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eeg

GeneTech 知识引擎共收录 127 篇相关科研实体，横跨 8 个垂直领域。数据来自 OpenAlex、arXiv、Crossref、PubMed、Europe PMC 等公开学术源，全部可溯源到原文。

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代表性文献（按质量分排序，前 60 条）

• Mental Workload and Performance in Motor Imagery-Based Brain-Computer Interfaces: A Rapid Systematic Review
  2026 · 仿生智能 · Motor Imagery based Brain-Computer Interfaces have emerged as a promising non invasive tool for neuromotor rehabilitation, offering users the ability to control external devices through the modulation of sensorimotor rhy…
• Yang et al. 2025 — A multi-day and high-quality EEG dataset for motor imagery brain-computer interface
  2026 · 仿生智能 · A multi-day, high-quality EEG dataset for motor imagery brain-computer interface research comprising 51 healthy subjects performing motor imagery tasks across three sessions on different days. The dataset includes two ex…
• EEG data offline and online during motor imagery for standing and sitting
  2026 · 仿生智能 · This dataset comprises electroencephalographic recordings from 32 participants performing motor imagery tasks during sit-to-stand and stand-to-sit transitions in both offline and online brain-computer interface (BCI) par…
• EEG data offline and online during motor imagery for standing and sitting
  2026 · 仿生智能 · This dataset comprises electroencephalographic recordings from 32 participants performing motor imagery tasks during sit-to-stand and stand-to-sit transitions in both offline and online brain-computer interface (BCI) par…
• BCI-FIT: A customization protocol for communication brain-computer interface systems.
  2026 · 仿生智能 · BCI-FIT is a customization protocol dataset for non-implantable communication brain-computer interface (cBCI) systems, comprising EEG recordings from five participants with speech and/or physical impairments due to amyot…
• BCI-FIT: A customization protocol for communication brain-computer interface systems.
  2026 · 仿生智能 · BCI-FIT is a customization protocol dataset for non-implantable communication brain-computer interface (cBCI) systems, comprising EEG recordings from five participants with speech and/or physical impairments due to amyot…
• Yang et al. 2025 — A multi-day and high-quality EEG dataset for motor imagery brain-computer interface
  2026 · 仿生智能 · A multi-day, high-quality EEG dataset for motor imagery brain-computer interface research comprising 51 healthy subjects performing motor imagery tasks across three sessions on different days. The dataset includes two ex…
• Alljoined-1.6M
  2026 · 仿生智能 · Alljoined-1.6M is a large-scale EEG dataset comprising over 1.6 million trials of neural responses to rapid serial visual presentation (RSVP) of natural images from the THINGS database. Recorded from 20 healthy adult par…
• Alljoined-1.6M
  2026 · 仿生智能 · Alljoined-1.6M is a large-scale EEG dataset comprising over 1.6 million trials of neural responses to rapid serial visual presentation (RSVP) of natural images from the THINGS database. Recorded from 20 healthy adult par…
• Electroencephalographic (EEG) Dataset of Stress-Induced Auditory Stimulation for Event-Related Oscillation Analysis and Machine Learning Classification
  2026 · 仿生智能 · This dataset contains 45 electroencephalographic (EEG) recordings acquired during an experimental protocol designed to induce stress corresponding to 15 subjects. The comparison conditions are relaxation and white noise …
• Electroencephalographic (EEG) Dataset of Stress-Induced Auditory Stimulation for Event-Related Oscillation Analysis and Machine Learning Classification
  2026 · 仿生智能 · This dataset contains 45 electroencephalographic (EEG) recordings acquired during an experimental protocol designed to induce stress corresponding to 15 subjects. The comparison conditions are relaxation and white noise …
• LASD-Net: Experimental Results and Pre-trained Model for SSVEP-BCI Cross-Subject Classification
  2026 · 仿生智能 · This dataset contains the full experimental results, pre-trained model weights, and supporting files for LASD-Net (Lightweight Attention-Enhanced Siamese Deep Neural Network with Harmonic Subband Decomposition and Meta-L…
• LASD-Net: Experimental Results and Pre-trained Model for SSVEP-BCI Cross-Subject Classification
  2026 · 仿生智能 · This dataset contains the full experimental results, pre-trained model weights, and supporting files for LASD-Net (Lightweight Attention-Enhanced Siamese Deep Neural Network with Harmonic Subband Decomposition and Meta-L…
• Neurophenomenology of Mild Cognitive Impairment: a Longitudinal EEG and Experience Report Study
  2026 · 脑科学 · Alzheimer's disease (AD) is the most common cause of dementia and represents one of the greatest challenges facing ageing societies worldwide (Alzheimer’s Association, 2022). The progressive deterioration of memory, exec…
• Neural complexity as a marker of pain perception
  2026 · 空间计算 · 1. Background When receiving a sensory stimulus, the brain possesses the capacity to balance information processing between chaos and redundancy, amplification and quenching, differentiation and integration(Kurth et al.,…
• Alcohol Use Disorder Prediction from EEG Using AI Algorithms: A Comprehensive Review
  2026 · 医疗人工智能 · Alcohol Use Disorder (AUD) is a relapsing condition, which is chronic and causes severe neurological, behavioral, and social disabilities. The traditional methods of diagnosing AUD are mainly based on the self-reported q…
• Alcohol Use Disorder Prediction from EEG Using AI Algorithms: A Comprehensive Review
  2026 · 医疗人工智能 · Alcohol Use Disorder (AUD) is a relapsing condition, which is chronic and causes severe neurological, behavioral, and social disabilities. The traditional methods of diagnosing AUD are mainly based on the self-reported q…
• Pre-registration: Cue-Interval Leakage and an External-Electrode Confound Control in Inner-Speech EEG Decoding — a Pre-Specified Re-evaluation of OpenNeuro ds003626
  2026 · 仿生智能 · This deposit contains a pre-registration, not results. Two versions are included. Version 1 was written before the dataset's published data descriptor had been read. Version 2 supersedes it and is the analysis plan; both…
• Pre-registration: Cue-Interval Leakage and an External-Electrode Confound Control in Inner-Speech EEG Decoding — a Pre-Specified Re-evaluation of OpenNeuro ds003626
  2026 · 仿生智能 · This deposit contains a pre-registration, not results. Two versions are included. Version 1 was written before the dataset's published data descriptor had been read. Version 2 supersedes it and is the analysis plan; both…
• Pre-registration: A Leakage-Audited Re-evaluation of Inner-Speech Decoding on OpenNeuro ds003626, with an External-Electrode Confound Control
  2026 · 仿生智能 · This is a pre-registration, not a results paper. It fixes in advance every analysis decision for a re-evaluation of inner-speech EEG decoding on the open dataset OpenNeuro ds003626 (Nieto et al., Scientific Data 9:52, 20…
• Diagnosing Motor-Imagery BCI Failure: A Three-Step Diagnostic Framework
  2026 · 仿生智能 · Version 3.1.0. This version adds the four figures. The v3.0.0 PDF carried the captions but not the artwork, because the manuscript is prepared with figures supplied as separate files, which is what the journal requires a…
• Diagnosing Motor-Imagery BCI Failure: A Three-Step Diagnostic Framework
  2026 · 仿生智能 · Version 3.0.0. This version corresponds to the manuscript submitted to the Journal of Neuroscience Methods on 2 August 2026. It supersedes v2.0.0, which described a two-step framework evaluated on a single cohort. The fr…
• The Quantum Neuroperceptual Horizon Hypothesis (QNPH): From Quantum Information to Neural Representation and Conscious Experience
  2026 · 仿生智能 · The Neuroperceptual Horizon Hypothesis proposes that the range of physical phenomena an organism can functionally incorporate into experience is constrained by receptors, transduction mechanisms, neural integration, lear…
• The Quantum Neuroperceptual Horizon Hypothesis (QNPH): From Quantum Information to Neural Representation and Conscious Experience
  2026 · 仿生智能 · The Neuroperceptual Horizon Hypothesis proposes that the range of physical phenomena an organism can functionally incorporate into experience is constrained by receptors, transduction mechanisms, neural integration, lear…
• Neuroperceptual Horizon Hypothesis: A Theoretical Framework for the Technological Expansion of Human Perception and Remote Exploration of the Universe
  2026 · 仿生智能 · Human experience of the universe is constrained not only by physical distance but also by the biological characteristics of the systems through which the brain acquires, processes, and integrates information. Humans do n…
• Neuroperceptual Horizon Hypothesis: A Theoretical Framework for the Technological Expansion of Human Perception and Remote Exploration of the Universe
  2026 · 仿生智能 · Human experience of the universe is constrained not only by physical distance but also by the biological characteristics of the systems through which the brain acquires, processes, and integrates information. Humans do n…
• Multi-source domain generalization with few-shot calibration for cross-dataset EEG state classification under proxy labels
  2026 · 仿生智能 · Repository. This archive is the versioned software and results companion to the manuscript "Multi-Source Domain Generalization with Few-Shot Calibration for Cross-Dataset EEG Hypnosis Depth Classification under Proxy Lab…
• Multi-Source Domain Generalization with Few-Shot Calibration for Cross-Dataset EEG Hypnosis Depth Classification under Proxy Labels
  2026 · 仿生智能 · Repository. This archive is the versioned software and results companion to the manuscript "Multi-Source Domain Generalization with Few-Shot Calibration for Cross-Dataset EEG Hypnosis Depth Classification under Proxy Lab…
• Personalized Brain Language Models for Context-Aware Neural Signal Interpretation
  2026 · 仿生智能 · Abstract: The efficacy of Brain–Computer Interfaces (BCIs) is often limited by the inherent variability in neural representations across individuals and the generalized nature of current decoding models. While significan…
• Personalized Brain Language Models for Context-Aware Neural Signal Interpretation
  2026 · 仿生智能 · Abstract: The efficacy of Brain–Computer Interfaces (BCIs) is often limited by the inherent variability in neural representations across individuals and the generalized nature of current decoding models. While significan…
• Classification of Mental Arithmetic States Using Heterogeneous Multi-Relational Graph Neural Networks on EEG Signals
  2026 · 仿生智能 · Electroencephalography (EEG) provides a non-invasive window into cognitive states, yet accurate detection of cognitive load during mental arithmetic remains challenging due to the non-stationary, nonlinear, and subject-d…
• Classification of Mental Arithmetic States Using Heterogeneous Multi-Relational Graph Neural Networks on EEG Signals
  2026 · 仿生智能 · Electroencephalography (EEG) provides a non-invasive window into cognitive states, yet accurate detection of cognitive load during mental arithmetic remains challenging due to the non-stationary, nonlinear, and subject-d…
• Security for Brain-Computer User Interface Requirements: A Review on Machine Learning-Driven Security Frameworks
  2026 · 仿生智能 · Brain–Computer Interfaces (BCIs) enable direct communication between the human brain and external devices by converting neural signals into actionable commands. With rapid adoption in healthcare, assistive technologies, …
• Security for Brain-Computer User Interface Requirements: A Review on Machine Learning-Driven Security Frameworks
  2026 · 仿生智能 · Brain–Computer Interfaces (BCIs) enable direct communication between the human brain and external devices by converting neural signals into actionable commands. With rapid adoption in healthcare, assistive technologies, …
• SSVEP SLR Protocol
  2026 · 仿生智能 · Retrospective registered protocol for a systematic review titled: "Contradictory Evidence on the Superiority of Deep Learning over Traditional Machine Learning for SSVEP Classification: A Systematic Review" Authors: Roll…
• Sleep Onset as Fibonacci Necessity Depth Collapse: EEG Band Boundaries as φ-Structured Attractors and the F(8) = 21 Hz Tipping Point
  2026 · 脑科学 · Fibonacci Causal Loop Theory (FCLT) predicts that systems governed by depth-2 necessity recursion S(n) = S(n−1) + S(n−2) will exhibit Fibonacci-structured transition thresholds and φ-ratio boundary conditions. This paper…
• Sleep onset as Fibonacci necessity-depth collapse: tests of four φ-structured frequency predictions in waking EEG, sleep transition, and cognitive-load gamma
  2026 · 脑科学 · Fibonacci Causal Loop Theory (FCLT) predicts that necessity-governed systems exhibit Fibonacci-structured transition thresholds and φ-ratio boundary conditions (P42). We test four such predictions against published EEG a…
• Sleep Onset as Fibonacci Necessity Depth Collapse: EEG Band Boundaries as φ-Structured Attractors and the F(8) = 21 Hz Tipping Point
  2026 · 脑科学 · Fibonacci Causal Loop Theory (FCLT) predicts that systems governed by depth-2 necessity recursion S(n) = S(n−1) + S(n−2) will exhibit Fibonacci-structured transition thresholds and φ-ratio boundary conditions. This paper…
• Neural Feedback Optimization Theory
  2026 · 脑科学 · Neural Feedback Optimization Theory addresses the critical need for dynamic, real-time interaction between intelligent learning environments and individual cognitive processes. By establishing a rigorous theoretical fram…
• Neural Feedback Optimization Theory
  2026 · 脑科学 · Neural Feedback Optimization Theory addresses the critical need for dynamic, real-time interaction between intelligent learning environments and individual cognitive processes. By establishing a rigorous theoretical fram…
• LongevityCommon
  2026 · 隐私计算与数据要素 · Aging, codified in ICD-11 (code XT9T “Ageing-related,” 2018; code MG2A “Ageing-associated decline in intrinsic capacity,” 2025), requires integrative biomarker frameworks that extend beyond individual epigenetic clocks a…
• LongevityCommon
  2026 · 隐私计算与数据要素 · Aging, codified in ICD-11 (code XT9T “Ageing-related,” 2018; code MG2A “Ageing-associated decline in intrinsic capacity,” 2025), requires integrative biomarker frameworks that extend beyond individual epigenetic clocks a…
• Personalized BCI Calibration Using Stable Individual Peak Frequency
  2025 · 仿生智能 · CORRECTED AND EXPANDED VERSION – DECEMBER 2025 This manuscript supersedes the previous version uploaded on November 25, 2025 (DOI: 10.5281/zenodo.17388037). The initial version analyzed only three subjects (A01T-A03T) an…
• Discovery of a Universal Harmonic Structure in REM Sleep EEG: The Brain as a Toroidal Resonator
  2025 · 脑科学 · The complex, quasi-chaotic dynamics of the human brain during Rapid Eye Movement (REM) sleep remain a profound puzzle. We report the discovery of a previously undocumented fine structure within the REM sleep electroencep…
• Discovery of a Universal Harmonic Structure in REM Sleep EEG: The Brain as a Toroidal Resonator
  2025 · 脑科学 · The complex, quasi-chaotic dynamics of the human brain during Rapid Eye Movement (REM) sleep remain a profound puzzle. We report the discovery of a previously undocumented fine structure within the REM sleep electroencep…
• Proprioception as Phase Integrity_ A Structured Resonance Reframe of Embodied Self-Localization
  2025 · 具身智能 · Supersession Note — April 30, 2026 This CODES-era work is an exploratory predecessor and is no longer the canonical statement of the author’s program. It has been superseded by the identity-persistence stack: Universal I…
• Proprioception as Phase Integrity_ A Structured Resonance Reframe of Embodied Self-Localization
  2025 · 具身智能 · Supersession Note — April 30, 2026 This CODES-era work is an exploratory predecessor and is no longer the canonical statement of the author’s program. It has been superseded by the identity-persistence stack: Universal I…
• Neuro-Dimensional Architecture of Brain Waves: A Unified Theoretical Framework for Macroscopic Neural Dynamics
  2025 · 类脑计算 · We propose a novel theoretical synthesis, the theory of Neuro-Dimensional Ar- chitecture (NDA), which reframes canonical brain wave activity (Delta, Theta, Al- pha, Beta, Gamma) as emergent, low-dimensional projections o…
• Neuro-Dimensional Architecture of Brain Waves: A Unified Theoretical Framework for Macroscopic Neural Dynamics
  2025 · 类脑计算 · We propose a novel theoretical synthesis, the theory of Neuro-Dimensional Ar- chitecture (NDA), which reframes canonical brain wave activity (Delta, Theta, Al- pha, Beta, Gamma) as emergent, low-dimensional projections o…
• Yang et al. 2025 — A multi-day and high-quality EEG dataset for motor imagery brain-computer interface
  2026 · 仿生智能 · A multi-day, high-quality EEG dataset for motor imagery brain-computer interface research comprising 51 healthy subjects performing left and right hand motor imagery tasks across three sessions. The dataset includes 59 E…
• Checkerboard m-sequence-based c-VEP dataset from
  2026 · 仿生智能 · A derivative EEG dataset containing checkerboard m-sequence-based code-modulated visual evoked potential (c-VEP) recordings from 16 healthy participants across 8 sessions. This dataset is derived from the source dataset …
• Shi et al. 2025 — HEFMI-ICH: a hybrid EEG-fNIRS motor imagery dataset for brain-computer interface in intracerebral hemorrhage
  2026 · 仿生智能 · HEFMI-ICH is a hybrid EEG-fNIRS motor imagery dataset designed for brain-computer interface applications in intracerebral hemorrhage rehabilitation. The dataset comprises 37 participants (17 healthy controls and 20 ICH p…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study P)
  2026 · 仿生智能 · BigP3BCI Study P is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects across 2 sessions each, using a 9x8 character grid spelling paradigm. The dataset contains 32-channel E…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study D)
  2026 · 仿生智能 · BigP3BCI Study D is a P300-based brain-computer interface dataset comprising EEG recordings from 17 healthy subjects performing a 6x6 character grid speller task. The dataset contains single-session recordings acquired a…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study Q)
  2026 · 仿生智能 · BigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study R)
  2026 · 仿生智能 · BigP3BCI Study R is a P300-based brain-computer interface dataset comprising EEG recordings from 20 subjects performing a 9x8 multi-face character grid speller task across two sessions. This derivative dataset is part of…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study S2)
  2026 · 仿生智能 · BigP3BCI Study S2 is a P300-based brain-computer interface dataset comprising EEG recordings from 24 healthy subjects performing a 9x8 house/tool visual speller paradigm. The dataset contains 32-channel EEG data sampled …
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study O)
  2026 · 仿生智能 · BigP3BCI Study O is a P300-based brain-computer interface dataset comprising EEG recordings from 18 ALS subjects across 2 sessions each, using a 9x8 character grid with supervised and checkerboard stimulus paradigms. The…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study J)
  2026 · 仿生智能 · BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI co…
• Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study J)
  2026 · 仿生智能 · BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI co…

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