mlsanityData to 14 Oct 2026

A Survey of fMRI to Image Reconstruction

arXiv 2502.16861 ↗First posted 24 Feb 2025cs.CVcited by 6

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Abstract (arXiv)

Functional magnetic resonance imaging (fMRI) based image reconstruction plays a pivotal role in decoding human perception, with applications in neuroscience and brain-computer interfaces. While recent advancements in deep learning and large-scale datasets have driven progress, challenges such as data scarcity, cross-subject variability, and low semantic consistency persist. To address these issues, we introduce the concept of fMRI-to-Image Learning (fMRI2Image) and present the first systematic review in this field. This review highlights key challenges, categorizes methodologies such as fMRI signal encoding, feature mapping, and image generator. Finally, promising research directions are proposed to advance this emerging frontier, providing a reference for future studies.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 36 of its 59 references that are in the map. First posted on arXiv 24 Feb 2025.

Builds on

36 of 59 references.

References · 36

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  4. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,403
  5. 2022Generative Adversarial Networkscited by 5,627
  6. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  7. 2021MLP-Mixer: An all-MLP Architecture for Visioncited by 1,446
  8. 2023Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priorscited by 160
  9. 2022Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decodingcited by 144
  10. 2015Generic decoding of seen and imagined objects using hierarchical visual featurescited by 120
  11. 2024MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Datacited by 109
  12. 2023Natural scene reconstruction from fMRI signals using generative latent diffusioncited by 97
24 more
  1. 2022Mind Reader: Reconstructing complex images from brain activitiescited by 85
  2. 2023Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activitycited by 71
  3. 2019From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRIcited by 67
  4. 2024MindBridge: A Cross-Subject Brain Decoding Frameworkcited by 66
  5. 2018BOLD5000: A public fMRI dataset of 5000 imagescited by 63
  6. 2022Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Featurescited by 63
  7. 2016Neural Encoding and Decoding with Deep Learning for Dynamic Natural Visioncited by 60
  8. 2022Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANscited by 55
  9. 2022Decoding natural image stimuli from fMRI data with a surface-based convolutional networkcited by 49
  10. 2023MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusioncited by 47
  11. 2023UniBrain: Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activitycited by 42
  12. 2024NeuroPictor: Refining fMRI-to-Image Reconstruction via Multi-individual Pretraining and Multi-level Modulationcited by 34
  13. 2021Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GANcited by 32
  14. 2024UMBRAE: Unified Multimodal Brain Decodingcited by 32
  15. 2024MindTuner: Cross-Subject Visual Decoding with Visual Fingerprint and Semantic Correctioncited by 32
  16. 2023Controllable Mind Visual Diffusion Modelcited by 30
  17. 2024NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstructioncited by 26
  18. 2023Through their eyes: multi-subject Brain Decoding with simple alignment techniquescited by 21
  19. 2024CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decodingcited by 13
  20. 2022Semantic Brain Decoding: from fMRI to conceptually similar image reconstruction of visual stimulicited by 12
  21. 2023Lite-Mind: Towards Efficient and Robust Brain Representation Networkcited by 6
  22. 2024See Through Their Minds: Learning Transferable Neural Representation from Cross-Subject fMRIcited by 5
  23. 2024Brain-Streams: fMRI-to-Image Reconstruction with Multi-modal Guidancecited by 3
  24. 2024MindShot: A Few-Shot Brain Decoding Framework via Transferring Cross-Subject Prior and Distilling Frequency Domain Knowledgecited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.

  1. 2025Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understandingcited by 34
  2. 2025VSI: Visual Subtitle Integration for Keyframe Selection to enhance Long Video Understandingcited by 1
  3. 2026SemVideo: Reconstructs What You Watch from Brain Activity via Hierarchical Semantic Guidancecited by 1
  4. 2026SODA: Sensitivity-Oriented Dynamic Acceleration for Diffusion Transformercited by 0
  5. 2026Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decodingcited by 0
  6. 2026Brain3D: EEG-to-3D Decoding of Visual Representations via Multimodal Reasoningcited by 0