MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion

Yizhuo Lu, Changde Du, Qiongyi Zhou, Dianpeng Wang, Huiguang He*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Reconstructing visual stimuli from brain recordings has been a meaningful and challenging task. Especially, the achievement of precise and controllable image reconstruction bears great significance in propelling the progress and utilization of brain-computer interfaces. Despite the advancements in complex image reconstruction techniques, the challenge persists in achieving a cohesive alignment of both semantic (concepts and objects) and structure (position, orientation, and size) with the image stimuli. To address the aforementioned issue, we propose a two-stage image reconstruction model called MindDiffuser1. In Stage 1, the VQ-VAE latent representations and the CLIP text embeddings decoded from fMRI are put into Stable Diffusion, which yields a preliminary image that contains semantic information. In Stage 2, we utilize the CLIP visual feature decoded from fMRI as supervisory information, and continually adjust the two feature vectors decoded in Stage 1 through backpropagation to align the structural information. The results of both qualitative and quantitative analyses demonstrate that our model has surpassed the current state-of-the-art models on Natural Scenes Dataset (NSD). The subsequent experimental findings corroborate the neurobiological plausibility of the model, as evidenced by the interpretability of the multimodal feature employed, which align with the corresponding brain responses.

Original languageEnglish
Title of host publicationMM 2023 - Proceedings of the 31st ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages5899-5908
Number of pages10
ISBN (Electronic)9798400701085
DOIs
Publication statusPublished - 26 Oct 2023
Event31st ACM International Conference on Multimedia, MM 2023 - Ottawa, Canada
Duration: 29 Oct 20233 Nov 2023

Publication series

NameMM 2023 - Proceedings of the 31st ACM International Conference on Multimedia

Conference

Conference31st ACM International Conference on Multimedia, MM 2023
Country/TerritoryCanada
CityOttawa
Period29/10/233/11/23

Keywords

  • brain-computer interface (bci)
  • controlled image reconstruction
  • fmri
  • probabilistic diffusion model

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