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• Symbiotic brain-machine drawing via visual brain-computer interfaces.
  Brain-computer interfaces (BCIs) are evolving from research prototypes into clinical, assistive, and performance enhancement technologies. Despite the rapid rise and promise of implantable technologies, there is a need for better and more capable wearable and …
  pubmed Wang G, Huang Y, Muckli L, Faccio D 2026 May 4 置信度 0.82
• A Closed-Loop ta-VNS System Synchronized with BCI-Based Motor Training for Post-Stroke Upper Limb Rehabilitation.
  Transcutaneous auricular vagus nerve stimulation (ta-VNS) involves applying electrical stimulation via electrodes to the auricular concha. This activates vagal afferent fibers, initiating an ascending pathway from the periphery to the brainstem, which ultimate…
  pubmed Zhong M, Jiang Y, Huang S, Chen P 等 2026 Apr 14 置信度 0.82
• Application of Graphene Dry Electrode in 512-Lead EEG Cap and Real-Time Monitoring EEG System.
  Dry electroencephalography (EEG) electrodes with low noise and minimal potential drift are crucial for daily wearable and high-density noninvasive brain-computer interfaces. In this study, a Na-doped vertical graphene dry electrode with a diameter of 2.8 mm wa…
  pubmed Liu J, Yang X, Li M, Zheng C 等 2026 置信度 0.82
• A Multi-perception fusion using shared-control method for brain-mobile robot.
  For human-robot collaboration, brain-computer interface is promising to express human perception to improve the adaptability of human-robot collaboration in complex environments. In this study, a multi-perception fusion using shared control method (MPF-SC) is …
  pubmed Wang C, Li M, Zhang P, Zhang Z 等 2026 May 置信度 0.82
• SSA-DCNet: a cross-session MI-EEG classification network based on deformable convolution and spatial-shift attention.
  Brain-computer interfaces (BCIs) based on motor imagery (MI) electroencephalogram (EEG) signals have shown tremendous potential in neurorehabilitation due to their non-invasive acquisition and ease of use. However, the cross-session nature of EEG signals-where…
  pubmed Du X, Wang H, Xi M, Qiu S 等 2026 May 置信度 0.82
• Design and Performance Evaluation of a Low-Cost High-SNR EOG Sensing System for Arabic Locked-In Syndrome Communication.
  Locked-in Syndrome (LIS) is a neurological condition in which individuals remain conscious but experience complete paralysis of voluntary muscles, except for eye movements-highlighting the need for reliable assistive communication technologies. This study pres…
  pubmed Alzahrani SI, Alomari N, Alkilani S, Alghamdi L 等 2026 Apr 15 置信度 0.82
• ATF3/SLC31A1-Mediated Cuproptosis Contributes to Bortezomib-Induced Peripheral Neurotoxicity and Intervention by (-)-Epigallocatechin Gallate.
  Bortezomib (BTZ), the first-generation proteasome inhibitor, has been approved for the treatment of relapsed, refractory, and newly diagnosed multiple myeloma. Despite its remarkable antitumor efficacy, BTZ treatment is severely limited by a high incidence of …
  pubmed Wang Y, Lu J, Feng X, Yang B 等 2026 Apr 21 置信度 0.82
• Foreign Body Response to Neuroimplantation: Machine Learning-Assisted Quantitative Analysis of Astrogliosis.
  Neuroimplants represent an emerging medical technology, offering new therapeutic approaches for severe neurological and psychiatric disorders. One of the key limitations to long-term neuroimplant performance is the foreign body response elicited by intracortic…
  pubmed Melnikova AA, Egorchev AA, Rosin AA, Nurullin LF 等 2026 Apr 15 置信度 0.82
• From patch-clamps to SPAD arrays-evolution and future perspectives of invasive neural interfacing toward integrated photonic implants.
  The investigation of neural circuit dynamics faces a fundamental challenge: existing tools cannot simultaneously achieve cellular resolution, millimeter-depth penetration, and compatibility with freely behaving subjects. Electrophysiology offers temporal preci…
  pubmed Qian X, Liu C, Zhang Y, Subramaniam S 等 2026 置信度 0.82
• Unified Online Adaptation Framework for Correlation Analysis-based Spatial Filtering Methods in SSVEP-based BCIs.
  Online adaptation is a promising technique for achieving calibration-free recognition in user-friendly brain-computer interfaces (BCIs) but remains underexplored for steady-state visual evoked potential (SSVEP) recognition. In our previous work on online multi…
  pubmed Wang Z, Shen L, Mi X, Cheng L 等 2026 May 1 置信度 0.82
• Deficient chaperone-mediated autophagy drives multiorgan fibrogenesis via SMAD2/4 stabilization to sustain TGFβ-SMAD signaling.
  Fibrotic diseases, driven by excessive extracellular matrix deposition, account for substantial global morbidity and mortality, yet effective therapies remain elusive. Emerging evidence highlights impaired protein homeostasis as a key contributor to fibrosis, …
  pubmed Jin JY, Song YX, Lu JB, Li GQ 等 2026 Sep 置信度 0.82
• A novel 3D region-based speller paradigm for BCI systems.
  This study proposes and evaluates a novel three-dimensional region-based (3D-RB) speller paradigm designed to enhance classification performance. EEG data were recorded from 15 participants using 32 channels. Classification accuracy was examined across both si…
  pubmed Turay T 2026 Apr 30 置信度 0.82
• Distinct frontal lobe subregions mediate the emergence and reporting of visual consciousness.
  Persistent debate surrounds whether the frontal lobe supports the emergence or reporting of consciousness, raising the hypothesis that distinct frontal subregions may support these processes. We addressed this by combining electroencephalography (EEG) with eye…
  pubmed Zhang Y, Li X, Jin Z, Zhang J 等 2026 置信度 0.82
• Homologous specialization of arcuate fasciculus ventrolateral frontal connectivity in marmosets and humans.
  The arcuate fasciculus (af) is a crucial dorsal pathway underpinning human language, yet its weak frontal connectivity in macaques-the standard primate model-creates an evolutionary puzzle. Here, we investigate the common marmoset, a distantly related platyrrh…
  pubmed Wang Y, Cheng L, Li D, Lu Y 等 2026 May 5 置信度 0.82
• Subject-Independent Deep Learning Framework for Motor Imagery Electroencephalogram Decoding in Neurorehabilitation.
  Motor imagery (MI) has emerged as a pivotal paradigm in non-invasive brain-computer interfaces (BCIs) for neurorehabilitation, enabling motor function restoration through mental rehearsal of movements. However, traditional MI electroencephalogram (EEG) classif…
  pubmed Lou X, Li X, Meng H, Li Z 2026 Apr 30 置信度 0.82
• Multi-source domain generalization with few-shot fine-tuning (MSDG-FT) for cross-dataset EEG mental workload classification.
  EEG-based mental workload (MWL) classifiers consistently achieve high within-dataset accuracy but collapse when applied across datasets recorded under different paradigms or hardware. This cross-domain generalisation gap limits real-world deployment of passive…
  pubmed G A, K D 2026 Jun 置信度 0.82
• Running virtual reality experiments online: A brief introduction and tutorial.
  Achieving meaningful and representative findings in cognitive/behavioural research requires both externally valid experimental settings and representative participant samples. Virtual reality (VR) has become a powerful tool for enhancing realism while maintain…
  pubmed Kumle L, Brazier A, Kovoor J, Keil J 等 2026 Apr 29 置信度 0.82
• Brain-Controlled Wheeled Mobile Robots: A Shared Control Framework Integrating Event-Triggered Mechanism and Deep Reinforcement Learning.
  This study addresses the problem of quantifying user control authority in brain-computer shared control by integrating Event-Triggered Control (ETC) with Deep Reinforcement Learning (DRL). Firstly, an ETC-based brain-computer shared-control framework is develo…
  pubmed Yu X, He X, Huang B, Li G 等 2026 置信度 0.82
• Recurrent Processing Dynamics in Occluded Object Recognition Revealed by Electroencephalography and Deep Neural Networks.
  The human visual system excels at recognizing occluded objects, yet the temporal dynamics of recurrent processing in this task remain unclear. Using high-temporal-resolution Electroencephalography (EEG), backward masking, and deep neural networks (DNNs), we em…
  pubmed Li R, Liu Z, Yan S, Zhang L 等 2026 Oct 置信度 0.82
• Longitudinal associations of cardiovascular-kidney-metabolic syndrome with midlife or late-life mental disorders and dementia, and the mediating role of metabolomic signature.
  Cardiovascular-Kidney-Metabolic (CKM) syndrome assesses the interconnections among metabolic, kidney, and cardiovascular diseases, rendering significant prognostic value for age-related chronic diseases and mortality. We aimed to investigate the effects of CKM…
  pubmed Zhao X, Lin Z, Zhang H, Zhang W 等 2026 Apr 28 置信度 0.82
• Low-power differencing feature extracts spiking-band activities for high-performance intracortical brain-computer interfaces.
  Intracortical brain-computer interfaces (iBCIs) demand computationally efficient feature extraction methods to process high-bandwidth neural signals in resource-constrained implantable systems. We present the mean absolute of n-th difference (MAND), a feature …
  pubmed Xu G, Yu C, Shao G, Pan G 等 2026 置信度 0.82
• An exceptionally conductive hydrogel for all-organic, ultraflexible, and chronic neural interfaces.
  Chronic neural interfaces are essential for advancing brain-computer interfaces, neuroprosthetics, and neuromodulation technologies. However, a long-standing trade-off between performance and longevity persists due to the scarcity of materials that simultaneou…
  pubmed Zhu R, Hu Z, Lou Z, Xie F 等 2026 May 5 置信度 0.82
• Sporadic Alzheimer's disease with bipolar-like features: a case report and a brief review of the current research status.
  Alzheimer's disease (AD) is among the main causes of cognitive impairment, memory loss, and dementia, particularly in old adults. It has been listed as one of the most expensive, lethal, and burdening diseases of the 21st century and develops with the process …
  pubmed Kong L, Yang Y, Zhou W, Hu S 2026 Apr 15 置信度 0.82
• The Spatiotemporal Structure of Neural Activity in Motor Cortex during Reaching.
  Intracortical brain-computer interfaces (BCIs) leverage knowledge about neural representations to translate movement-related neural activity into actions. BCI implants have targeted broad cortical regions known to have relevant motor representations, but emerg…
  pubmed Canfield RA, Ouchi T, Fang H, Macagno B 等 2026 May 20 置信度 0.82
• Stimulus Size Modulates Periodic and Aperiodic EEG Components in SSVEP-Based BCIs.
  Background/Objectives: Steady-State Visual Evoked Potential-based Brain-Computer Interfaces face a critical trade-off between system accuracy and user visual fatigue. To address this challenge, the objective of this study was to determine how the spatial manip…
  pubmed Padilla GL, Farfán FD 2026 Apr 18 置信度 0.82
• The Use of EEG in the Study of Emotional States and Visual Word Recognition with or Without Musical Stimulus in University Students with Dyslexia.
  This study investigated neural oscillatory dynamics underlying visual word recognition in university students with dyslexia using a portable brain-computer interface (BCI) EEG system. The sample included university students with dyslexia (N = 12) and matched c…
  pubmed Christodoulides P, Peschos D, Zakopoulou V 2026 Apr 6 置信度 0.82
• Deep Learning Decoding of Steady-State Visual Evoked Potential (SSVEP) for Real-Time Mobile Brain-Computer Interfaces: A Narrative Review from Laboratory Settings to Lightweight Engineering Applications.
  Background/Objectives : SSVEP-BCI has broad application potential in mobile human-computer interaction due to its high information transfer rate and stable signal characteristics. The introduction of deep learning technology has significantly advanced SSVEP de…
  pubmed Zhang H, Tao C 2026 Mar 31 置信度 0.82
• A Band-Aware Riemannian Network with Domain Adaptation for Motor Imagery EEG Signal Decoding.
  The decoding of motor imagery electroencephalography (MI-EEG) is constrained by core issues including low signal-to-noise ratio (SNR) and cross-session as well as cross-subject domain shift, which seriously impedes the practical deployment of brain-computer in…
  pubmed Wang Z, Ma Y, Du Y, She Q 2026 Mar 27 置信度 0.82
• Graph-Theoretical Signature from Neural and Vascular Signals Reveals Spinal Cord Stimulation Frequency-Specific Brain Network in Disorders of Consciousness Patients.
  Introdution: Spinal cord stimulation (SCS) has emerged as a promising neuromodulatory intervention for patients with disorders of consciousness (DoC). However, the identification of optimal stimulation frequencies remains a subject of ongoing debate. Although …
  pubmed Wang N, Chai X, He Y, Song J 等 2026 置信度 0.82
• MCFANet: a multi-class fusion attention network for motor imagery EEG classification.
  This paper proposes a Multi-Class Fusion Attention Network (MCFANet) that combines the multi-class spatial filtering outputs of FBCSP with the spatiotemporal feature extraction capability of convolutional neural networks for multi-class motor imagery EEG class…
  pubmed Zhao P, Liang T, Jia H, Dayan A 等 2026 置信度 0.82
• Neurofeedback in Major Depression.
  Emerging evidence highlights the significant interplay between mental health and brain health, underscoring the potential of non-pharmacological interventions for major depressive disorder. Brain-computer interfaces offer a promising avenue in psychiatry, adva…
  pubmed Tsai HJ, Tsai SJ 2026 置信度 0.82
• Discontinuous 3D Printing of Amorphous Photonic Crystal Hydrogels for Multifunctional Applications.
  Amorphous photonic crystals (APCs) offer angle-independent structural color for reliable sensing, yet their precise 3D fabrication remains challenging due to the tendency of particles to self-assemble into ordered structures. We develop a discontinuous digital…
  pubmed Ji YL, Yin B, Zhu G, Wang X 等 2026 Jun 置信度 0.82
• NeuroDecoder: A new framework for image decoding and reconstruction of EEG signals.
  Brain-Computer Interface (BCI) technology holds great promise for enhancing human health and quality of life, with visual stimulus reconstruction from EEG signals being a key application. However, the complexity and noise of EEG data challenge existing reconst…
  pubmed Ma W, Zhang H, Li Y, Wei M 2026 Apr 23 置信度 0.82
• From Bio-Interface Materials to Neural Integration: The Next-Generation Brain-Machine Interfaces Powered by Hydrogels.
  Brain-machine interfaces (BMIs), which serve as revolutionary tools for neural recording, modulation, and rehabilitation, are highly dependent on the biocompatibility and mechanical suitability of their electrode materials. Although traditional metal electrode…
  pubmed Li Z, Ge R, Zhao Z, Xiao H 等 2026 置信度 0.82
• On the prediction models for brain signal-based emotion recognition.
  This paper analyzes the factors contributing to the performance gap between subject-dependent and subject-independent EEG-based emotion recognition systems. With this key objective, the experiments are conducted in this work using two benchmark datasets; DEAP …
  pubmed Margaret MJ, Banu NMM, Madhumithaa S, Pathan AK 2026 Apr 22 置信度 0.82
• Resting-state EEG networks predict individual differences in cognitive flexibility.
  Cognitive flexibility, the ability to adapt behavior and switch between tasks in response to changing goals, is a core component of executive function. However, the multiscale resting-state mechanisms underlying individual differences remain poorly understood.…
  pubmed Xu P, Chen Y, Wei X, Qi J 等 2026 置信度 0.82
• An Optimized Encoding BCI Framework: Implementing Massive Command With Minimal Calibration.
  As a critical metric for brain-computer interfaces (BCIs), the number of commands directly defines the control capacity for practical applications. However, existing BCIs often suffer from limited command sets and prohibitive calibration costs. To address thes…
  pubmed Zhang S, Zhang H, Wei M, Yang C 2026 置信度 0.82
• RMETNet: A cross-subject motor imagery EEG signal classification model based on TSLANet and riemannian geometry features.
  Motor imagery electroencephalogram (MI-EEG) analysis is essential for natural interaction and autonomous control in brain-computer interfaces (BCIs). However, deep learning models often struggle with inter-subject variability, which limits their ability to gen…
  pubmed Zhao Y, He D, Ren F, Xia Q 等 2026 置信度 0.82
• Neural-LWE: a biometric-anchored authenticated key agreement for post-quantum brain-computer interfaces.
  The proliferation of Brain-Computer Interfaces (BCIs) and wireless Electroencephalography (EEG) devices necessitates security protocols that are simultaneously quantum-resistant and intrinsically linked to users’ biological identity. While standard post…
  pubmed Nasiraee H, Nazari F, Samsami-Khodadad F, Liu X 2026 Apr 21 置信度 0.82
• BR-SFDA: A Source-Target Bidirectional Refined SFDA for Privacy Preserving EEG-based BCIs.
  Due to significant inter-subject variability in feature distributions caused by the diversity of neural activity patterns, Electroencephalography (EEG)-based brain-computer interface (BCI) systems face considerable challenges in cross-subject EEG decoding. Tho…
  pubmed Zhang J, Liu J, Wang L, Peng Y 等 2026 Apr 21 置信度 0.82
• Enhancing Target Recognition Performance in SSVEP-Based Brain-Computer Interfaces via Deep Neural Networks With Pyramid Squeeze Attention.
  Steady state visual evoked potential (SSVEP)-based brain-computer interfaces have been widely studied for their fast response speeds and high information transfer rates. However, how to fully utilize the potential information of existing subjects to realize th…
  pubmed Wu X, Daly I, Lau AT, Chen W 等 2026 置信度 0.82
• From Selective Listening to Brain-Controlled Hearing: A Perspective on the Future of Auditory Technology.
  Understanding speech in noisy environments is a major challenge for millions, a problem that conventional hearing aids often exacerbate by amplifying all sounds indiscriminately. Auditory Attention Decoding (AAD) offers a revolutionary alternative: a brain-com…
  pubmed Mesgarani N 2026 置信度 0.82
• Enhancing the Performance of Event-Related Potential-Based Brain-Computer Interfaces Under Cognitive Distraction: A Multiwindow Adaptive Approach.
  Event-related potential (ERP)-based brain-- computer interfaces (BCIs) require focused attention to presented stimuli. However, their applications in real life frequently involve environments that demand multitasking and impose cognitive distraction. Such dist…
  pubmed Kim M, Heo D, Kim J, Kim SP 2026 置信度 0.82
• In Vivo Imaging With a Low-Cost MRI Scanner and Cloud Data Processing in Low-Resource Settings.
  The goal of this work is to demonstrate in vivo imaging with a low-cost, low-field MRI scanner built and operated in Africa and to show how systematic hardware and software improvements can mitigate the main operational limitations encountered in low-reso…
  pubmed Guallart-Naval T, Asiimwe R, Tusiime P, Nassejje MA 等 2026 Jun 置信度 0.82
• An intelligent EEG-based ensemble framework for communication assistance in Locked-In Syndrome patients.
  Locked-In Syndrome (LIS) is a neurological condition in which patients experience complete motor paralysis while preserving cognitive function, severely restricting their ability to communicate. Electroencephalography (EEG)-based brain–computer interfac…
  pubmed Selvam AK, Loganathan A 2026 置信度 0.82
• A systematic evaluation of EEG electrode geometry for enhanced signals: an experimental approach.
  The advancement of neural recording technologies is critical for improving our understanding of brain function and enhancing the efficacy of brain–computer-interfaces. Electroencephalography (EEG), is a non-invasive technique for recording brain electri…
  pubmed Razaghi Z, Faraji M, Mohammadpour R, Ebrahimpour R 等 2026 Apr 18 置信度 0.82
• High-Density EEG and Multi-Muscle EMG Dataset during Object Prehension with a sensorized Grasping Box in Humans.
  Understanding how cortical areas control prehension movements requires synchronized neural and muscular data. For this aim, we introduce a novel open-access dataset of synchronized EEG and EMG recordings during prehension movements. The dataset combines high-d…
  pubmed Lomele G, Lencioni T, D'Ambrosio S, Comanducci A 等 2026 Apr 18 置信度 0.82
• A midbrain circuit for high-fat-food induced conditioned taste aversion.
  Conditioned taste aversion (CTA) is a survival mechanism that prevents consumption of harmful foods. Yet its neural circuits, especially those for solid food aversion, are poorly understood. Using a male mouse model where high-fat food (HFF) was paired with Li…
  pubmed Zhan L, Wu X, Wang X, Xiao H 等 2026 Apr 18 置信度 0.82
• Advancing EEG-based assessment of consciousness and cognition in prolonged disorders of consciousness.
  Accurate assessment of residual awareness in patients with Prolonged Disorders of Consciousness (PDoC) remains a major clinical challenge, as conventional behavioural tools can underestimate covert cognition. This study evaluates whether a structured, multi-ph…
  pubmed du Bois N, Korik A, Hodge S, Hudson L 等 2026 Apr 17 置信度 0.82
• Adapting frozen foundation models for montage-agnostic high-resolution EEG event segmentation.
  Objective. Deploying brain-computer interfaces (BCIs) outside controlled laboratories requires detecting neural events in continuous electroencephalography (EEG) without relying on time-locked synchronization, while simultaneously generalizing across the diver…
  pubmed Ma J, Ruotsalo T 2026 May 26 置信度 0.82
• Progress in non-invasive neuromodulation based on consciousness-related neural circuits: a narrative review.
  Disorders of Consciousness (DOC) are characterized by abnormal function or disrupted connectivity of consciousness-related neural circuits, mainly presenting as Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) and Minimally Conscious State (MCS), wh…
  pubmed Wang Y, Zhai Y, Zheng Z, Wang N 等 2026 置信度 0.82
• The Compositional Encoding of Hand-Eye Coordinated Movements for Single Neurons in the Posterior Parietal Cortex.
  Human posterior parietal cortex (PPC) is thought to play an important role in hand-eye coordination, yet the underlying encoding mechanisms remain uncertain. We recorded 412 single neurons across 11 sessions from motor cortex (MC; n=251) and PPC (n=161) in a s…
  pubmed Mynhier NA, Gamez J, Pejsa K, Bari A 等 2026 Apr 7 置信度 0.82
• An Open Non-Invasive EEG Dataset for Spontaneous Auditory Attention Switch Decoding.
  Auditory brain-computer interfaces (BCIs) based on non-invasive electrodes offer significant potential for advancing the understanding of selective auditory attention mechanisms and enabling natural human-computer interaction. Despite growing interest in audit…
  pubmed Wang X, Ding Y, Ban Y, Wang L 等 2026 Apr 16 置信度 0.82
• Kalman phase transfer entropy (KTE-TP): a novel measure for information transfer measurement to enhance brain-computer decoding.
  Objective. To address the limitation that existing brain network analysis methods relying on relatively simplistic data processing models fail to capture the multimodal information embedded in neural signals, this study introduces a multidimensional informatio…
  pubmed Zhang J, Shi Z, Xu H, Rao Z 等 2026 Apr 30 置信度 0.82
• Measures of fatigue and performance are related to user interface and task in a communication BCI.
  Objective . This exploratory study compared two non-implantable communication brain-computer interfaces (cBCIs) to determine whether physiologic and self-report measures of mental fatigue, effort, and boredom were greater during calibration than during copy-sp…
  pubmed Klee D, Memmott T, Oken BS 2026 Apr 30 置信度 0.82
• Zero-Calibration MI Decoding via Self-Supervised Representation and Ensemble Learning.
  Motor Imagery (MI) is a core task in brain computer interface (BCI) research. Zero-calibration MI de coding, which eliminates the need for training subject specific models, significantly reduces data annotation and training time, thus attracting widespread att…
  pubmed Li Y, Su D, Wang X, Wei F 等 2026 Apr 16 置信度 0.82
• Encoding of speech modes and loudness in ventral precentral gyrus.
  The ability to vary the mode and loudness of speech is an important part of the expressive range of human vocal communication. However, the encoding of these behaviors in the ventral precentral gyrus (vPCG) has not been studied at the resolution of neuronal fi…
  pubmed Srinivasan A, Wairagkar M, Iacobacci C, Hou X 等 2026 Apr 15 置信度 0.82
• Transformative Technologies in Brain-Computer Interfaces-Innovations, Applications, and Challenges.
  pubmed Laureys S, Guger C, Meng J 2026 Feb 置信度 0.82
• Multi-scale EEG evidence for attention enhancement following long-term action video game training.
  Action video games (AVGs), characterized by a fast pace and high perceptual load, have been increasingly applied to probe cognitive enhancement and neural plasticity. While substantial behavioral evidence confirms that AVG training enhances various cognitive f…
  pubmed Wang J, Peng Y, Lv B, Yao D 2026 Jul 置信度 0.82
• Quantifying fractal and oscillatory components in neural signals for biomarker development.
  Neural activity encompasses both rhythmic oscillations and aperiodic background dynamics, reflecting complex brain function beyond traditional rhythm-centric views. The aperiodic component, once considered noise, is now recognised as a meaningful signal indica…
  pubmed Porcaro C, Bertoldo A 2026 Apr 30 置信度 0.82
• Rhythmic Motor Imagery Boosts Accuracy and Efficiency in Noninvasive Brain-Computer Interfaces.
  Decoding motor intentions from noninvasive brain recordings remains a longstanding challenge in neural engineering, particularly in advancing brain-computer interfaces (BCIs) for motor assistance and rehabilitation. The traditional motor imagery (MI) paradigm …
  pubmed Wei Y, Luo R, Xia Y, Mai X 等 2026 Apr 15 置信度 0.82
• Multidimensional visual feature encoding and functional organization in the pigeon entopallium.
  Understanding how birds perceive and recognize visual objects remains a fundamental question in neuroscience. The entopallium, a key node in the avian tectofugal pathway, has long been implicated in complex visual processing, yet its internal functional archit…
  pubmed Zhu JC, Zhu MJ, He QZ, Wu P 等 2026 Mar 18 置信度 0.82
• An Artificial Dopamine-Ionic Cascade Synapse for Adaptive Neuromorphic Attention.
  Biological intelligence operates through chemo-ionic signal processing, where neurotransmitters encode information as spatiotemporal chemical gradients that regulate ionic dynamics across neural synapses. Given the diversity of chemical neurotransmitters and i…
  pubmed Zhang H, Xiang Y, Zhang X, Zhang L 等 2026 May 置信度 0.82
• Rational design of G(i)-biased CB1 agonist with reduced side effects.
  The cannabinoid receptor 1 (CB1) has emerged as a promising candidate for next-generation non-opioid therapies. However, the development of therapeutics targeting CB1 has been consistently hindered by significant adverse effects. Here, through structure-activi…
  pubmed Liao YY, Che J, Gao YT, Xue J 等 2026 May 28 置信度 0.82
• PR(2)DM: Position-aware robust reconstruction with diffusion model for emotion recognition From EEG.
  Emotion recognition is significant in domains like smart education, mental health assistance, and brain-computer interface. Electroencephalography-based emotion recognition methods provide an objective approach to evaluating emotional states by analyzing the b…
  pubmed Xu W, Lin Y, Wang X, Liu J 等 2026 Jul 置信度 0.82
• A Hybrid Covert Attention-Augmented Motor Imagery Paradigm for Brain-Computer Interfaces.
  Motor imagery (MI) is widely used in brain-computer interfaces (BCIs) and has been applied in neurorehabilitation to support motor recovery in stroke patients. Although numerous decoding algorithms have been developed and achieve comparable performance, their …
  pubmed Cao B, Guo Y, Tian Y, Cao F 等 2026 置信度 0.82
• MBGFF Model for EEG-Text Generation Under Multi-Task Parallel Imagination.
  Brain-computer interface (BCI)-based text generation provides a promising communication pathway for individuals with severe motor or speech impairments. However, most existing EEG-based text generation studies rely on a single imagery modality, which limits in…
  pubmed Pan H, Teng B, Li Z, Li L 等 2026 Apr 13 置信度 0.82
• E2T: EEG-to-Trajectory Transformer for Motor Imagery-Based Fully-DoF Motion Prediction.
  Brain-computer interfaces (BCIs) using electroencephalography (EEG) enable non-invasive, real-time interaction for individuals with motor impairments by decoding neural signals associated with movement intention. Although traditional classification-based motor…
  pubmed Kwon BH, Jeong JH, Lee SW 2026 置信度 0.82
• Feedback-Related Dynamics of Hierarchical Error Processing in Goal-Directed Action.
  The performance monitoring system is essential for adaptive behavior and the development of brain-machine interfaces that utilize neural feedback signals. The posterior medial frontal cortex generates different error-related potentials (ErrP), including error-…
  pubmed Kroflic N, Kunavar T, Pauw K, Babic J 2026 置信度 0.82
• Domain generalized feature embedded learning for calibration-free event-related potentials recognition.
  Event-related potentials (ERPs) play an important role for building EEG-based brain computer interfaces (BCIs). However, due to the complex and varied spatio-temporal characteristics of ERPs across subjects, data distribution across subjects a very important i…
  pubmed Luo TJ 2026 Dec 置信度 0.82
• Electroencephalogram-based multimodal attention level classification using deep learning techniques.
  This study aims to develop a novel attention level prediction method using a multimodal brain-computer interface system that integrates electroencephalogram (EEG), electrocardiogram (ECG), and electrooculogram (EOG) signals to enhance prediction accuracy and r…
  pubmed Zhong Y, Wang Z, Zhao X, Xu T 等 2026 置信度 0.82
• Exploring the anti-diabetic potential of peimisine through bioinformatics analysis and in vitro studies.
  Fritillariae Cirrhosae Bulbus is a traditional herb with diverse activities, yet its active metabolites against type 2 diabetes (T2D) remain unclear.
  pubmed Feng X, Jin J, Ye X, Wu J 等 2026 置信度 0.82
• SSVEP-driven BCI authentication with reduced number of EEG electrodes across high and low frequency ranges.
  Growing concerns over data privacy, credential theft, and spoofing attacks have highlighted the limitations of traditional authentication methods in high-security settings. To address these challenges, we propose a steady-state visual evoked potential (SSVEP)-…
  pubmed Kiser A, Cantürk A, Volosyak I 2026 置信度 0.82
• Render EEG-Based Brain-Computer Interfaces Calibration-Free: Trade Space for Time in EEG Decoding.
  Goal: Electroencephalogram-based brain-computer interfaces (EEG BCIs) have broad applications in neurorehabilitation, clinical assessment, and assistive technologies. However, their practical deployment is severely limited by subject-specific calibration, whic…
  pubmed Liu M, Wang S, Cui W, Zhang S 等 2026 置信度 0.82
• Brain-computer interfaces based on intracortical recordings of neural activity for restoration of movement and communication of people with paralysis
  Paralysis has a severe impact on a patient's quality of life and entails a high emotional burden and life-long social and financial costs (`One Degree of Separation, Paralysis and Spinal Cord Injury in the United States' 2009; “Towards concerted efforts for tr…
  crossref Tomislav Milekovic 2018-03-12T17:53:47Z 置信度 0.70
• Application of Brain-Computer Interface Technology in Intelligent Bionic Neuroprosthetics
  crossref Szczepan Paszkiel 2022-07-08T16:08:06Z 置信度 0.70
• Confidence-Aware Neural Decoding of Overt Speech from EEG: Toward Robust Brain–Computer Interfaces
  crossref Soowon Kim, Byung-Kwan Ko, Seo-Hyun Lee 2026-03-19T20:04:24Z 置信度 0.70
• Data Augmentation for P300-based Brain-Computer Interfaces Using Generative Adversarial Networks
  A notable problem in Brain-Computer Interface (BCI) is the burden of collecting an adequate amount of training data to be used in estimating a robust classifier model. This study explores the prospect of using Generative Adversarial Networks (GANs), a novel fa…
  crossref Kassymzhomart Kunanbayev, Berdakh Abibullaev, Amin Zollanvari 2021-05-17T22:58:03Z 置信度 0.70
• Towards Successful Multi-user Brain-Computer Interface (BCI) Gaming: Analysis of the EEG Signatures and Connectivity
  The information related to the impact of multi-user BCI on cortical activity is still relatively limited. This ongoing study performed a competitive multi-user BCI gaming that is based on alpha band operant conditioning and explored the brain activity and conn…
  crossref Finda Putri, Hao Ding, Abdullah Garcia, Aleksandra Vuckovic 2019-10-02T09:03:48Z 置信度 0.70
• Subject-Independent Brain-Computer Interfaces with Open-Set Subject Recognition
  A brain-computer interface (BCI) can’t be effectively used since electroencephalography (EEG) varies between and within subjects. BCI systems require calibration steps to adjust the model to subject-specific data. It is widely acknowledged that this is a major…
  crossref Dong-Kyun Han, Geun-Deok Jang, Dong-Young Kim 2023-03-28T18:11:47Z 置信度 0.70
• Towards a whole body brain-machine interface system for decoding expressive movement intent Challenges and Opportunities
  The restoration and rehabilitation of human bipedal locomotion represent major goals for brain machine interfaces (BMIs), i.e., devices that translate neural activity into motor commands to control wearable robots to enable locomotive and non-locomotive tasks …
  crossref Jose L Contreras-Vidal, Jesus Cruz-Garcia, Anastasiya Kopteva 2017-02-20T16:35:38Z 置信度 0.70
• Towards robust machine learning methods for the analysis of brain data
  In this short abstract I will discuss recent directions that machine learning and BCI efforts of the BBCI team and coworkers have taken. It is the nature of this short text that many pointers to research are given all of which show a high overlap to prior own …
  crossref K.-R Muller 2018-03-12T21:53:47Z 置信度 0.70
• Hybrid Brain-Computer Interface Systems: Approaches, Features, and Trends
  Brain-computer interface (BCI) is an emerging field, and an increasing number of BCI research projects are being carried globally to interface computer with human using EEG for useful operations in both healthy and locked persons. Although several methods have…
  crossref Bijay Guragain, Ali Haider, Reza Fazel-Rezai 2018-10-17T06:48:31Z 置信度 0.70
• Enhanced EEG Signal Analysis for Brain Computer Interface Using Deep Learning Models
  The Brain-Computer Interface (BCI) systems involve direct human brain communication with other devices by deciphering the neural activity pattern.Electroencephalography (EEG) is very popular among other methods used in neuroimaging because of its non-invasiven…
  crossref M Ganga 2026-02-28T16:56:58Z 置信度 0.70
• Oscitancy tracking using Brain-Computer Interface
  Brain-Computer Interface (BCI) system is an advanced and emerging system in the field of computer applications. Every day road accidents are at an increase due to drunken driving and sleepiness. This paper proposes an EEG based BCI system to sense the Oscitanc…
  crossref S. Venkatesa Karthick Kumar, Anitha Julian 2012-04-25T16:53:53Z 置信度 0.70
• Subject Combination and Electrode Selection in Cooperative Brain-Computer Interface Based on Event Related Potentials
  New paradigms are required in Brain-Computer Interface (BCI) systems for the needs and expectations of healthy people. To solve this issue, we explore the emerging field of cooperative BCIs, which involves several users in a single BCI system. Contrary to clas…
  crossref Hubert Cecotti, Bertrand Rivet 2014-04-30T13:16:54Z 置信度 0.70
• Research on Brain-Computer Interface System Based on DSP and Zigbee
  The brain-computer interface (BCI) system creates a new communication channel between the computer and the brain, which can be used to exchange information between the human brain and the external environment or control peripheral equipments.And it is dependen…
  crossref 2019-10-18T07:21:55Z 置信度 0.70
• Visual rehabilitation strategies based on brain computer interface
  Vision is the most important sensory organ of human and visual impairment might significantly reduce the quality of human life. There are several methods that can be used to restore human visual system such as surgery, artificial retina and so on. Among which,…
  crossref Rui Xu 2022-10-07T20:31:23Z 置信度 0.70
• BCIO: Brain Computer Interface Ontology
  Brain Computer Interface (BCI) enable paralyze peoples to interact and control their environment by defining the direct communication between human feelings (brain) and technological aspects (external device).The feature extraction and translation of commands …
  crossref Muhammad Siddiq, Sheikh Kashif Raffat, Farhan Shafiq 2012-04-03T06:02:48Z 置信度 0.70
• Erratum to: Electroencephalography (EEG)-based neurofeedback training for brain–computer interface (BCI)
  crossref Kyuwan Choi 2014-02-11T11:07:28Z 置信度 0.70
• Application of Thermo-sensor in Brain-computer Interface
  The high precise thermo-sensors are introduced to the brain-computer interface for data acquirement. The structures, parameters and properties of most recent thermo-sensors are presented in detail. The suitable signal acquisition system is also discussed in th…
  crossref Ming-xiang GUI, Jing HUANG 2019-03-28T19:40:42Z 置信度 0.70
• Brain-Computer Interface Research
  crossref 2015-12-12T09:23:46Z 置信度 0.70
• Brain-Computer Interface
  You have accessThe ASHA LeaderFeature1 Sep 2007Brain-Computer Interface Yael Arbel Yael Arbel Google Scholar https://doi.org/10.1044/leader.FTR5.12122007.14 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In A brain-computer interface (BCI) is a…
  crossref Yael Arbel 2018-03-22T16:40:17Z 置信度 0.70
• Decision letter for "Standardization of protocol design for user training in EEG-based Brain-Computer Interface"
  crossref 2020-11-21T16:00:30Z 置信度 0.70
• The Developments of Text Entry and Recognition Using Brain-Computer Interfaces
  crossref Szymon Kaszura 2021-03-29T04:02:31Z 置信度 0.70
• Towards non-invasive brain-computer interface for hand/arm control in users with spinal cord injury
  Spinal cord injury (SCI) can disrupt the communication pathways between the brain and the rest of the body, restricting the ability to perform volitional movements. Neuroprostheses or robotic arms can enable individuals with SCI to move independently, improvin…
  crossref Gernot R. Muller-Putz, Joana Pereira, Patrick Ofner, Andreas Schwarz 等 2018-03-12T17:53:47Z 置信度 0.70
• Peer Review #2 of "Discriminating three motor imagery states of the same joint for brain-computer interface (v0.2)"
  The classification of electroencephalography (EEG) induced by the same joint is one of the major challenges for brain-computer interface (BCI) systems.In this paper, we propose a new framework, which includes two parts, feature extraction and classification.Ba…
  crossref 2021-08-29T02:31:48Z 置信度 0.70
• Fundamentals of EEG Signals
  crossref Narayan Panigrahi, Saraju P. Mohanty 2022-05-27T14:39:05Z 置信度 0.70
• Human 2.0 – Legal Implications of Brain-Computer Interface Technology
  Stellen Sie sich vor, Sie könnten durch reine Gedankenkraft Geräte steuern – das ist mit Blick auf die aktuellen Entwicklungen von Brain-Computer Interfaces (BCI) keine Zukunftsmusik mehr. Je weiter die Entwicklung von BCI-Technologie voranschreitet und zu mar…
  crossref Anne-Sophie Morand, Christine Schweikard 2023-06-12T23:00:55Z 置信度 0.70
• Usability of Transient VEPs in BCIs
  Among non-invasive Brain Computer Interfaces (BCIs), electroencephalogram (EEG) has been the most commonly used for them because EEG is advantageous in terms of its simplicity and ease of use, which meets BCI specifications when considering practical use. In g…
  crossref Natsue Yoshimura, Naoaki Itakur 2012-03-29T04:24:04Z 置信度 0.70