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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
Brain-aligning of semantic vectors improves neural decoding of visual stimuli—0
Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection in-hospital—0
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding—0
Data-Efficient Sleep Staging with Synthetic Time Series PretrainingCode0
Reconstructing Visual Stimulus Images from EEG Signals Based on Deep Visual Representation Model—0
FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease—0
Enhancing EEG-to-Text Decoding through Transferable Representations from Pre-trained Contrastive EEG-Text Masked Autoencoder—0
Contrastive Learning of Shared Spatiotemporal EEG Representations Across Individuals for Naturalistic Neuroscience—0
Generating Visual Stimuli from EEG Recordings using Transformer-encoder based EEG encoder and GAN—0
MinD-3D: Reconstruct High-quality 3D objects in Human Brain—0
Brain-optimized inference improves reconstructions of fMRI brain activityCode0
Aligning brain functions boosts the decoding of visual semantics in novel subjects—0
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
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
Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks—0
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph Convolutional Network—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