Eeg Decoding
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Benchmarks
CWL EEG/fMRI Dataset
Most implemented
Deep learning with convolutional neural networks for EEG decoding and visualization
Transformer-based Spatial-Temporal Feature Learning for EEG Decoding
Physics-inform attention temporal convolutional network for EEG-based motor imagery classification
DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
Papers
ProCA: Progressive Contrastive Alignment for Robust EEG Visual Decoding
Electroencephalogram (EEG) visual decoding aims to recover visual semantics from non-invasive neural time-series signals, for which robust alignment between noisy neural responses and stable semantic representations is k…
Contrastive LearningEeg DecodingEEG Decoding Using CNN and LSTM Network
Motor imagery (MI) brain--computer interfaces (BCIs) have emerged as a promising approach for establishing flexible communication pathways between the human brain and external devices , particularly for individuals affec…
Eeg DecodingEEG-PRIME: Prototype-Aligned Representation Learning with Multi-Level Conditioning for EEG Decoding
Electroencephalography (EEG) decoding models often generalize poorly across datasets and subjects due to domain shifts in acquisition protocols and individual neurophysiology. We propose EEG-PRIME, a two-stage EEG founda…
Representation LearningEmotion RecognitionEeg DecodingCoCoT-EEG: Contrastive-Pretrained Multiscale Convolutional Transformer for EEG Decoding
Self-supervised pretrained foundation models (FM) have shown early promise for non-invasive electroencephalogram (EEG) decoding applications. Many recent large-scale models converged on the approach of tokenizing raw EEG…
Contrastive LearningEeg DecodingTowards Robust EEG Decoding Based on Riemannian Self-Attention
Brain-Computer Interface (BCI) based on electroencephalography (EEG) enables direct interaction between the brain and external environments and has significant applications in assistive technologies, medical rehabilitati…
Eeg DecodingDual-Stream EEG Decoding for 3D Visual Perception
This paper explores a novel brain decoding model for 3D shape perception through a dual pathway architecture mirroring biological vision. Our bio-inspired approach implements separate decoding modules for object identity…
3D ReconstructionBrain DecodingEeg Decoding