I'm pretty sure this kind of thing has been done before, at least very lofi images. Maybe not in "high-resolution", but I really question the scientific value o

I'm pretty sure this kind of thing has been done before, at least very lofi images. Maybe not in "high-resolution", but I really question the scientific value of doing so.. it must necessarily be hallucinating details, similar to the common criticisms of upsampling networks. There is no way we are reading brain activity at sufficient details to reconstruct a "true" image directly from the data without a lot of inductive bias. There isn't even evidence that such data exists. (that at the lowest level brain activity actually corresponds to image-related detailed information). The most we have afaik is proof that certain neurons in the optical pathways respond to certain types of lines. I'm interested in being corrected on this point. But roughly inverting some relationship with random seeds of a generative network sounds like pretty iffy methodology to me. At most it's probably categorizing the brain activity and generating a random image based on that. (still cool of course! I'm just doubting that the high resolution images contain information that really reflects brain activity, that fact that this is possible is still a neat trick) I'm basing this criticism on the linked Vice article though, haven't read the paper yet admittedly.