SOTAVerified

Brain Decoding

Motor Brain Decoding is fundamental task for building motor brain computer interfaces (BCI).

Progress in predicting finger movements based on brain activity allows us to restore motor functions and improve rehabilitation process of patients.

Papers

Showing 7180 of 118 papers

TitleStatusHype
JGAT: a joint spatio-temporal graph attention model for brain decodingCode0
Structural Similarities Between Language Models and Neural Response MeasurementsCode0
Second Sight: Using brain-optimized encoding models to align image distributions with human brain activityCode0
Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks0
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph Convolutional Network0
Multi-view and Cross-view Brain Decoding0
On the benefits of self-taught learning for brain decoding0
Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding0
Cross-view Brain Decoding0
Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FingerFlexPearson Correlation0.67Unverified
2Gradient boosted trees on Riemannian featuresPearson Correlation0.53Unverified
3Multi purpose CNNPearson Correlation0.52Unverified
4CNN-LSTMPearson Correlation0.52Unverified
5Linear regression based on band-specific ECoGPearson Correlation0.48Unverified
6Interpretable Compact CNNPearson Correlation0.45Unverified
7Switching linear modelsPearson Correlation0.43Unverified
#ModelMetricClaimedVerifiedStatus
1FingerFlexPearson Correlation0.49Unverified