[amthewiz]

Current state of the art precision has yielded insights at the sensory-motor (e.g. precise understanding of what sensory inputs cause what neural activity) and at subsystem level (e.g. what mental activity "uses" what brain subsystems). I am sure more can be done with existing technology, but a grand unified theory would probably need more precision. It is somewhat akin to attempts at finding the grand unified theory of Physics that works both at quantum and cosmological scales.

[mistermann]

I wonder if I did a poor job asking the question. What I'm getting at is, I wonder if common & reproducible brain patterns that might not formerly have been noticeable (perhaps due to a lack of precision when observing them in isolation) might reveal themselves when running assisted deep learning on a large number of subjects' results across a broad but "strictly defined" set of mental experiences that are known to produce "extreme psychological reactions". Might we discover associations (at the brain wave level) between experiences where our current understanding of the brain would not suggest there might be any? Would this type of analysis even need high precision?

Out of curiosity, was it you that downvoted my question? I'm struggling to understand what has changed on HN lately, where purely unopinionated and relevant questions are now very commonly downvoted. It's this type of thing that has caused my curiosity in this area, I'm interested in finding an underlying reason why people increasingly seem to be offended or disagree so strongly with things that only a few years ago were generally considered completely innocuous?

Perhaps it was the tone of the question? But again, I don't think that would have garnered any downvotes on HN 5 years ago - what's changed? Might we be able to detect something in brain activity that could lead us to some new paths to study to explain this widespread behavior?

Possibly related, but not necessarily:

https://en.wikipedia.org/wiki/Overfitting

https://www.quora.com/In-machine-learning-is-more-data-alway...