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• MicrobialScope: an integrated genomic resource with rich annotations across bacteria, archaea, fungi, and viruses.
  Microorganisms, including bacteria, archaea, fungi, and viruses, are the most taxonomically diverse and ecologically dominant life forms on Earth, playing critical roles in ecosystems, human health, and industrial applications. While existing microbial databas…
  pubmed Feng X, Li Y, Zheng J, Chen X 等 2026 Jan 6 置信度 0.82
• A retrospective study on the clinical efficacy of pneumatic hand rehabilitation devices in managing post-stroke chirospasm following ischemic stroke.
  Chirospasm is a common sequela of ischemic stroke (IS), often resulting in substantial impairment of hand function and quality of life. Although conventional rehabilitation can partially improve motor recovery, it is often insufficient in effectively reducing …
  pubmed Deng X, Lai K, Huang W, Liao F 2025 Nov 14 置信度 0.82
• Metabolomics and metabolites in cancer diagnosis and treatment.
  Cancer is a leading cause of death worldwide. Metabolic reprogramming in cancers plays an important role in tumor initiation, malignant progression and therapeutic response. Based on this, significant progress has been made in the development of the metabolite…
  pubmed Cai M, Liu H, Shao C, Li T 等 2025 Nov 14 置信度 0.82
• A 40-Class SSVEP Speller Dataset: Beta Range Stimulation for Low-Fatigue BCI Applications.
  The inherent non-stationarity of electroencephalography (EEG) signals necessitates large, consistent datasets for reliable brain-computer interface (BCI) research. In steady-state visual evoked potential (SSVEP) paradigms, prolonged exposure to visual stimuli …
  pubmed Kim H, Won K, Ahn M, Jun SC 2025 Nov 5 置信度 0.82
• Non-Linear Modeling and Precision Analysis Approach for Implantable Multi-Channel Neural Recording Systems.
  High-precision implantable multi-channel neural recording systems are considered as having a crucial role in the diagnosis and treatment of neurological disorders. However, it is a significant design challenge to achieve an optimal trade-off among linear param…
  pubmed He J, Xu J, Wang Y 2025 Oct 17 置信度 0.82
• A Review on Low-Dimensional Nanoarchitectonics for Neurochemical Sensing and Modulation in Responsive Neurological Outcomes.
  Low-Dimensional Nanohybrids (LDNHs) have emerged as potent multifunctional platforms for neurosensing and neuromodulation, providing elevated spatial-temporal precision, versatility, and biocompatibility. This review examines the intersection of LDNHs with art…
  pubmed Tabish M, Malik I, Akhtar A, Afzal M 2025 Oct 2 置信度 0.82
• CoSpine open access simultaneous cortico-spinal fMRI database of thermal pain and motor tasks.
  Simultaneous cortico-spinal functional magnetic resonance imaging (fMRI) enables non-invasive investigation of integrated central nervous system function, but acquisition challenges have restricted the availability of public datasets and slowed the development…
  pubmed Wei Z, Lin X, Zhang L, Guo L 等 2025 Oct 27 置信度 0.82
• Deciphering Neural Mechanisms Underlying Marmoset Dynamic Natural Behaviors Using a Miniaturized Wireless Large-Scale Coverage Neural Recorder.
  Deciphering neural mechanisms underlying dynamic natural behaviors of freely moving species requires long-term recordings of large-scale brain activities. However, most conventional neural recorders are limited by their weights and measures, electrode coverage…
  pubmed Liu H, Cao X, Li J, Zheng L 等 2026 Jan 置信度 0.82
• Abnormal Brain Connectivity Patterns in Children with Global Developmental Delay Accompanied by Cognitive Impairment: A Resting-State EEG Study.
  Global developmental delay (GDD) is a common childhood neurodevelopmental disorder characterized by the core symptoms of cognitive impairment. However, the underlying neural mechanisms of the cognitive impairment remain unclear. This study aimed to both analyz…
  pubmed Hui Z, Zhang Y, Su Y, Kang J 等 2025 Sep 30 置信度 0.82
• Multi-Channel Neural Interface for Neural Recording and Neuromodulation.
  Neural interfaces have emerged as pivotal platforms for advancing digital neurotherapies by enabling the real-time acquisition and monitoring of neural signals. Traditional single-channel systems are inherently limited in their capacity to capture the complex …
  pubmed Kim E, Chung WG, Oh M, Paek J 等 2026 Feb 置信度 0.82
• BCIT's BEAST wheelchair takes on Cybathlon with power, precision, and pilot-led design.
  An extending, articulating powered wheelchair competed and won the wheelchair race at Cybathlon 2024.
  pubmed Kryt G, Dougall R, Borisoff J 2025 Sep 17 置信度 0.82
• Classification of Different Motor Imagery Tasks with the Same Limb Using Electroencephalographic Signals.
  Stroke is a neurological condition that often results in long-term motor deficits. Given the high prevalence of motor impairments worldwide, there is a critical need to explore innovative neurorehabilitation strategies that aim to enhance the quality of life o…
  pubmed Kauati-Saito E, Pereira ADS, Fontana AP, de Sá AMFLM 等 2025 Aug 26 置信度 0.82
• Current Neuroethical Perspectives on Deep Brain Stimulation and Neuromodulation for Neuropsychiatric Disorders: A Scoping Review of the Past 10 Years.
  BACKGROUND: The use of neuromodulation for the treatment of psychiatric disorders has become increasingly common, but this emerging treatment modality comes with ethical concerns. This scoping review aims to synthesize the neuroethical discourse from the past …
  pubmed Shaw J, Pyreddy S, Rosendahl C, Lai C 等 2025 Aug 14 置信度 0.82 Deep brain stimulationNeuromodulationNeuroscienceBrain stimulationSacral nerve stimulation
• Surfing beta burst waveforms to improve motor imagery-based BCI.
  Our understanding of motor-related, macroscale brain processes has been significantly shaped by the description of the event-related desynchronization (ERD) and synchronization (ERS) phenomena in the mu and beta frequency bands prior to, during, and following …
  pubmed Papadopoulos S, Darmet L, Szul MJ, Congedo M 等 2024 置信度 0.82
• Neurofeedback-induced desynchronization of sensorimotor rhythm elicits pre-movement downregulation of intracortical inhibition that shortens simple reaction time in humans: A double-blind, sham-controlled randomized study.
  Sensorimotor rhythm event-related desynchronization (SMR-ERD) is associated with the activities of cortical inhibitory circuits in the motor cortex. The self-regulation of SMR-ERD through neurofeedback training has demonstrated that successful SMR-ERD regulati…
  pubmed Muraoka Y, Iwama S, Ushiba J 2024 置信度 0.82
• Gut microbiota links to cognitive impairment in bipolar disorder via modulating synaptic plasticity.
  Cognitive impairment is an intractable clinical manifestation of bipolar disorder (BD), but its underlying mechanisms remain largely unexplored. Preliminary evidence suggests that gut microbiota can potentially influence cognitive function by modulating synapt…
  pubmed Tang A, Jiang H, Li J, Chen Y 等 2025 Aug 12 置信度 0.82
• Emerging Brain-to-Content Technologies from Generative AI and Deep Representation Learning.
  Rapid advances in generative artificial intelligence (AI) and deep representation learning have revolutionized numerous engineering applications in signal processing, computer vision, speech recognition and translation, and natural language processing due to a…
  pubmed Chen ZS, Zhe Chen, Xingyu Li 2024 Nov 置信度 0.82 Computer scienceRepresentation (politics)Generative grammarArtificial intelligenceDeep learning
• Leveraging meaning-induced neural dynamics to detect covert cognition via EEG during natural language listening-a case series.
  At least a quarter of adult patients with severe brain injury in a disorder of consciousness may have cognitive abilities that are hidden due to motor impairment. In this case series, we developed a tool that extracted acoustic and semantic processing biomarke…
  pubmed Alkhoury L, O'Sullivan J, Scanavini G, Dou J 等 2025 置信度 0.82
• Assistive Technologies for Individuals with a Disability from a Neurological Condition: A Narrative Review on the Multimodal Integration.
  BACKGROUND/OBJECTIVES: Neurological disorders often result in a broad spectrum of disabilities that impact mobility, communication, cognition, and sensory processing, leading to significant limitations in independence and quality of life. Assistive technologie…
  pubmed Bonanno M, Saracino B, Ciancarelli I, Panza G 等 2025 Jul 1 置信度 0.82 PersonalizationUsabilityCognitionComputer scienceQuality of life (healthcare)
• A randomised controlled trial of amygdala fMRI-neurofeedback versus sham-feedback in borderline-personality disorder - systematic literature review and introduction to the BrainSTEADy trial.
  Individuals with Borderline-Personality Disorder (BPD) experience intensive, unstable negative emotions. Hyperactivity of the amygdala is assumed to drive exaggerated emotional responses in BPD. Functional Magnetic Resonance Imaging (fMRI)-based neurofeedback …
  pubmed Paret C, Jindrová M, Kleindienst N, Eck J 等 2025 Jul 8 置信度 0.82
• A Systematic Review of Empirical Studies on Situation Awareness: Perspectives From the Interaction Among Humans, Machines, and the Task Environment.
  Situational awareness (SA) refers to "knowing what is going on" in a situation. As an essential concept originating in aviation literature approximately 40 years ago, SA has demonstrated significant potential and has since been extended across various f…
  pubmed Fang R, Zhou Q, Zhou C, Yuan S 等 2025 Oct 置信度 0.82
• The spectrum of overlapping anti-NMDAR encephalitis and demyelinating syndromes: a systematic review of presentation, diagnosis, management, and outcomes.
  Anti-NMDAR encephalitis frequently overlaps with demyelinating diseases (MOGAD, NMOSD, MS), creating complex syndromes with diverse presentations and challenging management.
  pubmed Saeed S, Wang H, Jia M, Liu TT 等 2025 Dec 置信度 0.82
• Performance-Recoverable Closed-Loop Neuroprosthetic System.
  Soft bioelectronics mechanically comparable to living tissues have driven advances in closed-loop neuroprosthetic systems for the recovery of sensory-motor functions. Despite notable progress in this field, critical challenges persist in achieving long-term st…
  pubmed Kim Y, Kang K, Koo JH, Jeong Y 等 2025 Sep 置信度 0.82
• [A portable steady-state visual evoked potential brain-computer interface system for smart healthcare].
  This paper realized a portable brain-computer interface (BCI) system tailored for smart healthcare. Through the decoding of steady-state visual evoked potential (SSVEP), this system can rapidly and accurately identify the intentions of subjects, thereby meetin…
  pubmed Zhu Y, Ji Z, Li S, Wang H 等 2025 Jun 25 置信度 0.82
• Neurotechnological Approaches to Cognitive Rehabilitation in Mild Cognitive Impairment: A Systematic Review of Neuromodulation, EEG, Virtual Reality, and Emerging AI Applications.
  Background/Objectives: Mild Cognitive Impairment (MCI) represents a clinical syndrome characterized by cognitive decline greater than expected for an individual's age and education level but not severe enough to significantly interfere with daily activities, w…
  pubmed Gkintoni E, Vassilopoulos SP, Nikolaou G, Vantarakis A 2025 May 28 置信度 0.82
• Virtual reality for stroke rehabilitation.
  Virtual reality applications have emerged as a treatment approach in stroke rehabilitation, with the first randomised trial published in 2004. A wide range of applications have been tested in research studies and adopted in clinical practice, from non-immersiv…
  pubmed Laver KE, Lange B, George S, Deutsch JE 等 2025 Jun 20 置信度 0.82
• Comparison of the effects of transcranial direct current stimulation combined with different rehabilitation interventions on motor function in people suffering from stroke-related symptoms: a systematic review and network meta-analysis.
  This study employs network meta-analysis to assess the efficacy of transcranial direct current stimulation (tDCS) combined with different rehabilitation approaches in enhancing motor function in people suffering from stroke-related symptoms (PSSS). The objecti…
  pubmed Zheng K, Guo L, Liang W, Liu P 2025 置信度 0.82
• The use of robotics and artificial intelligence in upper extremity rehabilitation following traumatic injury: A scoping review.
  With the recent advances in technology and its increased use in society, healthcare practices work to identify areas where technology can be implemented to enhance patient care. Rehabilitation has begun to incorporate the use of robotics and artificial intelli…
  pubmed Toner AA, Eberlin L, Pichaimuthu R, Tompkins T 等 2025 Apr-Jun 置信度 0.82
• Pseudo-linear summation explains neural geometry of multi-finger movements in human premotor cortex.
  How does the motor cortex combine simple movements (such as single finger flexion/extension) into complex movements (such as hand gestures, or playing the piano)? To address this question, motor cortical activity was recorded using intracortical multi-electrod…
  pubmed Shah NP, Avansino D, Kamdar F, Nicolas C 等 2025 May 30 置信度 0.82
• Neurophysiological Approaches to Lie Detection: A Systematic Review.
  Background and Objectives: Lie detection is crucial in domains such as security, law enforcement, and clinical assessments. Traditional methods suffer from reliability issues and susceptibility to countermeasures. In recent years, electroencephalography (EEG) …
  pubmed Taha BN, Baykara M, Alakuş TB 2025 May 18 置信度 0.82
• A Web-based Interface for Visualizing and Documenting SEEG Strategic Planning (WISP): Development and Qualitative Evaluation.
  WISP stands as an efficacious solution to the challenges associated with Stereoelectroencephalography (SEEG) strategic planning, offering lightweight and interactive web interfaces for rendering multiple brain views. These interfaces facilitate collaborative e…
  pubmed Chou WC, Hampson JP, Byrd AT, Lhatoo SD 等 2024 置信度 0.82
• A role for preparatory midfrontal theta in autism as revealed by a high executive load brain-computer interface reverse spelling task.
  Midfrontal theta oscillations have been linked to executive function, yet their role in autism-where this function is often compromised-remains unclear. We hypothesized that preparatory increases in theta power may help normalize performance in autism. To test…
  pubmed Dias C, Sousa T, Cruz A, Costa D 等 2025 May 14 置信度 0.82
• A bibliometric analysis of electroencephalogram research in stroke: current trends and future directions.
  Electroencephalography (EEG) has become an indispensable tool in stroke research for real-time monitoring of neural activity, prognosis prediction, and rehabilitation support. In recent decades, EEG applications in stroke research have expanded, particularly i…
  pubmed Liao XY, Jiang YE, Xu RJ, Qian TT 等 2025 置信度 0.82
• A systematic review of resting-state functional-MRI studies in the diagnosis, comorbidity and treatment of postpartum depression.
  Postpartum depression (PPD) is a common and serious mental health problem that affects many new mothers and their families worldwide. In recent years, there has been an increasing number of studies using magnetic resonance techniques (MRI), particularly functi…
  pubmed Tang Y, Tang Z, Zhou Y, Luo Y 等 2025 Aug 15 置信度 0.82
• Differentiation of Glioblastoma and Solitary Brain Metastasis Using Brain-Tumor Interface Radiomics Features Based on MR Images: A Multicenter Study.
  Glioblastoma (GBM) and solitary brain metastasis (SBM) exhibit similar radiomics features on magnetic resonance imaging (MRI), yet their treatment strategies and prognoses significantly differ. Therefore, accurate differentiation between these two types of tum…
  pubmed Chen Y, Guo W, Li Y, Lin H 等 2025 Jul 置信度 0.82
• What Else Is Happening to the Mirror Neurons?-A Bibliometric Analysis of Mirror Neuron Research Trends and Future Directions (1996-2024).
  Since its discovery in the late 20th century, research on mirror neurons has become a pivotal area in neuroscience, linked to various cognitive and social functions. This bibliometric analysis explores the research trajectory, key research topics, and future t…
  pubmed Sun Y, Yu N, Chen G, Liu T 等 2025 Apr 置信度 0.82
• Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field.
  To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation systems. The Detrended Fluctuation Analysis (DFA) exponent is chosen as the classification…
  pubmed Yu Z, Yang B, Wei P, Xu H 等 2025 Jan 置信度 0.82
• Signal acquisition of brain-computer interfaces: A medical-engineering crossover perspective review.
  Brain-computer interface (BCI) technology represents a burgeoning interdisciplinary domain that facilitates direct communication between individuals and external devices. The efficacy of BCI systems is largely contingent upon the progress in signal acquisition…
  pubmed Sun Y, Chen X, Liu B, Liang L 等 2024-04-16 置信度 0.82 ViewpointsBrain–computer interfaceComputer scienceModalitiesInterface (matter)
• Achieving High-Performance Transcranial Ultrasound Transmission Through Mie and Fano Resonance in Flexible Metamaterials.
  Transcranial ultrasound holds great potential in medical applications. However, the effective transmission of ultrasound through the skull remains challenging due to the acoustic impedance mismatch, as well as the non-uniform thickness, and the curved surface.…
  pubmed Chen J, Liu B, Peng G, Zhou L 等 2025 May 置信度 0.82
• High-Performance Synapse Arrays for Neuromorphic Computing via Floating Gate-Engineered IGZO Synaptic Transistors.
  Neuromorphic computing emulating the human brain offers a promising alternative to the Von Neumann architecture. Developing artificial synapses is essential for implementing hardware neuromorphic systems. Indium-gallium-zinc oxide (IGZO)-based synaptic transis…
  pubmed Park J, Yun Y, Bae S, Jang Y 等 2025 Jun 置信度 0.82
• Multi-modality NDE fusion using encoder-decoder networks for identify multiple neurological disorders from EEG signals.
  The complexity and diversity of brain activity patterns make it difficult to accurately diagnose neurological disorders such epilepsy, Parkinson's disease, schizophrenia, stroke, and Alzheimer's disease. Integrated and effective analysis of multiple data sourc…
  pubmed Jain S, Srivastava R 2025 Sep 置信度 0.82
• Accelerated algorithms for source orientation detection and spatiotemporal LCMV beamforming in EEG source localization.
  This paper illustrates the development of two efficient source localization algorithms for electroencephalography (EEG) data, aimed at enhancing real-time brain signal reconstruction while addressing the computational challenges of traditional methods. Accurat…
  pubmed Yektaeian Vaziri A, Makkiabadi B 2024 置信度 0.82
• Construction of a Multimodal 3D Atlas for a Micrometer-Scale Brain-Computer Interface Based on Mixed Reality.
  To develop a multimodal imaging atlas of a rat brain-computer interface (BCI) that incorporates brain, arterial, bone tissue and a BCI device using mixed reality (MR) for three-dimensional (3D) visualization.
  pubmed Zhou H, Yan ZN, Gao WH, Lv XX 等 2025 Apr 置信度 0.82
• Surface-based versus voxel-based finite element head models: comparative analyses of strain responses.
  Finite element (FE) models of the human head are important injury assessment tools but developing a high-quality, hexahedral-meshed FE head model without compromising geometric accuracy is a challenging task. Important brain features, such as the cortical fold…
  pubmed Zhou Z, Li X, Kleiven S 2025 Jun 置信度 0.82
• Man, Hibernating Animals, and Poikilothermic Fish: The Present and Future of BCI Technology.
  In 2024 and early 2025, several successful surgeries involving brain-computer interfaces (BCIs) gained media attention, including those conducted by Elon Musk's company Neuralink, which implanted BCIs in three paralyzed volunteers, allowing them to control com…
  pubmed Gielas AM 2025 Apr 4 置信度 0.82
• A bibliometric analysis of studies on artificial intelligence in neuroscience.
  The incorporation of artificial intelligence (AI) into neuroscience has the potential to significantly enhance our comprehension of brain function and facilitate more effective diagnosis and treatment of neurological disorders. Artificial intelligence (AI) tec…
  pubmed Tekin U, Dener M, Ugur Tekin, Murat Dener 2025 置信度 0.82 Transformative learningScope (computer science)NeuroinformaticsArtificial intelligenceCognitive neuroscience
• Feasibility of Immersive Virtual Reality Feedback for Enhancing Learning in Brain-Computer Interface Control of Ambulation.
  After prolonged paralysis, paraplegic spinal cord injury (SCI) patients typically lose the ability to generate the expected electroencephalogram (EEG) α/β modulation associated with leg movements. Brain computer interface (BCI)-controlled ambulatio…
  pubmed Chaudhry ZA, Baxter RH, Fu JL, Wang PT 等 2024 Jul 置信度 0.82
• Enhancing Brain Machine Interface Decoding Accuracy through Domain Knowledge Integration.
  This paper introduces a novel decoding approach for Brain Machine Interface (BMI) that enhances the estimation accuracy and stability of muscle activity by incorporating domain knowledge of motor control. Our approach uniquely integrates domain knowledge, focu…
  pubmed Okitsu K, Isezaki T, Obara K, Nishimura Y 2024 Jul 置信度 0.82
• Domain-Incremental Learning Framework for Continual Motor Imagery EEG Classification Task.
  Due to inter-subject variability in electroencephalogram (EEG) signals, the generalization ability of many existing brain-computer interface (BCI) models is significantly limited. Although transfer learning (TL) offers a temporary solution, in scenarios requir…
  pubmed Li D, Shin HB, Yin K, Lee SW 2024 Jul 置信度 0.82
• EEG Channel Localization and Selection via Training with Noise Injection for BCI Applications.
  Electroencephalography (EEG) is crucial for monitoring brain activity in neuroscience and clinical applications. However, the multitude of channels recorded by scalp electrodes poses challenges, including impractical usage and high model complexity. This paper…
  pubmed Huang CM, Lai WL, Yang CC, Hsieh YJ 等 2024 Jul 置信度 0.82
• Robust EEG-based Emotion Recognition Using an Inception and Two-sided Perturbation Model.
  Automated emotion recognition using electroencephalogram (EEG) signals has gained substantial attention. Although deep learning approaches exhibit strong performance, they often suffer from vulnerabilities to various perturbations, like environmental noise and…
  pubmed Sartipi S, Cetin M 2024 Jul 置信度 0.82
• An online brain-computer interface for a precise positioning of target based on rapid serial visual presentation.
  The brain-computer interface (BCI) based on rapid serial visual presentation (RSVP) provides a novel approach for efficiently optimizing traditional machine-based target detection, revealing a broad application prospect in security, entrainment, monitoring, et…
  pubmed Meng J, Yang M, Zhang S, Xu M 等 2024 Jul 置信度 0.82
• Time Window Optimization for Riemannian Geometry-based Motor Imagery EEG Classification.
  The existing Riemannian geometry-based approaches for brain computer interface (BCI) employ fixed time windows. However, the inherent variability and dynamic changes among subjects necessitate robust and adaptive solutions for time window optimization. Recogni…
  pubmed Zhuo F, Lv B, Tang F 2024 Jul 置信度 0.82
• Guiding Brain-to-Vocalization Decoder Design Using Structured Generalization Error.
  State-of-the-art intracortical neuroprostheses currently enable communication at 60+ words per minute for anarthric individuals by training on over 10K sentences to account for phoneme variability in different word contexts. There is limited understanding abou…
  pubmed Huang J, Tostado-Marcos P, Narasimha SM, Patel AN 等 2024 Jul 置信度 0.82
• Profiling a Raspberry Pi-Based Motor Imagery Classification to Facilitate At-Home BCI for Children with Disabilities.
  There has been incremental progress in moving BCI out of the laboratory environment and into the homes of those who would benefit most, especially children living with severe physical disabilities. Practical issues, such as available computational resources an…
  pubmed Idowu OP, Kinney-Lang E, Gulamhusein A, Irvine B 等 2024 Jul 置信度 0.82
• EEG Pattern Comparison and Classification Performance of Motor Imagery Between Supernumerary and Inherent Limbs.
  Adding supernumerary robotic limbs (SRLs) to humans and controlling them directly through the brain are main goals for movement augmentation. However, whether neural patterns that are distinct from the traditional inherent limbs motor imagery (MI) paradigm can…
  pubmed Wang Z, Liu Y, Wu W, Huang S 等 2024 Jul 置信度 0.82
• Baseline-Guided Representation Learning for Noise-Robust EEG Signal Classification.
  Brain-computer interfaces (BCIs) suffer from limited accuracy due to noisy electroencephalography (EEG) signals. Existing denoising methods often remove artifacts such as eye movement or use techniques such as linear detrending, which inadvertently discard cru…
  pubmed Lim EY, Yin K, Shin HB, Lee SW 2024 Jul 置信度 0.82
• Enhancement of Functional Connectivity in Frontal-Parietal Regions After BCI-Actuated Supernumerary Robotic Finger Training.
  The supernumerary robotic finger (SRF) can expand human hand abilities to achieve motor augmentation, and integrate with brain computer interface (BCI) to free the occupation of inherent body degrees of freedom. However, the neuro remodeling mechanisms of brai…
  pubmed Huang S, Liu Y, Xu W, Wang Z 等 2024 Jul 置信度 0.82
• Precision Enhancement in Sustained Visual Attention Training Platforms: Offline EEG Signal Analysis for Classifier Fine-Tuning.
  In this study, a novel open-source brain-computer interface (BCI) platform was developed to decode scalp electroencephalography (EEG) signals associated with sustained attention. The EEG signal collection was conducted using a wireless headset during a sustain…
  pubmed Norouzi M, Amirani MZ, Shahriari Y, Abiri R 2024 Jul 置信度 0.82
• Enhancing Auditory BCI Performance: Incorporation of Connectivity Analysis.
  Brain connectivity analysis to classify auditory stimuli applicable to invasive auditory BCI technology, particularly intracranial electroencephalography (iEEG) remains an exciting frontier. This study revealed insights into brain network dynamics, improving a…
  pubmed Ferdous TR, Pollonini L, Francis JT 2024 Jul 置信度 0.82
• EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network.
  Electroencephalogram (EEG) is a valuable technique to record brain electrical activity through electrodes placed on the scalp. Analyzing EEG signals contributes to the understanding of neurological conditions and developing brain-computer interface. Graph Sign…
  pubmed Ye H, Goerttler S, He F 2024 Jul 置信度 0.82
• A Study on Changes in Estimation Accuracy for EEG Data During Calibration and Operation in MI-BCI.
  Changes in psychological factors have been suggested to cause variations in brain-computer interface (BCI) performance. More specifically, differences in psychological variables between the calibration and operation phases may cause a decrease in accuracy duri…
  pubmed Kanda T, Isezaki T, Okitsu K 2024 Jul 置信度 0.82
• Patient-Involved Validation of A Somatosensory ERP-BCI Facilitated by Electric Stimulation for Stroke Rehabilitation.
  Brain-computer interface (BCI) is emerging as an effective complementary solution in the field of rehabilitation for the interaction between patients and robotic assistive devices. Specifically, the somatosensory event-related potentials (ERP) BCI has unique a…
  pubmed Wang J, Li X, Huang Y, Xiao D 等 2024 Jul 置信度 0.82
• Proxy-based Masking Module for Revealing Relevance of Characteristics in Motor Imagery.
  Brain-computer interface (BCI) has been developed for communication between users and external devices by reflecting users' status and intentions. Motor imagery (MI) is one of the BCI paradigms for controlling external devices by imagining muscle movements. MI…
  pubmed Han HT, Kim SJ, Lee DH, Lee SW 2024 Jul 置信度 0.82
• Enhanced BCI Performance using Diffusion Model for EEG Generation.
  In the realm of Motor Imagery (MI)-based Brain-Computer Interface (BCI), the widespread adoption of deep learning-based algorithms has resulted in an increased demand for a larger training sample size, thereby placing a heightened burden on users. This study a…
  pubmed Zhong Y, Yao L, Wang Y 2024 Jul 置信度 0.82
• Channel- and Label-Flip Data Augmentation for Motor Imagery-Based Brain-Computer Interfaces.
  Achieving high classification accuracy in motor-imagery-based brain-computer interfaces (BCIs) requires substantial amounts of training data. A challenge arises because of the impracticality of measuring large amounts of data from users. Data augmentation (DA)…
  pubmed Hoshino T, Kanoga S, Aoyama A 2024 Jul 置信度 0.82
• Dynamic Inverse Reinforcement Learning for Feedback-driven Reward Estimation in Brain Machine Interface Tasks.
  Reinforcement learning (RL)-based brain machine interfaces (BMIs) provide a promising solution for paralyzed people. Enhancing the decoding performance of RL-based BMIs relies on the design of effective reward signals. Inverse reinforcement learning (IRL) offe…
  pubmed Tan J, Wang Y 2024 Jul 置信度 0.82
• Transformer-Based Emotion Recognition with EEG.
  Emotion recognition via electroencephalography (EEG) has emerged as a pivotal domain in biomedical signal processing, offering valuable insights into affective states. This paper presents a novel approach utilizing a tailored Transformer-based model to predict…
  pubmed Patel K, Safavi F, Chandramouli R, Vinjamuri R 2024 Jul 置信度 0.82
• Antioxidant Coated Microelectrode Arrays: Effects on Putative Inhibitory and Excitatory Neurons.
  Intracortical microelectrode arrays (MEAs) are used to record neural activity in vivo at single-cell resolution for both neuroscience studies and for engineering restorative devices such as brain-computer interfaces (BCIs). The recording performance of these d…
  pubmed Sturgill BS, Jiang MS, Jeakle EN, Smith TJ 等 2024 Jul 置信度 0.82
• Toward the TCN-based Real-Time BCI System for Target Detection.
  This study focuses on developing a real-time Brain-Computer Interface (BCI) system, specifically designed for military applications, to enhance target detection in rapid serial visual presentation (RSVP) tasks. The proposed BCI system utilizes electroencephalo…
  pubmed Won E, Lim S, Kim Y, Dong SY 2024 Jul 置信度 0.82
• Towards EEG-based Talking-face Generation for Brain Signal-driven Dynamic Communication.
  Research on decoding speech or generating images from human brain activity holds intriguing potential as neuroprosthesis for patients and innovative communication tools for general users. However, previous studies have been constrained in generating fragmented…
  pubmed Park JH, Lee SH, Lee SW 2024 Jul 置信度 0.82
• Prediction errors from distinct perspectives induce separable EEG features for brain-computer interface.
  The ability to efficiently detect error is fundamental for human adaptive behaviors, and plays an increasingly crucial role in developing more intelligent brain-computer interface (BCI). Error-related potential (ErrP), which can reflect prediction error, has b…
  pubmed He F, Zhang S, Yang M, Meng J 等 2024 Jul 置信度 0.82
• An Adaptive Superposition Point Process Model with Neuronal Encoding Engagement Identification.
  Neuronal encoding is realized by modulating firing rates in response to various encoding factors, including external stimuli, behaviors, and complex neural interactions. The neuronal encoding engagement of various factors are dynamic, which reflects how neuron…
  pubmed Li M, Wang M, Wang Y 2024 Jul 置信度 0.82
• Reconstruction of Continuous Hand Grasp Movement from EEG Using Deep Learning.
  Brain-Computer Interface (BCI) is a promising neu-rotechnology offering non-muscular control of external devices, such as neuroprostheses and robotic exoskeletons. A new yet under-explored BCI control paradigm is Motion Trajectory Prediction (MTP). While MTP p…
  pubmed Tang Y, Robinson N, Fu X, Thomas KP 等 2024 Jul 置信度 0.82
• MEG Channel Selection Using Copula Entropy-Based Transfer Entropy for Motor Imagery BCI.
  Multi-channel magnetoencephalography (MEG) data provides high spatiotemporal resolution for motor imagery (MI)-based brain-machine interfaces (BCIs). However, not all channels contribute to the performance of BCIs. Taking into account the importance of specifi…
  pubmed Tang C, Jiang D, Chen B 2024 Jul 置信度 0.82
• Benchmarking motor imagery algorithms for pediatric users of brain-computer interfaces.
  Brain-computer interfaces (BCIs) can enable opportunities for self-expression and life participation for children with severe neurological disabilities. Unfortunately, the development and evaluation of state-of-the-art algorithms has largely neglected pediatri…
  pubmed Irvine B, Abou-Zeid H, Kirton A, Kinney-Lang E 2024 Jul 置信度 0.82
• Methodological Considerations in the Analysis of Acoustically Evoked Neural Signals: A Comparative Study of Active EEG, Passive EEG and MEG.
  Analyzing and deciphering brain signals on a single trial base is the main goal of brain-computer interface (BCI) research as well as neurolinguistics. In the present study, we have evaluated the efficacy of three neuroimaging techniques-active electroencephal…
  pubmed Kolbl N, Tziridis K, Krauss P, Schilling A 2024 Jul 置信度 0.82
• Design and Evaluate Semi-dry Watermill-like EEG Electrodes.
  Semi-dry electrodes act as the middle ground between wet and dry electrodes as they not only have similar contact features (equivalent circuit) with Ag/AgCl-based wet electrodes but also carry the conduct material in their cavity or sponge (e.g. absorb saline …
  pubmed Lu JB, Tsao Y, Wang YT 2024 Jul 置信度 0.82
• Bi-hemisphere Interaction Convolutional Neural Network for Motor Imagery Classification.
  Decoding EEG-based, Motor Imagery Brain-Computer Interfaces (MI-BCI) in a subject-independent manner is very challenging due to high dimensionality of the EEG signal, and high inter-subject variability. In recent years, Convolutional neural networks (CNNs) hav…
  pubmed Lin X, Eldele E, Chen Z, Wu M 等 2024 Jul 置信度 0.82
• Assessing the Impact of Environment and Electrode Configuration on P300 Speller Performance and EEG Signal Quality.
  Recent years have seen extensive use of brain-computer interfaces (BCIs) using electroencephalography (EEG). A critical element in BCI research is electrode selection, which influences performance, experiment duration, resource utilization, and consequently, c…
  pubmed Noble SC, Ward T, Ringwood JV 2024 Jul 置信度 0.82
• A Vision Transformer Architecture For Overt Speech Decoding From ECoG Data.
  Speech Brain-Computer Interfaces rely on decoding algorithms that transform neural activity into speech. A current challenge is to achieve intelligible speech synthesis in real time from continuous ongoing brain activity, ideally without the need of language m…
  pubmed Ben Ticha MB, Ran X, Roussel P, Bocquelet F 等 2024 Jul 置信度 0.82
• Textured Stimuli Comfort and Response in SSVEP-Based Brain Computer Interface.
  State of the art steady-state visual evoked potential (SSVEP) brain computer interface (BCI) stimuli are commonly high-contrast, solid color flashing objects which can contribute to visual discomfort and fatigue. The use of low-contrast, textured flashing stim…
  pubmed Schrag E, Comaduran-Marquez D, Kirton A, Kinney-Lang E 2024 Jul 置信度 0.82
• Evaluation of EEG and MEG responses during Fine Motor Imagery from the same limb.
  Motor imagery (MI) is an important brain-computer interface (BCI) paradigm. BCI systems based on fine MI can provide an intuitive control pathway of the outer device. Electroencephalography (EEG) is a widely used modality for MI due to its high temporal resolu…
  pubmed Jiang R, Qiu S, Wang Y, Zhang C 等 2024 Jul 置信度 0.82
• Role of Scalp EEG Brain Connectivity in Motor Imagery Decoding for BCI Applications.
  Brain Connectivity (BC) features of multichannel EEG have been proposed for Motor Imagery (MI) decoding in Brain-Computer Interface applications, but the advantages of BC features vs. single-channel features are unclear. Here, we consider three BC features, i.…
  pubmed Delavari F, Santaniello S 2024 Jul 置信度 0.82
• Automated Hyper-Parameter Optimization for Eye Movement Artifact Removal.
  Brain-computer interface (BCI) systems allow users to control external devices with their brain waves. However, electroencephalography (EEG) signals used by most BCI systems are prone to artifacts from various sources (e.g., muscle activity, eye movements, and…
  pubmed Marquez DC, Minhas A, Kinney-Lang E, Kirton A 2024 Jul 置信度 0.82
• Artificial touch feedback using microstimulation of human somatosensory cortex to convey grip force from a robotic hand.
  Invasive brain-machine interfaces can help restore function through the control of external devices while the addition of intracortical microstimulation (ICMS) can elicit sensations of touch and help provide further benefits for individuals living with sensori…
  pubmed Osborn LE, Christie B, McMullen DP, Thomas TM 等 2024 Jul 置信度 0.82
• Functional Connectivity Methods for Multi-Class Mental Workload Classification.
  Recently, significant attention has been drawn to the ability of network-based features to classify EEG signals reflecting varying levels of mental workload. Such features are based on methods of functional connectivity (FC), which quantify the statistical rel…
  pubmed Teymourlouei A, Hu M, Gentili R, Reggia J 2024 Jul 置信度 0.82
• Mental Fatigue Classification with High-Density Diffuse Optical Tomography: A Feasibility Study.
  High-Density Diffuse Optical Tomography (HD-DOT) presents as a promising tool for not only clinical use but also daily monitoring of mental states. This study employed wearable HD-DOT to evaluate mental fatigue, specifically examining the differences in functi…
  pubmed Chen J, Xia Y, Thomas A, Carlson T 等 2024 Jul 置信度 0.82
• Application of a Neural ODE to Classify Motion Control Strategy using EEG.
  Speed-accuracy trade offs exist in a variety of functional tasks, which may require differences in control strategies in future neuroprosthetic devices. It is the goal of this work to evaluate the predictability of different motor control strategies during wri…
  pubmed Ziegelman L, Hernandez ME 2024 Jul 置信度 0.82
• Advancing SSVEP-BCI Decoding: Cross-Subject Transfer Learning and Short Calibrated Approach with ELM-AE.
  The Steady-State Visually Evoked Potential (SSVEP) is a robust paradigm for developing a high-speed Brain-Computer Interface (BCI). However, one of the challenges of BCI is to face the variability of EEG signals between subjects to reduce or eliminate the time…
  pubmed Flores C, Casas P, de Carvalho SN, Attux R 2024 Jul 置信度 0.82
• A neuro-feedback prototype based on transcranial Doppler ultrasound for brain computer interface applications.
  This study proposes a TCD-based neurofeedback system designed to visualize interhemispheric hemodynamic imbalance based on the bilateral monitoring of middle cerebral arteries (MCAs). The difference between cerebral blood velocities collected from the right an…
  pubmed Rabbito R, Cinanni A, Bussi L, Guiot C 等 2024 Jul 置信度 0.82
• High-Frequency SSVEP-BCI Stimulation Frequency Optimization Based on BCI accuracy.
  This study investigates optimization of the stimulation frequency of blinking stimuli used for steady-state visual evoked potential (SSVEP) brain-computer interface (BCI) for individuals. Heare, we set the target BCI accuracy to 90%, and we propose and evaluat…
  pubmed Kondo S, Tanaka H 2024 Jul 置信度 0.82
• Revisiting the grammar of Tau aggregation and pathology formation: how new insights from brain pathology are shaping how we study and target Tauopathies
  Converging evidence continues to point towards Tau aggregation and pathology formation as central events in the pathogenesis of Alzheimer's disease and other Tauopathies. Despite significant advances in understanding the morphological and structural properties…
  openalex Galina Limorenko, Hilal A. Lashuel 2021-12-10 置信度 0.72 Tau pathologyPathologyNeurosciencePsychologyMedicine
• Animal models of head trauma
  openalex Ibolja Černak 2005-06-13 置信度 0.72 Traumatic brain injuryNeuroprotectionNeuroscienceAnimal modelHead injury
• Increasing accessibility to a large brain–computer interface dataset: Curation of physionet EEG motor movement/imagery dataset for decoding and classification
  A reliable motor imagery (MI) brain-computer interface (BCI) requires accurate decoding, which in turn requires model calibration using electroencephalography (EEG) signals from subjects executing or imagining the execution of movements. Although the PhysioNet…
  openalex Zaid Shuqfa, Abderrahmane Lakas, Abdelkader Nasreddine Belkacem 2024-02-12 置信度 0.72 Brain–computer interfaceMotor imageryComputer scienceElectroencephalographyDecoding methods
• Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis
  Brain stroke, or a cerebrovascular accident, is a devastating medical condition that disrupts the blood supply to the brain, depriving it of oxygen and nutrients. Each year, according to the World Health Organization, 15 million people worldwide experience a s…
  openalex João Fernandes, Vitor E.M. Cardoso, Alberto Comesaña-Campos, Alberto Pinheira 2024-07-04 置信度 0.72 Deep learningStroke (engine)Artificial intelligenceHealth careDemographics
• Fetal brain tissue annotation and segmentation challenge results
  In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research…
  openalex Kelly Payette, Hongwei Li, Priscille de Dumast, Roxane Licandro 等 2023-04-22 置信度 0.72 SegmentationComputer scienceArtificial intelligenceDeep learningContext (archaeology)
• Interfacing Aptamer-Modified Nanopipettes with Neuronal Media and Ex Vivo Brain Tissue
  High Resolution Image Download MS PowerPoint Slide Aptamer-functionalized biosensors exhibit high selectivity for monitoring neurotransmitters in complex environments. We translated nanoscale aptamer-modified nanopipette sensors to detect endogenous dopamine r…
  openalex Annina Stuber, Anna Cavaccini, Andreea Manole, A. V. Burdina 等 2023-11-22 置信度 0.72 AptamerNanotechnologyEx vivoBiosensorBiophysics
• Design and Evaluation of CPU-, GPU-, and FPGA-Based Deployment of a CNN for Motor Imagery Classification in Brain-Computer Interfaces
  Brain–computer interfaces (BCIs) have gained popularity in recent years. Among noninvasive BCIs, EEG-based systems stand out as the primary approach, utilizing the motor imagery (MI) paradigm to discern movement intentions. Initially, BCIs were predominantly f…
  openalex Federico Pacini, Tommaso Pacini, Giuseppe Lai, Alessandro Zocco 等 2024-04-25 置信度 0.72 Computer scienceField-programmable gate arrayInferenceBrain–computer interfaceCentral processing unit
• Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach
  Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to detect brain tumors early. Recent claims have been made that computer-aided diagnosis-based systems can diagnose b…
  openalex Tejas Shelatkar, Dr. Urvashi, Mohammad Shorfuzzaman, Abdulmajeed Alsufyani 等 2022-07-01 置信度 0.72 Deep learningArtificial intelligenceComputer scienceTransfer of learningBrain tumor