Yeah! Super super noisy - and maybe harder than you've described. At least you might overhear some meetings with a stethoscope-on-building approach.

That's kind of the motivation for trying a no-MEG, (comparatively) large dataset, ML approach - it strikes me as exactly the kind of problem to which transformer models might be particularly well-suited, if it's even possible to find a hint of anything in that noise at all.