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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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 118 papers

TitleStatusHype
Aligning brain functions boosts the decoding of visual semantics in novel subjects—0
Lite-Mind: Towards Efficient and Robust Brain Representation NetworkCode1
Brain decoding: toward real-time reconstruction of visual perception—0
BELT:Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervision—0
Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion modelsCode0
UniBrain: Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activity—0
Memory Encoding ModelCode1
Through their eyes: multi-subject Brain Decoding with simple alignment techniques—0
Retinotopy Inspired Brain Encoding Model and the All-for-One Training Recipe—0
UniCoRN: Unified Cognitive Signal ReconstructioN bridging cognitive signals and human language—0
DreamCatcher: Revealing the Language of the Brain with fMRI using GPT Embedding—0
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
Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain ActivitiesCode1
Brain Captioning: Decoding human brain activity into images and textCode1
Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks—0
Natural scene reconstruction from fMRI signals using generative latent diffusionCode1
BrainCLIP: Bridging Brain and Visual-Linguistic Representation Via CLIP for Generic Natural Visual Stimulus DecodingCode1
Semantic Brain Decoding: from fMRI to conceptually similar image reconstruction of visual stimuliCode1
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph Convolutional Network—0
Multi-view and Cross-view Brain Decoding—0
On the benefits of self-taught learning for brain decoding—0
Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding—0
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All datasetsBCI Competition IV: ECoG to Finger MovementsStanford ECoG library: ECoG to Finger Movements

Benchmark Results

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