Research Papers Topics
Using machine learning to read, model, and causally probe how the brain represents perception.
Brain Decoding · Independent Researcher
Brain-Diffuser turns natural scene reconstruction from fMRI signals into a concrete research object, with evidence anchors, method tradeoffs, and limits for practical use.
Brain Decoding · Independent Researcher
DreamDiffusion turns EEG-to-image generation into a concrete research object, with evidence anchors, method tradeoffs, and limits for practical use.
Brain Decoding · Independent Researcher
MinD-Vis turns fMRI-to-image reconstruction with latent diffusion into a concrete research object, with evidence anchors, method tradeoffs, and limits for practical use.
Brain2Qwerty decodes typed sentences from non-invasive brain recordings: MEG reaches 32% CER on average, EEG trails at 67%, and the best participants reach 19%.
Brain Decoding · Princeton University
MindEye maps fMRI activity into CLIP-like spaces for retrieval and diffusion reconstruction, showing state-of-the-art retrieval and image reconstruction on NSD.
BrainCause uses text-to-image generation plus an fMRI encoder to causally test what brain regions represent, cutting false-positive localizations from 73.4% to 23% across 260 visual concepts.