82
• Controlling Virtual Reality With Brain Signals: State of the Art of Using VR-Based Feedback in Neurofeedback Applications.
  The rapid progress of commercial virtual reality (VR) technology, open access to VR development software as well as open-source instructions for creating brain-VR interfaces have increased the number of VR-based neurofeedback (NF) training studies. Controlling…
  pubmed Kober SE, Wood G, Berger LM 2025 Dec 置信度 0.82
• Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.
  Background Although the application of brain-computer interface (BCI) technology in rehabilitation has been extensively studied, a systematic and comprehensive bibliometric analysis of this area remains lacking. Thus, this study aims to analyze the research pr…
  pubmed Liu M, Fang M, Jin S, Liu B 等 2024 置信度 0.82 RehabilitationInterface (matter)Brain–computer interfaceComputer scienceData science
• Factors influencing the social acceptance of brain-computer interface technology among Chinese general public: an exploratory study.
  This study investigates the impact of social factors on public acceptance of brain-computer interface (BCI) technology within China's general population. As BCI emerges as a pivotal advancement in artificial intelligence and a cornerstone of Industry 5.0, unde…
  pubmed Xia R, Yang S, RuiTong Xia, Shusheng Yang 2024 置信度 0.82 Exploratory researchPsychologyInterface (matter)Technology acceptance modelBrain–computer interface
• A subjective and objective fusion visual fatigue assessment system for different hardware and software parameters in SSVEP-based BCI applications.
  With the development of brain-computer interface industry, large amounts of related applications have entered people's vision. BCI applications based on steady-state visual evoked potentials (SSVEP) are widely used because they do not require pre-training and …
  pubmed Tian P, Xu G, Han C, Du C 等 2024 Nov 13 置信度 0.82
• Localizing the seizure onset zone and predicting the surgery outcomes in patients with drug-resistant epilepsy: A new approach based on the causal network.
  Accurate localization of the seizure onset zone (SOZ) is crucial for surgical treatment in patients with drug-resistant epilepsy (DRE). However, clinical identification of SOZ often relies on physician experience and has a certain subjectivity. Therefore, it i…
  pubmed Chen M, Guo K, Lu K, Meng K 等 2025 Jan 置信度 0.82
• Tensor decomposition-based channel selection for motor imagery-based brain-computer interfaces.
  The number of electrode channels in a brain-computer interface (BCI) affects not only its classification performance, but also its convenience in practical applications. Despite many studies on channel selection in motor imagery (MI)-based BCI systems, they co…
  pubmed Huang Z, Wei Q 2024 Jun 置信度 0.82
• An Asynchronous Training-Free SSVEP-BCI Detection Algorithm for Non-Equal Prior Probability Scenarios.
  SSVEP-based brain-computer interface (BCI) systems have received a lot of attention due to their relatively high Signal to Noise Ratio (SNR) and less training requirements. Most of the existing steady-state visual evoked potential (SSVEP) detection algorithms …
  pubmed Wang J, Cui Y, Zhang H, Wu H 等 2024 置信度 0.82
• Local field potential-based brain-machine interface to inhibit epileptic seizures by spinal cord electrical stimulation.
  Objective. This study proposes a closed-loop brain-machine interface (BMI) based on spinal cord stimulation to inhibit epileptic seizures, applying a semi-supervised machine learning approach that learns from Local Field Potential (LFP) patterns acquired on th…
  pubmed Garcia Cerqueira EM, de Medeiros RE, da Silva Fiorin F, de Arújo E Silva M 等 2024 Nov 25 置信度 0.82
• Endocisternal interfaces for minimally invasive neural stimulation and recording of the brain and spinal cord.
  Minimally invasive neural interfaces can be used to diagnose, manage and treat many disorders, with reduced risks of surgical complications. However, endovascular probes lack access to key cortical, subcortical and spinal targets, and are not typically explant…
  pubmed Chen JC, Dhuliyawalla A, Garcia R, Robledo A 等 2025 Jun 置信度 0.82
• Author Correction: A novel interface for cortical columnar neuromodulation with multipoint infrared neural stimulation.
  pubmed Tian F, Zhang Y, Schriver KE, Hu JM 等 2024 Nov 11 置信度 0.82
• An open-source user interface for real-time ultra-fast solving of electric fields around segmented deep brain stimulation electrodes.
  pubmed Henry KR, Ingersoll M, Wartman W, Jiang F 等 2024 Nov-Dec 置信度 0.82
• Steady-State Visual Evoked Potential-Based Brain-Computer Interface System for Enhanced Human Activity Monitoring and Assessment.
  Advances in brain-computer interfaces (BCIs) have enabled direct and functional connections between human brains and computing systems. Recent developments in artificial intelligence have also significantly improved the ability to detect brain activity pattern…
  pubmed Chen Y, Shi X, De Silva V, Dogan S 等 2024 Nov 3 置信度 0.82 Brain–computer interfaceElectroencephalographyComputer scienceInterface (matter)Brain activity and meditation
• A Cross-Attention-Based Class Alignment Network for Cross-Subject EEG Classification in a Heterogeneous Space.
  Domain adaptation (DA) techniques have emerged as a pivotal strategy in addressing the challenges of cross-subject classification. However, traditional DA methods are inherently limited by the assumption of a homogeneous space, requiring that the source and ta…
  pubmed Ma S, Zhang D 2024 Nov 3 置信度 0.82
• Study of the Brain Functional Connectivity Processes During Multi-Movement States of the Lower Limbs.
  Studies using source localization results have shown that cortical involvement increased in treadmill walking with brain-computer interface (BCI) control. However, the reorganization of cortical functional connectivity in treadmill walking with BCI control is …
  pubmed Wei P, Chen T, Zhang J, Li J 等 2024 Oct 31 置信度 0.82
• Comparison of Subdural and Intracortical Recordings of Somatosensory Evoked Responses.
  Micro-electrocorticography (µECoG) electrodes have emerged to balance the trade-off between invasiveness and signal quality in brain recordings. However, its large-scale applicability is still hindered by a lack of comparative studies assessing the relati…
  pubmed Rettore Andreis F, Meijs S, Nielsen TGNDS, Janjua TAM 等 2024 Oct 25 置信度 0.82