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
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
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
Group-level Brain Decoding with Deep LearningCode1
Cross-view Brain Decoding0
Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques0
Natural Image Reconstruction from fMRI using Deep Learning: A Survey0
A case study on profiling of an EEG-based brain decoding interface on Cloud and Edge servers0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FingerFlexPearson Correlation0.67Unverified
2Gradient boosted trees on Riemannian featuresPearson Correlation0.53Unverified
3CNN-LSTMPearson Correlation0.52Unverified
4Multi purpose CNNPearson 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