Hey, I don't have any specific papers. And I think neuroscience makes it sound fancier than it maybe is in reality. But the primary concepts are spaced-repetition, elaborative encoding, and active recall. And the main focus is really on reducing friction with putting these practices into play.
I think the reality of neuroscience and behavioral research at this point in time is that it's just really difficult to translate neuro -> behavior and thought processes. There are some decently well researched learning methods, such as spaced repetition and enhancing depth of knowledge but we don't have a totally clear picture on why these things work well.
There are suspicions of course, such as how deeper knowledge of a subject is able to integrate the information into more parts of the network, but afaik the actual biochemical mechanisms and how those translate into network dynamics and recall for a lot of memory and learning functions are still fairly unknown.
If anyone knows of some solid studies (preferably using humans) I would be more than happy to read them, learning and memory is a fascinating area of neuroscience.
Hopefully, with relatively new equipment that allows more precise realtime brain sensing, we should have more insightful research in the years to come.[0] But the issue of defining learning itself will remain thorny.
