Are you saying the demonstrated results are all in sample? Because this is definitely not true for out of sample data. And the GP comment implies that there is in fact a validation/holdout set.

I'm also confused by this. If everything was done properly, test results on the holdout set would've been shown. Wasnt that the case?

Yes but the input isn't an integer from 1 to 10 right? It's MRI data.

Although it seems they're only able to extract the subject of the brain activity, not any actual "pictures".

It's still a legitimate direction to pursue. Once you get to large enough training sets, it's basically the same way our own brains work. We don't perceive or remember all the details of a building - just "building, style 19B", plus a few extra generic parameters like distance, angle, color and so on. Totally manageable for deep learning to recognize, and perhaps even combine.

But unless they tested this on a single human being; doesn't this mean that we can read brains (it's just this one particular reader is bad).

I am pretty pretty sure that this is just per person. so all it does is categorize complex brain patterns of one person into 10 category numbers and then do some hula hoop to display the numbers.

From the paper, it's four people from the NSD:

« We analyzed data for four of the eight subjects who completed all imaging sessions (subj01, subj02, subj05, and subj07 »

P3 here: https://www.biorxiv.org/content/biorxiv/early/2022/11/21/202...