Looks interesting, but as another user pointed out not particularly novel (aside from the decoder model being used). One thing I wish these studies did is to test these models on subjects that weren’t used for training of the model, to see if these methods generalize to several people (or at least a few-shot training/testing on new subjects). I do actually like the idea of using latent diffusion models for these tasks, as long-term our brain does not store perfect reconstruction of images.

Modern machine learning is really an amalgamation of older disciplines (signal processing, control theory, optimization, estimation theory, etc…). One example is the LASSO algorithm was originally developed for signal processing applications. So to get to your question, it’d be impossible to capture its scope! Topics like adaptive signal processing, optimal signal processing, image processing, pattern recognition, and estimation & detection theory are all traditional signal processing topics that have merged into the AI field.