From human brain fMRI to Stable Diffusion reconstructed image 🤓 Recent advancements in neuroscience and computer vision have brought us closer than ever before to a world where we can understand what someone is thinking just by reading their brain activity. In a new study, researchers propose a novel method based on a diffusion model (DM) to reconstruct images from human brain activity obtained via functional magnetic resonance imaging (fMRI). How accurate is it? The top row represents the image shown to the human, and the image below is reconstructed using a diffusion model.
The technique relies on a latent diffusion model (LDM) termed Stable Diffusion, which reduces the computational cost of DMs while preserving their high generative performance. The study shows that this new method can reconstruct high-resolution images with high fidelity in a straightforward fashion without the need for any additional training or fine-tuning of complex deep-learning models. Additionally, the researchers provide a quantitative interpretation of different LDM components from a neuroscientific perspective, allowing us to understand better the connection between computer vision models and our visual system. Overall, this study proposes a promising method for reconstructing images from human brain activity, offering a unique way to understand how the brain represents the world. Join us in exploring the exciting possibilities of mind reading!