So I would say the core thrust of this idea is essentially about resonance. Acoustics enters the picture in that one key way we traditionally analyze resonance is we analyze the acoustic properties of the signal medium/context — so I’d define the meaning of ‘neural acoustics’ in relation to ‘neural resonance’. I don’t think I was very clear about this conceptual hierarchy in my writeup.

I’m not sure if resonance applies to the other structured dynamical contexts you mentioned. I’d have to think about that.

*You bring up the issue of acoustics being a more-or-less ‘deterministic science’, whereas the brain is highly dynamical or contextual. I think that’s actually a strength of this theory, that a key part of how the brain accomplishes some types of computation is by changing the profile of what patterns do resonate within certain regions. But yeah, you’d need some sort of notation or structure that could allow for this…

I feel like I should toss in the obligatory disclaimer that modeling specific neural circuits is always going to be more predictive than mid-level abstractions like neural resonance. But until we get to that point on a large scale, I think there’s quantitative and qualitative information to be extracted via the lens of resonance/acoustics. Or maybe a better way to put it would be, they’re efficient variables for predicting functional dynamics or typing neural circuits.

(Kinda reminds me of IBM’s cat cortex simulation, which included a virtual EEG so they could check ‘sanity check’ their emergent statistical behavior… pretty amazing! Even though they definitely oversold how their sim complexity compared to a real brain…)

You and I have been thinking along parallel lines! Resonance in the brain? Exactly right!

Check out this on-line book I am working on…

http://sharp.bu.edu/~slehar/HRezBook/HRezBook.html

And this paper…

http://sharp.bu.edu/~slehar/ConstructiveAspect/ConstructiveAspect.html

Steve Lehar
slehar@gmail.com