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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 51–100 of 118 papers

TitleStatusHype
Cross-view Brain Decoding—0
Decoding and interpreting cortical signals with a compact convolutional neural network—0
Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time-series neuroimaging data—0
Decoding finger flexion from band-specific ECoG signals in humans—0
Decoding finger movements from ECoG signals using switching linear models—0
Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding—0
Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection in-hospital—0
Multi-view and Cross-view Brain Decoding—0
Natural Image Reconstruction from fMRI using Deep Learning: A Survey—0
Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction—0
On Creating A Brain-To-Text Decoder—0
On the benefits of self-taught learning for brain decoding—0
Predicting Classification Accuracy When Adding New Unobserved Classes—0
Probability Distribution Alignment and Low-Rank Weight Decomposition for Source-Free Domain Adaptive Brain Decoding—0
Reconstructing Visual Stimulus Images from EEG Signals Based on Deep Visual Representation Model—0
Reconstruction of the External Stimuli from Brain Signals—0
Retinotopy Inspired Brain Encoding Model and the All-for-One Training Recipe—0
Riemannian Geometry for the classification of brain states with intracortical brain-computer interfaces—0
SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding—0
Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks—0
Social-sparsity brain decoders: faster spatial sparsity—0
Through their eyes: multi-subject Brain Decoding with simple alignment techniques—0
Towards end-to-end optimisation of functional image analysis pipelines—0
UniBrain: Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activity—0
UniCoRN: Unified Cognitive Signal ReconstructioN bridging cognitive signals and human language—0
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding—0
ViEEG: Hierarchical Neural Coding with Cross-Modal Progressive Enhancement for EEG-Based Visual Decoding—0
Explainable Emotion Decoding for Human and Computer Vision—0
Generating Visual Stimuli from EEG Recordings using Transformer-encoder based EEG encoder and GAN—0
Gradient Hyperalignment for multi-subject fMRI data alignment—0
Hierarchical Multi-resolution Mesh Networks for Brain Decoding—0
Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features—0
High-Dimensional Classification for Brain Decoding—0
How Many Bytes Can You Take Out Of Brain-To-Text Decoding?—0
Interpretability in Linear Brain Decoding—0
Interpreting wide-band neural activity using convolutional neural networks—0
Learning Deep Temporal Representations for Brain Decoding—0
MEG Decoding Across Subjects—0
MinD-3D: Reconstruct High-quality 3D objects in Human Brain—0
MindAligner: Explicit Brain Functional Alignment for Cross-Subject Visual Decoding from Limited fMRI Data—0
MindFormer: Semantic Alignment of Multi-Subject fMRI for Brain Decoding—0
MindSemantix: Deciphering Brain Visual Experiences with a Brain-Language Model—0
MindShot: Brain Decoding Framework Using Only One Image—0
Mixed-norm Regularization for Brain Decoding—0
Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)—0
Functional Magnetic Resonance Imaging data augmentation through conditional ICACode0
Extracting representations of cognition across neuroimaging studies improves brain decodingCode0
Domain Adaptation-Enhanced Searchlight: Enabling classification of brain states from visual perception to mental imageryCode0
Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for Cognitive and Psychiatric ApplicationsCode0
Spurious reconstruction from brain activityCode0
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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