Personally, I haven’t seen any need to consider it. Explaining the sensation of consciousness is like explaining why a bell doesn’t sound like the color red. What’s more interesting to me is to explain what function it serves in a brain, and does that function really require resonating quantum states?
Resonators can be:
1/ Over damped.
2/ Critically damped.
3/ Under damped.
Which can be measured as a Q value.
Usually some positive feedback is needed for oscillation:
1/ A small amount of positive feedback will just boost the Q value. (Regeneration)
2/ A large amount of positive feedback will set the system oscillating.
3/ In some cases positive feedback can cause hysteresis where the system locks in one state or another rather than oscillate.
If the gain of the thing providing the positive feedback increases with amplitude then the amplitude of oscillation will increase until the system slams into some physical constraint, voltage, energy limitations, whatever.
If the gain is exactly constant with amplitude (difficult in real physical systems)
then an oscillation will continue with whatever amplitude it started with.
If the gain decreases with amplitude the the system will oscillate at some moderate amplitude where the loop gain around the system becomes exactly 1.
And it can get even more complicated than that when there are other temporal aspects involved.
I have internalized much of Grossberg’s ideas on his ART models. I see that as a good approximation of how HTM responds to inputs - resonating with known inputs. HTM adds that it resonates with known sequences.
As far as comparison to the traditional resonance theory - a good starting point is to think of it as a piano where the closest matching string starts to sing out as long as the input sound is present.
That model only gets you so far in understanding as the piano is a fully parallel system, where neural networks mix the various internal representations together.
So - how is it different? When you apply the input it tries to respond but perhaps the resonance is poor as some stronger learned pattern is trying to respond even though it really is a poor match.
A key feature is that patterns that are not a good match get tired and fade out, allowing the weaker but better match patterns to assert themselves and resonate. Habituation.
This is the adaptive part of the ART name.
Naturally, there is a learning model that goes with all this.
This is the very first time I encountered a system that searches through its internal representations to find a good match.
You may find his instar and outstar neurons to be strange but on reflection - it does capture the key biological features necessary for his model.
Even if you are fully invested in HTM theory there is much to be learned reading Grossberg’s works - It is like learning a new language - it may help you better understand your mother tongue.
He has been doing this stuff forever and really knows his neuroscience.
If you are interested here are some links to check out:
Thanks, @bitking. Joe in the video did such a poor job explaining ART (bringing up panpsychism, proto consciousness, and quantum resonance fields) that I didn’t actually take the time to look into it any further. I see that the theory is not so “woo woo” after all. Definitely looks worth digging into further.
I’m starting to look into this. Grossberg recently published a book Conscious Mind, Resonant Brain: How Each Brain Makes a Mind If others are interested we could perhaps share notes.