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• To move without moving: a perspective article on motor imagery.
  pubmed Duarte-Mendes P, Ramalho A, Bertollo M, Neiva HP 等 2025 置信度 0.82
• A heart rate variability-driven framework for depression screening leveraging emotion-elicited autonomic divergence.
  pubmed Zhu Z, Wang X, Xu Y, Chen W 等 2025 Dec 24 置信度 0.82
• Diffusion along perivascular spaces as a marker for Glymphatic system impairment in spinocerebellar Ataxia type 3.
  pubmed Xia XY, Huang ZQ, Lin HH, Liu ZY 等 2026 Jan 置信度 0.82
• Multicomponent interventions and technologies to reduce the burden of frailty, functional, and cognitive decline: insights from the Age-It Research Program.
  pubmed Okoye C, Cuffaro L, Pozzi FE, Ferrara MC 等 2025 Dec 1 置信度 0.82
• Structure basis for the activation of KCNQ2 by endogenous and exogenous ligands.
  pubmed Zhao Y, Yang Z, Shi S, Hao H 等 2026 Jan 27 置信度 0.82
• Reliable AI Platform for Monitoring BCI Caused Brain Injury and Providing Real-Time Protection.
  pubmed He C, Ding Y, Rabczuk T, Ding C 2026 Feb 置信度 0.82
• User-centred usability of a virtual reality tool for assessing instrumental activities of daily living in children and adolescents with ADHD.
  pubmed Romero-Ayuso D, Vidal-Ramírez C, Pérez-Rodríguez S, Del Pino-González A 等 2026 Jul 置信度 0.82
• Brain Implants in the Age of Artificial Intelligence.
  pubmed Kundu B, Pleitez J 2025 Nov-Dec 置信度 0.82
• GPR30 in spinal cholecystokinin-positive neurons modulates neuropathic pain.
  pubmed Chen Q, Wu H, Xie S, Zhu F 等 2025 Dec 23 置信度 0.82
• A wireless, 60-channel, AI-enabled neurostimulation platform.
  pubmed Rizzuto DS, Herrema HG, Hu Z, Utin D 等 2026 Jan-Feb 置信度 0.82
• Exploring the n-back task: insights, applications, and future directions.
  pubmed Huang S, Chen C, Mo Y, Zhao Y 等 2025 置信度 0.82
• Open-access fNIRS dataset for motor imagery of lower-limb knee and ankle joint tasks.
  pubmed Khan H, Nazeer H, Minhas HS, Naseer N 等 2025 置信度 0.82
• Object-centric proto-symbolic behavioural reasoning from pixels.
  pubmed van Bergen R, Hübotter J, Lago A, Lanillos P 2026 May 置信度 0.82
• A multi-scale deep CNN based on attention mechanism for EEG emotion recognition.
  pubmed Zhou Y, Jiang R, Zhang J 2026 Mar 置信度 0.82
• Gray matter volume predicts decision speed and reveals stage-specific contributions of large-scale brain networks in gambling tasks.
  pubmed Zhang T, Zhang Q, Xiong R, Zhang J 等 2026 Jan 置信度 0.82
• Sensorimotor event-related desynchronization and hemodynamic responses during motor and tactile imagery.
  pubmed Yakovlev L, Miroshnikov A, Syrov N, Berkmush-Antipova A 等 2025 Dec 19 置信度 0.82
• Genetic and Clinical Characteristics of Chinese Adult Patients With Krabbe Disease.
  pubmed Zhang Y, Huang HF, Xie JJ, Ni W 等 2025 Dec 置信度 0.82
• The relationship between heart rate variability and baseline state anxiety during stress and recovery.
  pubmed Xu Y, Wei Y, Xu M, Zhou H 等 2025 Dec 18 置信度 0.82
• Classification of EEG-fNIRS bimodal brain signals for motor imagery tasks based on wavelet transform and spatio-temporal domain processing.
  pubmed Zhang L, Li B, Cao M, Peng C 等 2026 Feb 6 置信度 0.82
• Early-Onset Parkinson's Disease: Unique Features and Management Approaches.
  pubmed Hickman J, Tsai A, Fullard M, Korsmo M 等 2025 Dec 18 置信度 0.82
• Decoding preparatory movement state-based motor imagery with multi layer energy decoder.
  pubmed Zhang Y, Li M, Guo M, Xu G 等 2025 Dec 17 置信度 0.82
• Structure-Property Modulation in Pyrolytic Photoresist Films Enabled Size-Dependent Electrochemical Performance of Neural Interfaces.
  pubmed Wang J, Liu H, Wu W, Hu X 等 2025 Dec 31 置信度 0.82
• Exploring the Potential of SSVER-BCI Based on Contactless Measurement Using Optically Pumped Magnetometers.
  pubmed Wang F, Cao F, Gao J, An N 等 2025 Dec 16 置信度 0.82
• Microbubble-enhanced ultrasound stimulation of β-cells improves insulin release and glycemic control in mice.
  pubmed Wu Y, Zhao X, Jiang Y, Chen C 等 2025 Dec 16 置信度 0.82
• Therapeutic targeting of YOD1 disrupts the PAX-FOXO1/N-Myc feedback loop in rhabdomyosarcoma.
  pubmed Ying W, Yu J, Wang X, Liu J 等 2026 Feb 9 置信度 0.82
• A novel method for EEG-based motor imagery classification using feature fusion.
  pubmed Chen Y, Ge H, Deng C 2025 Dec 15 置信度 0.82
• Enhancing Soldiers for Future Warfare: Good Science; Bad Ethics?
  pubmed Evans NG, L Gross M, Shandler R 2025 Dec 15 置信度 0.82
• Lysergic acid diethylamide-derived excitatory/inhibitory ratio change enhances global synchrony in functional brain dynamics.
  pubmed Zhang L, Shi W, Zhao Z, Wang Z 等 2025 Dec 置信度 0.82
• Cerebral Neurovascular Networks May Serve as Potential Targets for Identifying Disorders of Consciousness: A Synchronous Electroencephalography and Functional Near-Infrared Spectroscopy Study.
  pubmed Wang N, Si J, He Y, Song J 等 2025 Dec 置信度 0.82
• Transformer-based hybrid systems to combat BCI illiteracy.
  pubmed Pfeffer MA, Wong JKW, Ling SH 2026 Jan 1 置信度 0.82
• Deep equilibrium-adversarial robust unfolding network for MRI reconstruction.
  pubmed Zhou T, Shang K, Liu C, Cui Z 等 2025 Dec 置信度 0.82
• Brain-computer interfaces race to the clinic.
  pubmed Peplow M 2025 Dec 置信度 0.82
• Intelligent electroencephalogram feature engineering for rapid mental health diagnosis.
  pubmed Kripalal A, Sekar C 2026 Mar 置信度 0.82
• Generation and characterization of a human-derived iPSC line (HZSMHCi003-A) from a male child with fragile X syndrome.
  pubmed Tian X, Zhang X, Zhou C, Jiang Y 等 2026 Feb 置信度 0.82
• ASA-STGCN: Adaptive Sparse Awareness-Spatiotemporal Graph Convolutional Network for Multi-Class Motor Imagery EEG Classification.
  pubmed Meng M, Yu P, She Q, Xi X 等 2025 Dec 12 置信度 0.82
• [Prospects and technical challenges of non-invasive brain-computer interfaces in manned space missions].
  pubmed Ju Y, Liu J, Li Z, Liu Y 等 2025 Aug 28 置信度 0.82
• [Potential biological mechanisms underlying spaceflight-induced depression symptoms in astronauts].
  pubmed Li Z, Liu J, Liu B, Wang M 等 2025 Aug 28 置信度 0.82
• Gut microbiota modulates synaptic plasticity, connectivity, and dopamine transmission in the VTA-mPFC pathway in bipolar depression.
  pubmed Tang A, Chen Y, Si K, Lai J 等 2026 May 置信度 0.82
• Longitudinal multitask wireless electrocorticography data from two fully implanted nonhuman primates.
  pubmed Yang H, Fukuma R, Namima T, Okuda K 等 2025 Dec 11 置信度 0.82
• Tactile-evoked EEG Dataset for Natural Perception Using an Integrated Stimulation-Recording Framework.
  pubmed Mao L, Liu P, Li J, Wang X 等 2025 Dec 11 置信度 0.82
• High-Fidelity Functional Ultrasound Reconstruction via a Visual Auto-Regressive Framework.
  pubmed Chen X, Li Z, Shen Y, Mahmud M 等 2025 Dec 11 置信度 0.82
• Brain-computer interfaces: a new horizon in communication for locked-in syndrome.
  pubmed Ali MR, Talpur Y, Irshad NUN, Imran SB 2025 Dec 置信度 0.82
• Comparison of Classifier Calibration Schemes for Movement Intention Detection in Individuals with Cerebral Palsy for Inducing Plasticity with Brain-Computer Interfaces.
  pubmed Jochumsen M, Sulkjær CS, Dalgaard KS 2025 Dec 2 置信度 0.82
• Traditional Machine Learning Outperforms EEGNet for Consumer-Grade EEG Emotion Recognition: A Comprehensive Evaluation with Cross-Dataset Validation.
  pubmed Paredes Ocaranza CR, Yun B, Paredes Ocaranza ED 2025 Nov 28 置信度 0.82
• EEG-based meditation decoding: tackling subject variability with spatial and temporal alignment.
  pubmed Karaiskou AI, Varon C, Ates Musluoglu C, Alaerts K 等 2025 Dec 22 置信度 0.82
• Multi-source self-guided domain adaptation framework for EEG-based emotion recognition.
  pubmed Tan Y, Li B, Sun Z, Duan F 等 2026 Mar 置信度 0.82
• TCPL: task-conditioned prompt learning for few-shot cross-subject motor imagery EEG decoding.
  pubmed Wang P, Xie T, Zhou Y, Gong P 等 2025 置信度 0.82
• Second harmonic generation for brain imaging: pathology-related studies.
  pubmed Paveliev M, Melnikova A, Samigullin DV, Egorchev AA 等 2025 Sep 27 置信度 0.82
• Novel dual AMPK/NRF2 activation by leucocyanidin from Hawthorn (Crataegus) for mitochondria repair-Targeted therapy of hepatic steatosis.
  pubmed Li Y, Ye M, He Q, Yang B 等 2026 Jan 置信度 0.82
• Beta Burst Waveform Diversity: A Window onto Cortical Computation.
  pubmed Rayson H, Moreau Q, Gailhard S, Szul MJ 等 2026 Feb 置信度 0.82
• [Movement image training and brain-computer interface in cognitive rehabilitation].
  The paper provides an overview of studies on the use of movement image training and brain-computer interfaces (BCIs) for cognitive rehabilitation in patients with neurological diseases. Based on the analysis of studies published from 2004 to 2025, the effectiv…
  pubmed Labor VV, Mokienko OA, Cherkasova AN, Ikonnikova ES 等 2025 置信度 0.82 CognitionPhysical medicine and rehabilitationCognitive trainingRehabilitationCognitive rehabilitation therapy
• Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data during an inner speech task.
  pubmed Simistira Liwicki F, Saini R, Chakladar DD, Rakesh S 等 2025 Dec 置信度 0.82
• Long-term unsupervised recalibration of cursor-based intracortical brain-computer interfaces using a hidden Markov model.
  pubmed Wilson GH, Stein EA, Kamdar F, Avansino DT 等 2026 Jul 置信度 0.82
• The Berlin bimanual test for stroke survivors (BeBiT-S): evaluating exoskeleton-assisted bimanual motor function after stroke.
  pubmed Vermehren M, Colucci A, Angerhöfer C, Peekhaus N 等 2025 Dec 8 置信度 0.82
• An open dataset of multidimensional signals based on different speech patterns in pragmatic Mandarin.
  pubmed Zhao R, Bai Y, Zhang S, Zhu J 等 2025 Dec 8 置信度 0.82
• Patterned wireless transcranial optogenetics generates artificial perception.
  pubmed Wu M, Yang Y, Zhang J, Efimov AI 等 2026 Jan 置信度 0.82
• An EEG dataset to study neural correlates of audiovisual long-term memory retrieval.
  pubmed Matran-Fernandez A, Halder S 2025 Dec 8 置信度 0.82
• 3M-CPSEED, An EEG-based Dataset for Chinese Pinyin Production in Overt, Mouthed, and Imagined Speech.
  pubmed Ma X, Jiang Y, Jiang N 2025 Dec 8 置信度 0.82
• sEEG-based brain-computer interfacing in a large adult and pediatric cohort.
  Abstract Objective . Stereoelectroencephalography (sEEG) is a mesoscale intracranial monitoring technique that records from the brain volumetrically with depth electrodes. sEEG is typically used for monitoring of epileptic foci, but can also serve as a useful …
  pubmed A Jensen M, Schalk G, Ince N, Hermes D 等 2025 Dec 30 置信度 0.82 Motor imageryBrain–computer interfaceKinesthetic learningComputer scienceInterfacing
• Functional recovery induced by KCC2-enabled relay pathways in completely injured spinal cords in adult rats.
  pubmed Wang Y, Liu F, Shan Q, Wang X 等 2025 Dec 16 置信度 0.82
• Voxel-Level Brain States Prediction Using Swin Transformer.
  pubmed Sun Y, Chahine D, Wen Q, Liu T 等 2025 Dec 置信度 0.82
• Cross-Species Cortical Geometry Reveals Conserved Gradients Across Primates and Human-Specific Expansion.
  pubmed Wei Y, Wang Y, Wei T, Lu X 等 2025 Nov 28 置信度 0.82
• A Scalable 1024-Channel Ultra-Low-Power Spike Sorting Chip with Event-Driven Detection and Spatial Clustering.
  pubmed Akhoundi A, Yan P, Landbrug Y, Hays M 等 2025 Nov 置信度 0.82
• Long-Term Brain-Computer Interface Functional Electrical Stimulation Enhances Neuroplasticity and Functional Recovery in Elderly Stroke: A 4.5-Year Longitudinal Study Integrating Electroencephalography Biomarkers and Clinical Assessments.
  pubmed Chen S, Xie N, Tang Y, Ji Y 等 2025 置信度 0.82
• Deep Learning Architectures for Code-Modulated Visual Evoked Potentials Detection.
  pubmed Nair K, Cecotti H 2025 Nov 26 置信度 0.82
• Characterization of error-related potentials during the command of a lower-limb exoskeleton based on deep learning.
  pubmed Soriano-Segura P, Ortiz M, Polo-Hortigüela C, Iáñez E 等 2025 Dec 6 置信度 0.82
• From machine learning to neuroimaging: a comprehensive review of flavor prediction and recognition techniques.
  pubmed Wang J, Wang S, Li D, Fan W 等 2026 Jan 置信度 0.82
• A computational model of canonical cortical microcircuits for dynamic Bayesian inference and control as inference.
  pubmed Yamauchi N, Tawatsuji Y, Suzuki Y, Yamakawa H 等 2026 Jan 置信度 0.82
• Evolution of users' subjective experience over three training sessions with an EEG Motor-Imagery Brain-Computer Interface (MI-BCI).
  pubmed Roc A, Kolodzienski L, Dreyer P, Appriou A 等 2026 Feb 1 置信度 0.82
• Expanding Senses using Neurotechnology
  This textbook is an essential guide for students, researchers, and professionals in the interdisciplinary field of neurotechnology.
  crossref Ujwal Chaudhary 2025-02-18T22:58:10Z 置信度 0.70
• Welcome Message from the General Chairs
  It is a great pleasure to welcome you to the 13th International Winter Conference on Brain–Computer Interface. BCI2025 will be taking a hybrid conference format with both virtual and on–site attendees as anothersuccessful edition.
  crossref 2025-03-28T02:29:03Z 置信度 0.70
• Imagined Speech and Visual Imagery as Intuitive Paradigms for Brain-Computer Interfaces
  Brain-computer interfaces (BCIs) have shown promise in supporting communication for individuals with motor or speech impairments. Recent advancements such as brain-to-speech or brain-to-image technology aim to reconstruct speech from neural activity. However, …
  crossref Seo-Hyun Lee, Ji-Ha Park, Deok-Seon Kim 2025-03-28T02:29:03Z 置信度 0.70
• Ambient assisted living through passive brain–computer interface technology for assisting paralyzed people
  crossref Sanchita Goswami, Prithu Banik, Aniket Kumar Meena, Anjaneyulu Bendi 2025-01-31T14:26:37Z 置信度 0.70
• MATLAB® for Brain-Computer Interface Systems
  The book extensively explores Brain-Computer Interfaces (BCIs), emphasizing both the theoretical foundations and practical applications within this rapidly advancing field. It provides a thorough coverage of BCI fundamentals and practical implementation using …
  crossref Faridoddin Shariaty, Sanjiban Sekhar Roy 2025-05-23T11:21:24Z 置信度 0.70
• Filter Bank CSP with Riemannian Weighting for Disability-Centric Motor Imagery Brain Computer Interface v1
  This protocol is devoted to describing the steps involved in processing signal-based (EEG) motor imagery (MI) for brain-computer interfaces (BCI), from pre-processing to classification. Emphasis is placed on the various methods used, in particular the feature …
  crossref Souissi Jihen 2025-07-07T14:23:42Z 置信度 0.70
• Real-Time Monitoring Technology for Physiological States in Brain Computer Interface Systems
  crossref Chenxi Hu 2026-02-19T17:58:48Z 置信度 0.70
• Brain Signal-Based Motion Sickness Classification in Automobile Passengers
  Motion sickness remains a critical challenge for enhancing passenger comfort, particularly in autonomous vehicles, where non-driving activities are a primary benefit. This study investigates the multi-class classification of motion sickness levels using brain …
  crossref Tae Hun Kim, Hyun Min Lee, Jinung An 2025-03-28T02:29:03Z 置信度 0.70
• Brain Stimulation Theory and Techniques
  crossref Ujwal Chaudhary 2025-02-18T22:58:23Z 置信度 0.70
• Deep Learning Meets Source Reconstruction
  Accurately analyzing both structural and functional brain data from multimodal neuroimaging is a challenge. Applying deep learning has helped to gain insight into structural relationships across brain regions and complex dynamics of cognitive states. In this b…
  crossref K.-R Müller, M. Morik 2025-03-28T02:29:03Z 置信度 0.70
• Brain–computer interface
  crossref Shraddha Jain Shrama, Ratnalata Gupta 2024-11-08T03:41:00Z 置信度 0.70
• A comparison of deep learning methods and conventional methods for classification of SSVEP signals in brain-computer interface framework
  crossref Srinivas Rao Gorre, Ravichander Janapati, Ch. Rajendra Prasad, Usha Desai 2024-11-08T03:30:20Z 置信度 0.70
• Brain Computer Interface
  crossref Abdul Satti 2010-05-04T17:43:12Z 置信度 0.70
• Brain-Computer Interface for Aroma Perception
  Consumer sensory satisfaction, particularly aroma, dictates food product success. Olfaction starts in the nasal cavity, where odour molecules trigger electrical signals that travel to the brain, integrating with memories and emotions. Traditional sensory evalu…
  crossref Monica Velusamy, Mahendran Radhakrishnan 2025-06-24T14:43:46Z 置信度 0.70
• REMOVED: A case study on artifical intelligence based data processing in passive brain–computer interface
  crossref Parveen Kumar Sekharamantry, Usama A. Syed, Umer Farooq, Dinh Dung Van 2025-01-31T14:26:37Z 置信度 0.70
• Machine Learning with Brain Data
  crossref Ujwal Chaudhary 2025-02-18T22:58:25Z 置信度 0.70
• Invasive Brain Stimulation Techniques
  crossref Ujwal Chaudhary 2025-02-18T22:58:18Z 置信度 0.70
• Non-invasive Brain Stimulation Techniques
  crossref Ujwal Chaudhary 2025-02-18T22:58:16Z 置信度 0.70
• Towards a Neural ODE Generative Model of Cortical Dynamics
  Cytoarchitecture studies have revealed that neurons in cortex are not arranged at random, but instead follow a stereotyped pattern - repeated throughout the cortex. This powerful canonical microcircuit (CMC) motif subtends learning, memory, and a vast array of…
  crossref PK Douglas 2025-03-28T02:29:03Z 置信度 0.70
• Enhancing Organizational Systems With Brain-Computer Interface Technologies
  This research is being conducted to determine whether or not the application of brain-computer interface technology has the potential to improve organizational systems. As a result of the fact that they enable a direct connection to be made between the brain a…
  crossref Konda Hari Krishna, Navruzbek Shavkatov, Anantha Murthy, Muntadher Abed Hussein 等 2025-05-14T13:56:44Z 置信度 0.70
• Enhancing E-Learning With Brain-Computer Interface in Education
  The field of brain-computer interface (BCI) technology is developing quickly, and its fast growth could transform e-learning by bringing more engaging and intuitive educational experiences to the platform. To enhance educational outcomes, the integration of BC…
  crossref Ankur Jain, Prithu Sarkar, Abhishika Sharma, Neelu Jain 等 2025-05-14T13:56:44Z 置信度 0.70
• Application and Prospects of Non-Invasive Brain-Computer Interface (BCI) Technologies
  The BCI technology has long been known as a technology that could transform our modern world entirely. Despite most of the BCI today being invasive, non-invasive BCI are also developing toward its real world implementation. Compared with the traditional ones, …
  crossref Ruomu Xu 2025-06-26T07:55:48Z 置信度 0.70
• MetaIDNet: A Fast Brain-Computer Interface for Color Vision Assessment
  Brain-computer interfaces (BCIs) for color vision assessment measure color vision without requiring any behavioral responses from the participant, benefiting people with limited communication capabilities. The participant only needs to look at a visual stimulu…
  crossref Hadi Habibzadeh, Daphney-Stavroula Zois, James J. S. Norton 2025-03-18T23:54:21Z 置信度 0.70
• A Comprehensive Review of Brain-Computer Interface Technology: Advances, Applications, and Challenges in Neural Signal Decoding
  Brain-Computer Interface (BCI) technology enables direct communication between the human brain and external devices by decoding neural signals, offering transformative potential in medical rehabilitation, communication, human-robot interaction, and neuroprosth…
  crossref NAKSHATRA S PREM 2025-06-19T18:34:06Z 置信度 0.70
• Application and Future Prospects of Brain-Computer Interface in Neurological Diseases
  Brain-computer interface(BCI) is becoming into a panacea for people with neurological disorders,which can help people control the machine with their minds and help them restore their body function.It has the promise of becoming the next generation of hardware …
  openalex Chengrui Song 2025-12-19 置信度 0.72 Interface (matter)Panacea (medicine)MainstreamBrain–computer interfaceComputer science
• Volitional deep brain stimulation via neurofeedback: A brain-computer-interface case study
  crossref Jin-Xiao Zhang, Pria Daniel, Jiyeon Suh, Lucia Ricciardi 等 2025-02-25T05:19:01Z 置信度 0.70
• Enhancing Human-Computer Interaction Through Brain-Computer Interface: Technological Advances
  Brain-Computer Interface (BCI) has gained significant attention due to its potential to transform human-computer interaction (HCI), especially through non-invasive methods like electroencephalography (EEG). This essay explores the fundamental principles of non…
  crossref Ruoyao Zhang 2025-04-21T02:27:55Z 置信度 0.70
• STFEnc: A Novel Deep Encoder for Brain-Computer Interface Based on Interpretable Brain Features
  Brain-computer interface (BCI) is a technology that enables direct connection and interaction of brain activity with external devices or systems. The encoding and decoding of neural signals play a crucial role in BCIs. The quality of such encodings are the key…
  crossref Zonghan Du, Zhongyuan Lai 2025-03-12T13:52:43Z 置信度 0.70
• Preprocessing Techniques for Brain Signal Data
  crossref Ujwal Chaudhary 2025-02-20T10:09:48Z 置信度 0.70
• Semantic Reconstruction of Language from Non-Invasive Brain Recordings
  crossref Jerry Tang, Milena Korostenskaja 2025-03-11T12:20:08Z 置信度 0.70
• Conclusion
  The exploration of Brain-Computer Interface (BCI) systems within this text has spanned a wide array of topics, methodologies, and applications, demonstrating the interdisciplinary nature of BCI research and its profound potential to impact various aspects of h…
  crossref Faridoddin Shariaty, Sanjiban Sekhar Roy 2025-05-23T11:21:24Z 置信度 0.70