GoKawiil
Tech News
Scientists led by Michal Irani at the Weizmann Institute built an AI 'brain decoder' that analyzes fMRI scans to reconstruct images a person is viewing. The system was trained on high-resolution public brain scan data from eight subjects and uses a diffusion model to generate visual recreations of what the person saw, with the work presented at two recent conferences.
Researchers led by Michal Irani at the Weizmann Institute built an AI system that reconstructs images a person is viewing from their fMRI brain scans, aiming for closer matches in structure and content than prior decoders. The system uses two coupled models—a decoder that splits predictions into image structure and content, and an encoder that predicts brain activity from images—trained together to refine outputs via a diffusion model. About 70% of training images were never actually shown to subjects in a scanner, since the encoder generated synthetic brain-activity pairings for them.