mlsanityData to 14 Oct 2026

Decoding Natural Images from EEG for Object Recognition

arXiv 2308.13234 ↗First posted 25 Aug 2023cs.HC cs.AI eess.SPcited by 81

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Abstract (arXiv)

Electroencephalography (EEG) signals, known for convenient non-invasive acquisition but low signal-to-noise ratio, have recently gained substantial attention due to the potential to decode natural images. This paper presents a self-supervised framework to demonstrate the feasibility of learning image representations from EEG signals, particularly for object recognition. The framework utilizes image and EEG encoders to extract features from paired image stimuli and EEG responses. Contrastive learning aligns these two modalities by constraining their similarity. With the framework, we attain significantly above-chance results on a comprehensive EEG-image dataset, achieving a top-1 accuracy of 15.6% and a top-5 accuracy of 42.8% in challenging 200-way zero-shot tasks. Moreover, we perform extensive experiments to explore the biological plausibility by resolving the temporal, spatial, spectral, and semantic aspects of EEG signals. Besides, we introduce attention modules to capture spatial correlations, providing implicit evidence of the brain activity perceived from EEG data. These findings yield valuable insights for neural decoding and brain-computer interfaces in real-world scenarios. The code will be released on https://github.com/eeyhsong/NICE-EEG.

Key facts. Cited by 81 papers in the map (data through 14 Oct 2026). Builds on 26 of its 66 references that are in the map. First posted on arXiv 25 Aug 2023.

Builds on

26 of 66 references.

References · 26

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14 more
  1. 2022OmniVL:One Foundation Model for Image-Language and Video-Language Taskscited by 143
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Citing papers per year: 2023: 1; 2024: 12; 2025: 25; 2026: 43.

81 papers.

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  1. 2024Visual Decoding and Reconstruction via EEG Embeddings with Guided Diffusioncited by 81
  2. 2025Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Priorcited by 29
  3. 2024CognitionCapturer: Decoding Visual Stimuli From Human EEG Signal With Multimodal Informationcited by 28
  4. 2024Neuro-3D: Towards 3D Visual Decoding from EEG Signalscited by 23
  5. 2024Visual Neural Decoding via Improved Visual-EEG Semantic Consistencycited by 21
  6. 2024Self-supervised Learning for Electroencephalogram: A Systematic Surveycited by 19
  7. 2024Neural-MCRL: Neural Multimodal Contrastive Representation Learning for EEG-based Visual Decodingcited by 14
  8. 2025NeuroBridge: Bio-Inspired Self-Supervised EEG-to-Image Decoding via Cognitive Priors and Bidirectional Semantic Alignmentcited by 14
  9. 2024Mind's Eye: Image Recognition by EEG via Multimodal Similarity-Keeping Contrastive Learningcited by 12
  10. 2025CineBrain: A Large-Scale Multi-Modal Brain Dataset During Naturalistic Audiovisual Narrative Processingcited by 11
  11. 2025Towards Robust Multimodal Physiological Foundation Models: Handling Arbitrary Missing Modalitiescited by 11
  12. 2024NECOMIMI: Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion Modelscited by 10
38 more
  1. 2025Human-Aligned Image Models Improve Visual Decoding from the Braincited by 7
  2. 2026Let EEG Models Learn EEGcited by 7
  3. 2024Dual-TSST: A Dual-Branch Temporal-Spectral-Spatial Transformer Model for EEG Decodingcited by 6
  4. 2025WaveMind: Towards a Conversational EEG Foundation Model Aligned to Textual and Visual Modalitiescited by 6
  5. 2025ViEEG: Hierarchical Visual Neural Representation for EEG Brain Decodingcited by 5
  6. 2026Aligning What EEG Can See: Structural Representations for Brain-Vision Matchingcited by 5
  7. 2026HyFI: Hyperbolic Feature Interpolation for Brain-Vision Alignmentcited by 5
  8. 2024Achieving More Human Brain-Like Vision via Human EEG Representational Alignmentcited by 4
  9. 2025Unlocking In-Context Learning for Natural Datasets Beyond Language Modellingcited by 4
  10. 2025EEG2TEXT-CN: An Exploratory Study of Open-Vocabulary Chinese Text-EEG Alignment via Large Language Model and Contrastive Learning on ChineseEEGcited by 4
  11. 2025Foundation Models for Cross-Domain EEG Analysis Application: A Surveycited by 4
  12. 2026Deep Models, Shallow Alignment: Uncovering the Granularity Mismatch in Neural Decodingcited by 4
  13. 2026Subject-Aware Multi-Granularity Alignment for Zero-Shot EEG-to-Image Retrievalcited by 4
  14. 2024AI for Biomedicine in the Era of Large Language Modelscited by 3
  15. 2025A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyondcited by 3
  16. 2025Category-aware EEG image generation based on wavelet transform and contrast semantic losscited by 3
  17. 2025Transformer-based EEG Decoding: A Surveycited by 3
  18. 2025Spatial-Functional awareness Transformer-based graph archetype contrastive learning for Decoding Visual Neural Representations from EEGcited by 3
  19. 2026Learning Brain Representation with Hierarchical Visual Embeddingscited by 3
  20. 2026ZUNA: Flexible EEG Superresolution with Position-Aware Diffusion Autoencoderscited by 3
  21. 2026Autoregressive Visual Decoding from EEG Signalscited by 3
  22. 2026SATTC: Structure-Aware Label-Free Test-Time Calibration for Cross-Subject EEG-to-Image Retrievalcited by 3
  23. 2026What Are We Actually Decoding? Source Attribution for Non-Invasive Brain-to-Language Retrievalcited by 3
  24. 2025EgoBrain: Synergizing Minds and Eyes For Human Action Understandingcited by 2
  25. 2025From Pixels to Feelings: Aligning MLLMs with Human Cognitive Perception of Imagescited by 2
  26. 2026CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignmentcited by 2
  27. 2023SI-SD: Sleep Interpreter through awake-guided cross-subject Semantic Decodingcited by 1
  28. 2024Adaptive Modality Balanced Online Knowledge Distillation for Brain-Eye-Computer based Dim Object Detectioncited by 1
  29. 2025Bridging Brain with Foundation Models through Self-Supervised Learningcited by 1
  30. 20253D-Telepathy: Reconstructing 3D Objects from EEG Signalscited by 1
  31. 2025Image-to-Brain Signal Generation for Visual Prosthesis with CLIP Guided Multimodal Diffusion Modelscited by 1
  32. 2025DynaMind: Reconstructing Dynamic Visual Scenes from EEG by Aligning Temporal Dynamics and Multimodal Semantics to Guided Diffusioncited by 1
  33. 2025Decoding Visual Neural Representations by Multimodal with Dynamic Balancingcited by 1
  34. 2025Decoding Dynamic Visual Experience from Calcium Imaging via Cell-Pattern-Aware Pretrainingcited by 1
  35. 2025Unveiling Deep Semantic Uncertainty Perception for Language-Anchored Multi-modal Vision-Brain Alignmentcited by 1
  36. 2026ENIGMA: EEG-to-Image in 15 Minutes Using Less Than 1% of the Parameterscited by 1
  37. 2026Hierarchic-EEG2Text: Assessing EEG-To-Text Decoding across Hierarchical Abstraction Levelscited by 1
  38. 2026EEG2Vision: A Multimodal EEG-Based Framework for 2D Visual Reconstruction in Cognitive Neurosciencecited by 1

50 most cited of 81 All 81 (JSON)