Same thing as the brain pretty much, except we have root control over the NN in a way we don't with the brain. To my knowledge, some angles have been explored.

Same thing as the brain pretty much, except we have root control over the NN in a way we don't with the brain. To my knowledge, some angles have been explored. Finding which inputs maximally stimulate indiv neurons, and tracing that up the chain. There was a fantastic article that did this on ImageNet - the takeaway was that neurons adjacent to the input encode sharp, basic features (like edges), and "higher-level" ones encode more nuanced stuff (textures, fur, wheels). Then ablations, as you mentioned. And finally, rerunning the same training data on differently sized + shaped architectures. AI systems are missing at least one level of complexity. All neurons in a NN layer fire simultaneously, unlike brain neurons, which trigger each other async.