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Electroencephalogram (EEG)
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Electroencephalogram (EEG) is a method of recording brain activity using electrophysiological indexes. When the brain is active, a large number of postsynaptic potentials generated synchronously by neurons are formed after summation. It records the changes of electric waves during brain activity and is the overall reflection of the electrophysiological activities of brain nerve cells on the surface of cerebral cortex or scalp. Brain waves originate from the postsynaptic potential of the apical dendrites of pyramidal cells. The formation of synchronous rhythm of EEG is also related to the activity of nonspecific projection system of cortex and thalamus. EEG is the basic theoretical research of brain science. EEG monitoring is widely used in its clinical application.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Aligning Humans and Robots via Reinforcement Learning from Implicit Human Feedback
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding
CATVis: Context-Aware Thought Visualization
An Automated Classifier of Harmful Brain Activities for Clinical Usage Based on a Vision-Inspired Pre-trained Framework
eegFloss: A Python package for refining sleep EEG recordings using machine learning models
DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
AGTCNet: A Graph-Temporal Approach for Principled Motor Imagery EEG Classification
The time course of visuo-semantic representations in the human brain is captured by combining vision and language models
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Cross-Modal Epileptic Signal Harmonization: Frequency Domain Mapping Quantization for Pre-training a Unified Neurophysiological Transformer
Efficient and faithful reconstruction of dynamical attractors using homogeneous differentiators
On using AI for EEG-based BCI applications: problems, current challenges and future trends
Leveraging Transfer Learning and User-Specific Updates for Rapid Training of BCI Decoders
Exploring EEG Indicators to Evaluate Listening Difficulties in Noisy Environments
A Silent Speech Decoding System from EEG and EMG with Heterogenous Electrode Configurations
Differences in Neurovascular Coupling in Patients with Major Depressive Disorder: Evidence from Simultaneous Resting-State EEG-fNIRS
CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm
PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
Brain2Vec: A Deep Learning Framework for EEG-Based Stress Detection Using CNN-LSTM-Attention
MMME: A Spontaneous Multi-Modal Micro-Expression Dataset Enabling Visual-Physiological Fusion
Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA
Self-Calibrating BCIs: Ranking and Recovery of Mental Targets Without Labels
The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities
SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models
Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task
Decoding Saccadic Eye Movements from Brain Signals Using an Endovascular Neural Interface
Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms
Novel software for continuous wavelet analysis enable EEG real-time analysis on portable computers
Neural Responses to Affective Sentences Reveal Signatures of Depression
Sub-Scalp EEG for Sensorimotor Brain-Computer Interface
StARS DCM: A Sleep Stage-Decoding Forehead EEG Patch for Real-time Modulation of Sleep Physiology
Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
EEG Foundation Models for BCI Learn Diverse Features of Electrophysiology
Large Language Models for EEG: A Comprehensive Survey and Taxonomy
EEG2TEXT-CN: An Exploratory Study of Open-Vocabulary Chinese Text-EEG Alignment via Large Language Model and Contrastive Learning on ChineseEEG
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