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• Improving the Performance of Electrotactile Brain-Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials.
  Traditional tactile brain-computer interfaces (BCIs), particularly those based on steady-state somatosensory-evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contrast, using…
  pubmed Novičić M, Djordjević O, Miler-Jerković V, Konstantinović L 等 2024 Dec 17 置信度 0.82 Brain–computer interfaceSupport vector machineComputer scienceSomatosensory systemElectroencephalography
• Optically Controlled Drug Delivery Through Microscale Brain-Machine Interfaces Using Integrated Upconverting Nanoparticles.
  The aim of this work is to incorporate lanthanide-cored upconversion nanoparticles (UCNP) into the surface of microengineered biomedical implants to create a spatially controlled and optically releasable model drug delivery device in an integrated fashion. Our…
  pubmed Víg L, Zátonyi A, Csernyus B, Horváth ÁC 等 2024 Dec 14 置信度 0.82
• Humanity Test-EEG Data Mediated Artificial Intelligence Multi-Person Interactive System.
  Artificial intelligence (AI) systems are widely applied in various industries and everyday life, particularly in fields such as virtual assistants, healthcare, and education. However, this paper highlights that existing research has often overlooked the philos…
  pubmed Fang F, Gao T, Wu J 2024 Dec 12 置信度 0.82
• Unlocking Security for Comprehensive Electroencephalogram-Based User Authentication Systems.
  With recent significant advancements in artificial intelligence, the necessity for more reliable recognition systems has rapidly increased to safeguard individual assets. The use of brain signals for authentication has gained substantial interest within the sc…
  pubmed Khalil AEK, Perez-Diaz JA, Cantoral-Ceballos JA, Antelis JM 2024 Dec 11 置信度 0.82
• Selective Auditory Attention Detection Using Combined Transformer and Convolutional Graph Neural Networks.
  Attention is one of many human cognitive functions that are essential in everyday life. Given our limited processing capacity, attention helps us focus only on what matters. Focusing attention on one speaker in an environment with many speakers is a critical a…
  pubmed Geravanchizadeh M, Shaygan Asl A, Danishvar S 2024 Nov 30 置信度 0.82
• Emotion Recognition Model of EEG Signals Based on Double Attention Mechanism.
  Emotions play a crucial role in people's lives, profoundly affecting their cognition, decision-making, and interpersonal communication. Emotion recognition based on brain signals has become a significant challenge in the fields of affective computing and human…
  pubmed Ma Y, Huang Z, Yang Y, Zhang S 等 2024 Dec 21 置信度 0.82
• hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction.
  Modeling multi-channel electroencephalographic (EEG) time-series is a challenging tasks, even for the most recent deep learning approaches. Particularly, in this work, we targeted our efforts to the high-fidelity reconstruction of this type of data, as this is…
  pubmed Cisotto G, Zancanaro A, Zoppis IF, Manzoni SL 2024 置信度 0.82
• Biologically inspired heterogeneous learning for accurate, efficient and low-latency neural network.
  The pursuit of artificial neural networks that mirror the accuracy, efficiency and low latency of biological neural networks remains a cornerstone of artificial intelligence (AI) research. Here, we incorporated recent neuroscientific findings of self-inhibitin…
  pubmed Wang B, Zhang Y, Li H, Dou H 等 2025 Jan 置信度 0.82
• Individual structural covariance connectome reveals aberrant brain developmental trajectories associated with childhood maltreatment.
  The long-term impact of childhood maltreatment (CM) on an individual's physical and mental health is suggested to be mediated by altered neurodevelopment. However, the exact neurobiological consequences of CM remain unclear.
  pubmed Pang Y, Zhao S, Zhang Z, Xu J 等 2025 Jan 置信度 0.82
• Emotion recognition using multi-scale EEG features through graph convolutional attention network.
  Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in patients with consciousness disorders, assisting in the diagnosis of depression, and assessing cognitive load. T…
  pubmed Cao L, Zhao W, Sun B 2025 Apr 置信度 0.82
• EEG channel and feature investigation in binary and multiple motor imagery task predictions.
  Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high classification accuracy. Although various machine learning methods have al…
  pubmed Degirmenci M, Yuce YK, Perc M, Isler Y 2024 置信度 0.82
• Adaptive deep feature representation learning for cross-subject EEG decoding.
  The collection of substantial amounts of electroencephalogram (EEG) data is typically time-consuming and labor-intensive, which adversely impacts the development of decoding models with strong generalizability, particularly when the available data is limited. …
  pubmed Liang S, Li L, Zu W, Feng W 等 2024 Dec 31 置信度 0.82
• Differences in spatiotemporal dynamics for processing specific semantic categories: An EEG study.
  Semantic processing is an essential mechanism in human language comprehension and has profound implications for speech brain-computer interface technologies. Despite recent advances in brain imaging techniques and data analysis algorithms, the mechanisms under…
  pubmed Le TT, Luong DAQ, Joo H, Kim D 等 2024 Dec 30 置信度 0.82
• Motion Cognitive Decoding of Cross-Subject Motor Imagery Guided on Different Visual Stimulus Materials.
  Motor imagery (MI) plays an important role in brain-computer interfaces, especially in evoking event-related desynchronization and synchronization (ERD/S) rhythms in electroencephalogram (EEG) signals. However, the procedure for performing a MI task for a sing…
  pubmed Luo TJ, Li J, Li R, Zhang X 等 2024 Dec 19 置信度 0.82
• ESI-GAL: EEG source imaging-based trajectory estimation for grasp and lift task.
  Electroencephalogram (EEG) signals-based motor kinematics prediction (MKP) has been an active area of research to develop Brain-computer interface (BCI) systems such as exosuits, prostheses, and rehabilitation devices. However, EEG source imaging (ESI) based k…
  pubmed Jain A, Kumar L 2025 Mar 置信度 0.82
• EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer.
  Emotions play a crucial role in human thoughts, cognitive processes, and decision-making. EEG has become a widely utilized tool in emotion recognition due to its high temporal resolution, real-time monitoring capabilities, portability, and cost-effectiveness. …
  pubmed Cheng Z, Bu X, Wang Q, Yang T 等 2024 Dec 28 置信度 0.82
• Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus.
  Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexu…
  pubmed Guo X, Feng Y, Ji X, Jia N 等 2025 Jan 置信度 0.82
• Mechanisms of low MHC I expression and strategies for targeting MHC I with small molecules in cancer immunotherapy.
  Major histocompatibility complex (MHC) class I load antigens and present them on the cell surface, which transduces the tumor-associated antigens to CD8 + T cells, activating the acquired immune system. However, many tumors downregulate MHC I expression to eva…
  pubmed Kong S, Zhang J, Wang L, Li W 等 2025 Feb 28 置信度 0.82
• An Ensemble Deep Learning Approach for EEG-Based Emotion Recognition Using Multi-Class CSP.
  In recent years, significant advancements have been made in the field of brain-computer interfaces (BCIs), particularly in the area of emotion recognition using EEG signals. The majority of earlier research in this field has missed the spatial-temporal charact…
  pubmed Yousefipour B, Rajabpour V, Abdoljabbari H, Sheykhivand S 等 2024 Dec 14 置信度 0.82
• Novel rehabilitation technologies in pediatric rehabilitation: knowledge towards translation.
  Knowledge translation (KT) refers to the process of applying the most promising research outcomes into practice to ensure that new discoveries and innovations improve healthcare accessibility, effectiveness, and accountability. The objective of this perspectiv…
  pubmed Gefen N, Mazer B, Krasovsky T, Weiss PL 2025 Jul 置信度 0.82
• An Unsupervised Feature Extraction Method based on CLSTM-AE for Accurate P300 Classification in Brain-Computer Interface Systems.
  The P300 signal, an endogenous component of event-related potentials, is extracted from an electroencephalography signal and employed in Brain-computer Interface (BCI) devices.
  pubmed Afrah R, Amini Z, Kafieh R 2024 Dec 置信度 0.82
• Unraveling EEG correlates of unimanual finger movements: insights from non-repetitive flexion and extension tasks.
  The loss of finger control in individuals with neuromuscular disorders significantly impacts their quality of life. Electroencephalography (EEG)-based brain-computer interfaces that actuate neuroprostheses directly via decoded motor intentions can help restore…
  pubmed Sun Q, Merino EC, Yang L, Van Hulle MM 2024 Dec 26 置信度 0.82
• Performance investigation of MVMD-MSI algorithm in frequency recognition for SSVEP-based brain-computer interface and its application in robotic arm control.
  This study focuses on improving the performance of steady-state visual evoked potential (SSVEP) in brain-computer interfaces (BCIs) for robotic control systems. The challenge lies in effectively reducing the impact of artifacts on raw data to enhance the perfo…
  pubmed Fu R, Niu S, Feng X, Shi Y 等 2025 May 置信度 0.82
• Synchronous bilateral Wilms tumors are prone to develop independently and respond differently to preoperative chemotherapy.
  Wilms tumor (WT) is the most common kidney cancer in infants and young children. The determination of the clonality of bilateral WTs is critical to the treatment, because lineage-independent and metastatic tumors may require different treatment strategies. Her…
  pubmed Tao T, Liu S, He M, Zhao M 等 2025 May 1 置信度 0.82
• A Roadmap for Implanting Electrode Arrays to Evoke Tactile Sensations Through Intracortical Stimulation.
  Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface (BCI) to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise ta…
  pubmed Downey JE, Schone HR, Foldes ST, Greenspon C 等 2024 Dec 15 置信度 0.82
• 3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal.
  Non-invasive brain-computer interfaces (BCI) hold great promise in the field of neurorehabilitation. They are easy to use and do not require surgery, particularly in the area of motor imagery electroencephalography (EEG). However, motor imagery EEG signals oft…
  pubmed Li X, Chu Y, Wu X, Xiaoguang Li 等 2024 置信度 0.82
• STAFNet: an adaptive multi-feature learning network via spatiotemporal fusion for EEG-based emotion recognition.
  Emotion recognition using electroencephalography (EEG) is a key aspect of brain-computer interface research. Achieving precision requires effectively extracting and integrating both spatial and temporal features. However, many studies focus on a single dimensi…
  pubmed Hu F, He K, Qian M, Liu X 等 2024 置信度 0.82
• Decoding thoughts, encoding ethics: A narrative review of the BCI-AI revolution.
  OBJECTIVES: This narrative review aims to analyze mechanisms underlying Brain-Computer Interface (BCI) and Artificial Intelligence (AI) integration, evaluate recent advances in signal acquisition and processing techniques, and assess AI-enhanced neural decodin…
  pubmed Rudroff T, Thorsten Rudroff 2024-12-22 置信度 0.82 NarrativeDecoding methodsEncoding (memory)Brain–computer interfaceCognitive science
• An attention-based motor imagery brain-computer interface system for lower limb exoskeletons.
  Lower-limb exoskeletons have become increasingly popular in rehabilitation to help patients with disabilities regain mobility and independence. Brain-computer interface (BCI) offers a natural control method for these exoskeletons, allowing users to operate the…
  pubmed Ma X, Chen W, Pei Z, Zhang J 2024 Dec 1 置信度 0.82
• Review of Functional Cranioplasty and Implantable Neurotechnology.
  Cranioplasty for secondary reconstruction of cranial defects has historically focused on simply replacing the missing cranial bone to restore cerebral protection and fluid dynamics, but recent innovations have led to the development of customized cranial impla…
  pubmed Gordon CR, Perez CF 2025 Mar-Apr 01 置信度 0.82
• A novel dual-step transfer framework based on domain selection and feature alignment for motor imagery decoding.
  In brain-computer interfaces (BCIs) based on motor imagery (MI), reducing calibration time is gradually becoming an urgent issue in practical applications. Recently, transfer learning (TL) has demonstrated its effectiveness in reducing calibration time in MI-B…
  pubmed Bai G, Jin J, Xu R, Wang X 等 2024 Dec 置信度 0.82
• Decoding of movement-related cortical potentials at different speeds.
  The decoding of electroencephalogram (EEG) signals, especially motion-related cortical potentials (MRCP), is vital for the early detection of motor intent before movement execution. To enhance the decoding accuracy of MRCP and promote the application of early …
  pubmed Zhang J, Shen C, Chen W, Ma X 等 2024 Dec 置信度 0.82
• A bimodal deep learning network based on CNN for fine motor imagery.
  Motor imagery (MI) is an important brain-computer interface (BCI) paradigm. The traditional MI paradigm (imagining different limbs) limits the intuitive control of the outer devices, while fine MI paradigm (imagining different joint movements from the same lim…
  pubmed Wu C, Wang Y, Qiu S, He H 2024 Dec 置信度 0.82
• STGAT-CS: spatio-temporal-graph attention network based channel selection for MI-based BCI.
  Brain-computer interface (BCI) based on the motor imagery paradigm typically utilizes multi-channel electroencephalogram (EEG) to ensure accurate capture of physiological phenomena. However, excessive channels often contain redundant information and noise, whi…
  pubmed Meng M, Xu B, Ma Y, Gao Y 等 2024 Dec 置信度 0.82
• MSHANet: a multi-scale residual network with hybrid attention for motor imagery EEG decoding.
  EEG decoding plays a crucial role in the development of motor imagery brain-computer interface. Deep learning has great potential to automatically extract EEG features for end-to-end decoding. Currently, the deep learning is faced with the chanllenge of decodi…
  pubmed Li M, Li J, Zheng X, Ge J 等 2024 Dec 置信度 0.82
• Coherence-based channel selection and Riemannian geometry features for magnetoencephalography decoding.
  Magnetoencephalography (MEG) records the extremely weak magnetic fields on the surface of the scalp through highly sensitive sensors. Multi-channel MEG data provide higher spatial and temporal resolution when measuring brain activities, and can be applied for …
  pubmed Tang C, Gao T, Wang G, Chen B 2024 Dec 置信度 0.82
• Data-driven natural computational psychophysiology in class.
  Objective. The assessment of mental fatigue (MF) and attention span in educational and healthcare settings frequently relies on subjective scales or methods such as induced-task interruption tools. However, these approaches are deficient in real-time evaluatio…
  pubmed Huang Y, Huan Y, Zou Z, Wang Y 等 2024 Dec 置信度 0.82
• Extrasinusoidal macrophages are a distinct subset of immunologically active dural macrophages.
  Although macrophages in the meningeal compartments of the central nervous system (CNS) have been comprehensively characterized under steady state, studying their contribution to physiological and pathological processes has been hindered by the lack of specific…
  pubmed Amann L, Fell A, Monaco G, Sankowski R 等 2024 Dec 20 置信度 0.82
• Cognitive Remediation in Patients With Bipolar Disorder: A Randomized Trial by Sequential tDCS and Navigated rTMS Targeting the Primary Visual Cortex.
  Non-invasive brain stimulation (NIBS), such as transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), has emerged as a promising alternative in the precise treatment of clinical symptoms, such as the cognitive i…
  pubmed Zhou H, Wang M, Xu T, Zhang X 等 2024 Dec 置信度 0.82
• Advancing public health through technological rehabilitation: insights from a national clinician survey.
  In the evolving healthcare landscape, technology has emerged as a key component in enhancing system efficiency and offering new avenues for patient rehabilitation. Despite its growing importance, detailed information on technology's specific use, types, and ap…
  pubmed Capecci M, Gandolfi M, Straudi S, Calabrò RS 等 2024 Dec 19 置信度 0.82
• Tactile imagery affects cortical responses to vibrotactile stimulation of the fingertip.
  Mental imagery is a crucial cognitive process, yet its underlying neural mechanisms remain less understood compared to perception. Furthermore, within the realm of mental imagery, the somatosensory domain is particularly underexplored compared to other sensory…
  pubmed Morozova M, Yakovlev L, Syrov N, Lebedev M 等 2024 Dec 15 置信度 0.82
• Combining motion performance with EEG for diagnosis of mild cognitive impairment: a new perspective.
  pubmed Wan X, Xing S, Zhang Y, Duan D 等 2024 置信度 0.82
• Task-relevant stimulus design improves P300-based brain-computer interfaces.
  In the pursuit of refining P300-based brain-computer interfaces (BCIs), our research aims to propose a novel stimulus design focused on selective attention and task relevance to address the challenges of P300-based BCIs, including the necessity of repetitive s…
  pubmed Kim J, Cho YS, Kim SP 2024 Dec 18 置信度 0.82
• Simultaneous encoding of speed, distance, and direction in discrete reaching: an EEG study.
  Objective. The complicated processes of carrying out a hand reach are still far from fully understood. In order to further the understanding of the kinematics of hand movement, the simultaneous representation of speed, distance, and direction in the brain is e…
  pubmed Srisrisawang N, Müller-Putz GR 2024 Dec 27 置信度 0.82
• A neurocognitive pathway for engineering artificial touch.
  Artificial haptics has the potential to revolutionize the way we integrate physical and virtual technologies in our daily lives, with implications for teleoperation, motor skill acquisition, rehabilitation, gaming, interpersonal communication, and beyond. Here…
  pubmed Nisky I, Makin TR 2024 Dec 20 置信度 0.82
• EEG-based action anticipation in human-robot interaction: a comparative pilot study.
  As robots become integral to various sectors, improving human-robot collaboration is crucial, particularly in anticipating human actions to enhance safety and efficiency. Electroencephalographic (EEG) signals offer a promising solution, as they can detect brai…
  pubmed Vieira R, Moreno P, Vourvopoulos A, Rodrigo Vieira 等 2024 置信度 0.82
• Explainable fNIRS-based pain decoding under pharmacological conditions via deep transfer learning approach.
  Assessment of pain and its clinical diagnosis rely on subjective methods which become even more complicated under analgesic drug administrations.
  pubmed Eken A, Yüce M, Yükselen G, Erdoğan SB 2024 Oct 置信度 0.82
• Editorial: Neurocomputational models of language processing.
  pubmed Hofmann MJ, Chang YN, Brouwer H, Zock M 2024 置信度 0.82
• Neurosurgical and BCI approaches to visual rehabilitation in occipital lobe tumor patients.
  This study investigates the effects of occipital lobe tumors on visual processing and the role of brain-computer interface (BCI) technologies in post-surgical visual rehabilitation. Through a combination of pre-surgical functional magnetic resonance imaging (f…
  pubmed Ma J, Rui Z, Zou Y, Qin Z 等 2024 Dec 15 置信度 0.82
• Designing Silk Biomaterials toward Better Future Healthcare: The Development and Application of Silk-Based Implantable Electronic Devices in Clinical Diagnosis and Therapy.
  Implantable medical electronic devices (IMEDs) have attracted great attention and shown versatility for solving clinical problems ranging from real-time monitoring of physiological/ pathological states to electrical stimulation therapy and from monitoring brai…
  pubmed Lv Q, Li Q, Cao P, Wei C 等 2025 Feb 置信度 0.82
• 3D-BCLAM: A Lightweight Neurodynamic Model for Assessing Student Learning Effectiveness.
  Evaluating students' learning effectiveness is of great importance for gaining a deeper understanding of the learning process, accurately diagnosing learning barriers, and developing effective teaching strategies. Emotion, as a key factor influencing learning …
  pubmed Zhuang W, Zhang Y, Wang Y, He K 2024 Dec 9 置信度 0.82
• An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model.
  Electroencephalography (EEG) is a non-invasive technique with high temporal resolution and cost-effective, portable, and easy-to-use features. Motor imagery EEG (MI-EEG) data classification is one of the key applications within brain-computer interface (BCI) s…
  pubmed Megalingam RK, Sankardas KS, Manoharan SK 2024 Nov 30 置信度 0.82
• MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification.
  Decoding lower-limb motor imagery (MI) is highly important in brain-computer interfaces (BCIs) and rehabilitation engineering. However, it is challenging to classify lower-limb MI from electroencephalogram (EEG) signals, because lower-limb motions (LLMs) inclu…
  pubmed Li LL, Cao GZ, Zhang YP, Li WC 等 2024 Nov 28 置信度 0.82
• Development and application of the Demands for Population Health Interventions (Depth) framework for categorising the agentic demands of population health interventions.
  The 'agentic demand' of population health interventions (PHIs) refers to the capacity, resources and freedom to act that interventions demand of their recipients to benefit, which have a socio-economical pattern. Highly agentic interventions, e.g. information …
  pubmed Garrott K, Ogilvie D, Panter J, Petticrew M 等 2024 Mar 4 置信度 0.82
• The design and implementation of multi-character classification scheme based on EEG signals of visual imagery.
  In visual-imagery-based brain-computer interface (VI-BCI), there are problems of singleness of imagination task and insufficient description of feature information, which seriously hinder the development and application of VI-BCI technology in the field of res…
  pubmed Pan H, Song W, Li L, Qin X 2024 Oct 置信度 0.82
• Review of Applications in Brain-Computer Interfaces Using the EMOTIV Insight Headset
  This review explores advancements in Brain-Computer Interfaces (BCIs) using the EMOTIV Insight headset, a non-invasive electroencephalography (EEG) device. The study addresses the rising interest in affordable EEG devices for applications like robotic control,…
  openalex Yamin Thwe, Nipat Jongsawat, Julaluk Watthananon, Padma Nyoman Crisnapati 等 2024-09-25 置信度 0.72 HeadsetBrain–computer interfaceComputer scienceHuman–computer interactionElectroencephalography
• Modulatory Effects of Phytochemicals on Gut–Brain Axis: Therapeutic Implication
  This article explores the potential therapeutic implications of phytochemicals on the gut-brain axis (GBA), which serves as a communication network between the central nervous system and the enteric nervous system. Phytochemicals, which are compounds derived f…
  openalex Khojasteh Rahimi Jaberi, Vahab Alamdari-Palangi, Amir Savardashtaki, Pooya Vatankhah 等 2024-05-21 置信度 0.72 Gut–brain axisNeuroscienceBiologyMedicineGut flora
• Transfer learning enables predictions in network biology
  openalex Christina V. Theodoris, Ling Xiao, Anant Chopra, Mark Chaffin 等 2023-05-31 置信度 0.72 Computer scienceContext (archaeology)Deep learningArtificial intelligenceTransfer of learning
• Control of Electric Wheelchair by Brain‐Computer Interface Using Mixed Reality and Virtual Sound Source
  Abstract A brain‐computer interface for operating an electric wheelchair (wheelchair BCI) has been studied to support independent living for physically disabled patients. The current wheelchair BCI systems are facing the problem that the wheelchair cannot be m…
  openalex Fumina Mori, Masato Sugino, Yunshan Huang, Kiyoshi Kotani 等 2024-03-20 置信度 0.72 WheelchairVirtual realityInterface (matter)Computer scienceSound (geography)
• Kirigami‐Structured, Low‐Impedance, and Skin‐Conformal Electronics for Long‐Term Biopotential Monitoring and Human–Machine Interfaces
  Abstract Epidermal dry electrodes with high skin‐compliant stretchability, low bioelectric interfacial impedance, and long‐term reliability are crucial for biopotential signal recording and human–machine interaction. However, incorporating these essential char…
  openalex Meili Xia, Jianwen Liu, Beom Jin Kim, Yongju Gao 等 2023-11-20 置信度 0.72 PEDOT:PSSMaterials scienceElectrodeElectrical impedancePerspiration
• Benchmarking brain–computer interface algorithms: Riemannian approaches vs convolutional neural networks
  Abstract Objective. To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural networks for EEG-based brain–computer interfaces remains absent from published work. We address this research gap by using MOABB, The Mother O…
  openalex Manuel Eder, Jiachen Xu, Moritz Grosse‐Wentrup 2024-07-25 置信度 0.72 BenchmarkingConvolutional neural networkComputer scienceInterface (matter)Brain–computer interface
• Spatial transcriptomics at the brain-electrode interface in rat motor cortex and the relationship to recording quality
  Abstract Study of the foreign body reaction to implanted electrodes in the brain is an important area of research for the future development of neuroprostheses and experimental electrophysiology. After electrode implantation in the brain, microglial activation…
  openalex Quentin A. Whitsitt, Akash Saxena, Bella Patel, Blake M. Evans 等 2024-06-17 置信度 0.72 ElectrophysiologyTranscriptomeAstrogliosisNeuroscienceGlial fibrillary acidic protein
• Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity
  openalex Alik S. Widge 2023-07-06 置信度 0.72 Deep brain stimulationPsychologyNeurosciencePsychiatryBrain stimulation
• The potential power of Neuralink – how brain-machine interfaces can revolutionize medicine
  1. Brain-machine interfaces (BMIs) were once considered an idea grounded in science fiction but are becoming tangible due to advances in neuroengineering and computational neuroscience. One leader ...
  openalex Rahul Kumar, Ethan Waisberg, Joshua Ong, Andrew G. Lee 2025-04-27 置信度 0.72 NeuroscienceMedicineComputer sciencePsychology
• Peripheral neural interfaces for reading high-frequency brain signals
  openalex Jaime Ibáñez, Blanka Zicher, Etienne Burdet, Stuart N. Baker 等 2025-06-27 置信度 0.72 InterfacingPeripheralReading (process)Computer sciencePeripheral nervous system
• Graphene oxide electrodes enable electrical stimulation of distinct calcium signalling in brain astrocytes
  Astrocytes are responsible for maintaining homoeostasis and cognitive functions through calcium signalling, a process that is altered in brain diseases. Current bioelectronic tools are designed to study neurons and are not suitable for controlling calcium sign…
  openalex R. Fabbri, Alessandra Scidà, Emanuela Saracino, Giorgia Conte 等 2024-07-10 置信度 0.72 GrapheneCalciumNeuroscienceCalcium signalingMaterials science
• Analysis of hindlimb muscle moment arms in Tyrannosaurus rex using a three-dimensional musculoskeletal computer model: implications for stance, gait, and speed
  Muscle moment arms are important determinants of muscle function; however, it is challenging to determine moment arms by inspecting bone specimens alone, as muscles have curvilinear paths that change as joints rotate. The goals of this study were to (1) develo…
  openalex John R. Hutchinson, Frank C. Anderson, Silvia S. Blemker, Scott L. Delp 2005-01-01 置信度 0.72 AnatomyAnkleHindlimbGaitMoment (physics)
• Devices used for photobiomodulation of the brain—a comprehensive and systematic review
  A systematic review was conducted to determine the trends in devices and parameters used for brain photobiomodulation (PBM). The revised studies included clinical and cadaveric approaches, in which light stimuli were applied to the head and/or neck. PubMed, Sc…
  openalex Filipa Fernandes, Sofia Oliveira, Francisca Monteiro, Michael Gasik 等 2024-04-10 置信度 0.72 ScopusWeb of scienceSystematic reviewMedicineMEDLINE
• The Effect of Processing Techniques on the Classification Accuracy of Brain-Computer Interface Systems
  Background/Objectives : Accurately classifying Electroencephalography (EEG) signals is essential for the effective operation of Brain-Computer Interfaces (BCI), which is needed for reliable neurorehabilitation applications. However, many factors in the process…
  pubmed András Adolf, Csaba Márton Köllőd, Gergely Márton, Ward Fadel 等 2024 Dec 18 置信度 0.82 Brain–computer interfaceComputer scienceArtifact (error)Classifier (UML)Pipeline (software)
• Brain Organoids: A Game-Changer for Drug Testing
  Neurological disorders are the second cause of death and the leading cause of disability worldwide. Unfortunately, no cure exists for these disorders, but the actual therapies are only able to ameliorate people's quality of life. Thus, there is an urgent need …
  openalex Chiara Giorgi, Giorgia Lombardozzi, Fabrizio Ammannito, Marta Sofia Scenna 等 2024-03-22 置信度 0.72 OrganoidDrugComputer sciencePharmacologyNeuroscience
• iTBS on RDLPFC improves performance of motor imagery: a brain-computer interface study combining EEG and fNIRS
  BACKGROUND: Some individuals using brain-computer interfaces (BCIs) exhibit ineffective control during motor imagery-based BCI (MI-BCI) training. MI-BCI performance correlates with the activation in the frontoparietal attention network, premotor-parietal netwo…
  openalex Jialin Chen, Quan Liu, Gengbin Chen, Guiyuan Cai 等 2025-07-31 置信度 0.72 Brain–computer interfaceMotor imageryElectroencephalographyNeurologyNeuroimaging
• Refining neural network algorithms for accurate brain tumor classification in MRI imagery
  Brain tumor diagnosis using MRI scans poses significant challenges due to the complex nature of tumor appearances and variations. Traditional methods often require extensive manual intervention and are prone to human error, leading to misdiagnosis and delayed …
  openalex Asma Alshuhail, Arastu Thakur, R Chandramma, T R Mahesh 等 2024-05-21 置信度 0.72 Computer scienceArtificial neural networkArtificial intelligenceRefining (metallurgy)Brain tumor
• The potential of graphene coatings as neural interfaces
  Graphene coatings hold transformative potential for brain interfaces. This review explores the physico-chemical aspects of chemical vapor deposited graphene coatings in neurological applications, highlighting the key properties of an ideal interface.
  openalex Vicente Lopes, Gabriel Moreira, Mattia Bramini, Andrea Capasso 2024-01-01 置信度 0.72 GrapheneNanotechnologyMaterials scienceBiocompatibilityInterface (matter)
• RETRACTED: An efficient brain tumor detection and classification using pre-trained convolutional neural network models
  In cases of brain tumors, some brain cells experience abnormal and rapid growth, leading to the development of tumors. Brain tumors represent a significant source of illness affecting the brain. Magnetic Resonance Imaging (MRI) stands as a well-established and…
  openalex K. Nishanth Rao, Osamah Ibrahim Khalaf, Vasagiri Krishnasree, Aruru Sai Kumar 等 2024-08-26 置信度 0.72 Convolutional neural networkComputer scienceArtificial intelligenceDeep learningConfusion matrix
• Using transient, effector-specific neural responses to gate decoding for brain–computer interfaces
  Abstract Objective. Real-world implementation of brain–computer interfaces (BCIs) for continuous control of devices should ideally rely on fully asynchronous decoding approaches. That is, the decoding algorithm should continuously update its output by estimati…
  openalex Brian M Dekleva, Jennifer L. Collinger 2025-01-14 置信度 0.72 Computer scienceNeural decodingDecoding methodsBrain–computer interfaceAsynchronous communication
• Pattern Descriptors Orientation and MAP Firefly Algorithm Based Brain Pathology Classification Using Hybridized Machine Learning Algorithm
  Magnetic Resonance Imaging (MRI) is a significant technique used to diagnose brain abnormalities at early stages. This paper proposes a novel method to classify brain abnormalities (tumor and stroke) in MRI images using a hybridized machine learning algorithm.…
  openalex B. Deepa, M. Murugappan, M. G. Sumithra, Mufti Mahmud 等 2021-07-27 置信度 0.72 Artificial intelligencePattern recognition (psychology)Computer scienceRandom forestSupport vector machine
• Enhancing Classification Accuracy with Integrated Contextual Gate Network: Deep Learning Approach for Functional Near-Infrared Spectroscopy Brain–Computer Interface Application
  Brain–computer interface (BCI) systems include signal acquisition, preprocessing, feature extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning (DL) algorithms play a crucial role in enhancing accuracy. Unlike traditional ma…
  openalex Jamila Akhter, Noman Naseer, Hammad Nazeer, Haroon Khan 等 2024-05-10 置信度 0.72 Computer scienceArtificial intelligencePreprocessorInterface (matter)Feature extraction
• Ensemble Technique for Brain Tumor Patient Survival Prediction
  Brain Tumours pose a significant health challenge, demanding the immediate development of reliable and automated detection methods within the medical sphere. Swift and accurate identification of these Tumours is crucial for effective treatment and the well-bei…
  openalex D. S. Vinod, S. P. Shiva Prakash, Hussain AlSalman, Abdullah Y. Muaad 等 2024-01-01 置信度 0.72 Computer scienceArtificial intelligence
• Human-Computer Interaction
  openalex Masaaki Kurosu, Ayako Hashizume 2023-01-01 置信度 0.72 Computer scienceHuman–computer interaction
• Fetal brain MRI atlases and datasets: A review
  Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal br…
  openalex Tommaso Ciceri, Luca Casartelli, Florian Montano, Stefania Conte 等 2024-04-01 置信度 0.72 NeuroimagingNeuroscienceBrain developmentIdentification (biology)Psychology
• A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain
  Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention from the brain signals is a major step toward the development of bionic ears emulating human capabilities. Electroencephalography (EEG)-based auditory attention…
  openalex Siqi Cai, Peiwen Li, Haizhou Li 2023-08-16 置信度 0.72 Computer scienceElectroencephalographyDecoding methodsNeural decodingArtificial neural network
• Automatic detection for bioacoustic research: a practical guide from and for biologists and computer scientists
  Recent years have seen a dramatic rise in the use of passive acoustic monitoring (PAM) for biological and ecological applications, and a corresponding increase in the volume of data generated. However, data sets are often becoming so sizable that analysing the…
  openalex Arik Kershenbaum, Çağlar Akçay, Lakshmi Babu Saheer, Alex Barnhill 等 2024-10-17 置信度 0.72 BioacousticsComputer scienceField (mathematics)Artificial intelligenceData science
• Human brain imaging with high‐density electroencephalography: Techniques and applications
  Electroencephalography (EEG) is a technique for non-invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitat…
  openalex Marco Marino, Dante Mantini 2024-08-22 置信度 0.72 ElectroencephalographyNeuroscienceNeuroimagingBrain activity and meditationComputer science
• Conceptual Integration Networks
  Conceptual integration—“blending”—is a general cognitive operation on a par with analogy, recursion, mental modeling, conceptual categorization, and framing. It serves a variety of cognitive purposes. It is dynamic, supple, and active in the moment of thinking…
  openalex Gilles Fauconnier, Mark Turner 1998-03-01 置信度 0.72 Conceptual blendingCategorizationComputer scienceFraming (construction)Cognition
• The e-Flower: A hydrogel-actuated 3D MEA for brain spheroid electrophysiology
  Traditional microelectrode arrays (MEAs) are limited to measuring electrophysiological activity in two dimensions, failing to capture the complexity of three-dimensional (3D) tissues such as neural organoids and spheroids. Here, we introduce a flower-shaped ME…
  openalex Eleonora Martinelli, Outman Akouissi, Luca Liebi, Ivan Furfaro 等 2024-10-16 置信度 0.72 SpheroidElectrophysiologyMicroelectrodeSelf-healing hydrogelsMaterials science
• Hodge Laplacian of Brain Networks
  The closed loops or cycles in a brain network embeds higher order signal transmission paths, which provide fundamental insights into the functioning of the brain. In this work, we propose an efficient algorithm for systematic identification and modeling of cyc…
  openalex D. Vijay Anand, Moo K. Chung 2023-01-03 置信度 0.72 Laplace operatorInferenceComputer scienceTheoretical computer scienceAlgorithm
• Physiological assessment of brain, cardiovascular, and respiratory changes in multimodal motor imagery brain-computer interface training
  Brain-Computer Interfaces (BCIs) can provide a non-muscular communication channel for individuals with motor impairments. When integrated with virtual reality (VR) and haptic feedback, motor imagery (MI)-based BCIs can augment the rehabilitation outcome for pa…
  openalex Evangelos Georgaras, Athanasios Vourvopoulos 2025-01-02 置信度 0.72 Brain–computer interfaceMotor imageryTraining (meteorology)Interface (matter)Physical medicine and rehabilitation
• Federated Learning with Privacy Preserving for Multi- Institutional Three-Dimensional Brain Tumor Segmentation
  BACKGROUND AND OBJECTIVES: Brain tumors are complex diseases that require careful diagnosis and treatment. A minor error in the diagnosis may easily lead to significant consequences. Thus, one must place a premium on accurately identifying brain tumors. Howeve…
  openalex Mohammed Elbachir Yahiaoui, Makhlouf Derdour, Rawad Abdulghafor, Sherzod Turaev 等 2024-12-23 置信度 0.72 Computer scienceArtificial intelligenceSegmentationConfidentialitySimilarity (geometry)
• Brain-inspired computing systems: a systematic literature review
  Abstract Brain-inspired computing is a growing and interdisciplinary area of research that investigates how the computational principles of the biological brain can be translated into hardware design to achieve improved energy efficiency. Brain-inspired comput…
  openalex Mohamadreza Zolfagharinejad, Unai Alegre-Ibarra, Tao Chen, Sachin Kinge 等 2024-06-01 置信度 0.72 Computer scienceNeuromorphic engineeringScope (computer science)Efficient energy useField (mathematics)
• [A review of functional electrical stimulation based on brain-computer interface].
  Individuals with motor dysfunction caused by damage to the central nervous system are unable to transmit voluntary movement commands to their muscles, resulting in a reduced ability to control their limbs. However, traditional rehabilitation methods have probl…
  openalex Yao Wang, Yuhan Li, Hongyan Cui, Meng Li 等 2024-08-25 置信度 0.72 Brain–computer interfaceFunctional electrical stimulationInterface (matter)StimulationNeuroscience
• Virtual reality-empowered deep-learning analysis of brain cells
  Abstract Automated detection of specific cells in three-dimensional datasets such as whole-brain light-sheet image stacks is challenging. Here, we present DELiVR, a virtual reality-trained deep-learning pipeline for detecting c-Fos + cells as markers for neuro…
  openalex Doris Kaltenecker, Rami Al-Maskari, Moritz Negwer, Luciano Hoeher 等 2024-04-22 置信度 0.72 Deep learningComputer sciencePipeline (software)VisualizationClearance
• 1924–2024: First centennial of EEG
  • Hans Berger’s first brain signal recording in 1924 initiated the field of Electroencephalography. • This review covers the evolution, impact, and future of EEG and neurophysiological techniques. • IFCN’s role in global collaboration, education, and research …
  openalex Paolo Maria Rossini, Jonathan Cole, Walter Paulus, Ulf Ziemann 等 2024-12-19 置信度 0.72 CentennialElectroencephalographyMedicinePsychologyNeuroscience
• A Spatially Diverse 2TX-3RX Galvanic-Coupled Transdural Telemetry for Tether-Less Distributed Brain–Computer Interfaces
  A near-field galvanic coupled transdural telemetry ASICs for intracortical brain-computer interfaces is presented. The proposed design features a two channels transmitter and three channels receiver (2TX-3RX) topology, which introduces spatial diversity to eff…
  openalex Chengyao Shi, Yuming He, Marios Gourdouparis, Guido Dolmans 等 2024-03-04 置信度 0.72 TelemetryBandwidth (computing)Computer scienceTransmitterTransceiver
• Machine Learning Supporting Virtual Reality and Brain–Computer Interface to Assess Work–Life Balance Conditions for Employees
  The widespread adoption of the Industry 5.0 paradigm puts people and their applications at the center of attention and, with the increasing automation and robotization of work, the need for workers to acquire new, more advanced skills increases. The developmen…
  openalex Dariusz Mikołajewski, Adrianna Piszcz, Izabela Rojek, Krzysztof Galas 2024-11-15 置信度 0.72 Virtual realityHuman–computer interactionInterface (matter)Work (physics)Brain–computer interface
• Human–computer interaction in healthcare: Comprehensive review
  Technological advancements have fundamentally transformed healthcare systems and significantly altered the interactions between medical professionals and information interfaces. This study provides a comprehensive review of the role of human–computer interacti…
  openalex Meher Langote, Saniya Saratkar, Praveen Kumar, Prateek Verma 等 2024-01-01 置信度 0.72 Health careComputer scienceHuman–computer interactionData sciencePolitical science
• Evaluation of Different Visual Feedback Methods for Brain—Computer Interfaces (BCI) Based on Code-Modulated Visual Evoked Potentials (cVEP)
  Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices using electroencephalography (EEG) signals. BCIs based on code-modulated visual evoked potentials (cVEPs) are based on visual stimuli, thus appropriate visual f…
  openalex Milán András Fodor, Hannah Herschel, Atilla Cantürk, Gernot Heisenberg 等 2024-08-22 置信度 0.72 Brain–computer interfaceVisual evoked potentialsComputer scienceVisual feedbackElectroencephalography
• Neuralite: Enabling Wireless High-Resolution Brain-Computer Interfaces
  Intracortical brain-computer interfaces (iBCIs) promise to sense brain activity at an unprecedented scale and resolution. However, unlocking this potential for practical, untethered applications remains an unsolved challenge. The major barrier is the significa…
  openalex Hongyao Liu, Junyi Wang, Lan Zhai, Yuguang Fang 等 2024-12-04 置信度 0.72 Computer scienceWirelessBrain–computer interfaceResolution (logic)Human–computer interaction
• On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds
  Fifth generation (5G) mobile communication systems have entered the stage of commercial deployment, providing users with new services, improved user experiences as well as a host of novel opportunities to various industries. However, 5G still faces many challe…
  openalex Cheng‐Xiang Wang, Xiaohu You, Xiqi Gao, Xiuming Zhu 等 2023-01-01 置信度 0.72 Key (lock)Software deploymentComputer scienceTelecommunicationsWhite paper
• Classification of Brain Tumor based on Machine Learning Algorithms: A Review
  Brain tumor classification using machine learning algorithms is pivotal for medical diagnostics, particularly in magnetic resonance imaging (MRI) analysis. This review provides a comprehensive overview of recent advancements in brain tumor classification metho…
  openalex Omran Azeez, Adnan Mohsin Abdulazeez 2024-12-29 置信度 0.72 Computer scienceMachine learningArtificial intelligenceAlgorithm
• Regenerative peripheral nerve interface free muscle graft mass and function
  BACKGROUND: Regenerative peripheral nerve interfaces (RPNIs) transduce neural signals to provide high-fidelity control of neuroprosthetic devices. Traditionally, rat RPNIs are constructed with ~150 mg of free skeletal muscle grafts. It is unknown whether large…
  openalex Yaxi Hu, Daniel C. Ursu, Racquel A. Sohasky, Ian C. Sando 等 2020-12-09 置信度 0.72 Isometric exerciseSkeletal musclePeripheralAnatomyRegeneration (biology)