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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 61–70 of 118 papers

Title	Date	Tasks	Status	Hype
DreamCatcher: Revealing the Language of the Brain with fMRI using GPT Embedding	Jun 16, 2023	Brain DecodingDecoder	—Unverified	0
JGAT: a joint spatio-temporal graph attention model for brain decoding	Jun 3, 2023	Brain DecodingFunctional Connectivity	CodeCode Available	0
Structural Similarities Between Language Models and Neural Response Measurements	Jun 2, 2023	Brain Decoding	CodeCode Available	0
Second Sight: Using brain-optimized encoding models to align image distributions with human brain activity	Jun 1, 2023	Brain DecodingImage Reconstruction	CodeCode Available	0
Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities	May 26, 2023	Brain DecodingBrain Visual Reconstruction	CodeCode Available	1
Brain Captioning: Decoding human brain activity into images and text	May 19, 2023	Brain DecodingDepth Estimation	CodeCode Available	1
Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks	May 15, 2023	Brain DecodingTransfer Learning	—Unverified	0
Natural scene reconstruction from fMRI signals using generative latent diffusion	Mar 9, 2023	Brain Computer InterfaceBrain Decoding	CodeCode Available	1
BrainCLIP: Bridging Brain and Visual-Linguistic Representation Via CLIP for Generic Natural Visual Stimulus Decoding	Feb 25, 2023	Brain DecodingImage Generation	CodeCode Available	1
Semantic Brain Decoding: from fMRI to conceptually similar image reconstruction of visual stimuli	Dec 13, 2022	Brain DecodingImage Reconstruction	CodeCode Available	1

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All datasets BCI Competition IV: ECoG to Finger Movements Stanford ECoG library: ECoG to Finger Movements

Benchmark Results

#	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