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 111–118 of 118 papers

Title	Date	Tasks	Status
High-Dimensional Classification for Brain Decoding	Apr 10, 2015	Brain DecodingClassification	—Unverified
Deep learning of fMRI big data: a novel approach to subject-transfer decoding	Jan 31, 2015	Brain DecodingDecoder	—Unverified
Learning Deep Temporal Representations for Brain Decoding	Dec 23, 2014	Brain DecodingGeneral Classification	—Unverified
MEG Decoding Across Subjects	Apr 16, 2014	Brain DecodingEnsemble Learning	—Unverified
Mixed-norm Regularization for Brain Decoding	Mar 14, 2014	Brain DecodingERP	—Unverified
Discriminative Functional Connectivity Measures for Brain Decoding	Feb 23, 2014	Brain DecodingFunctional Connectivity	—Unverified
Decoding finger flexion from band-specific ECoG signals in humans	Jun 28, 2012	Brain Computer InterfaceBrain Decoding	—Unverified
Decoding finger movements from ECoG signals using switching linear models	Mar 6, 2012	Brain Decoding	—Unverified

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#	Model	Metric	Claimed	Verified	Status
1	FingerFlex	Pearson Correlation	0.67	—	Unverified
2	Gradient boosted trees on Riemannian features	Pearson Correlation	0.53	—	Unverified
3	Multi purpose CNN	Pearson Correlation	0.52	—	Unverified
4	CNN-LSTM	Pearson Correlation	0.52	—	Unverified
5	Linear regression based on band-specific ECoG	Pearson Correlation	0.48	—	Unverified
6	Interpretable Compact CNN	Pearson Correlation	0.45	—	Unverified
7	Switching linear models	Pearson Correlation	0.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FingerFlex	Pearson Correlation	0.49	—	Unverified