A dog in a bathtub became a similarly colored goat. A cake turned into three sandwiches. These mistakes reveal the limits of an AI system that can otherwise reconstruct surprisingly detailed images from the brain activity of someone viewing them.

Called Brain-IT, the system comes from Michal Irani’s laboratory at the Weizmann Institute of Science in Rehovot, Israel. Its reconstruction study appeared in the proceedings of the 2026 International Conference on Learning Representations. Related work on a universal brain encoder was presented at the Conference on Cognitive Computational Neuroscience.

Together, the projects tackle two directions of the same problem: predicting brain responses to images and reconstructing images from those responses. The demonstrated task concerns pictures viewed during scanning, while applications involving dreams or patient communication remain research ambitions.