I can only tell you how I do it in my design, to the extent that it’s complete. In the brain, there is this predictive coding idea: https://en.wikipedia.org/wiki/Predictive_coding, where prediction is supposed to be measured. Of course, that’s far far from fully known, and I am not a neuroscientist.
My critique was about how introspection is actually practiced: not very deeply. I specifically said that it’s the key for theoretical design, which is what I do. And it’s just a matter of degree, all thinking can be considered introspection, you just have to dig a lot deeper to understand GI. Deeper than in any other problem by a mile.
So GI is currently unmeasurable in living critters?
Predictive coding as implemented in flat (single layer) HTM is a lot closer to pattern completion, with a report if the system is unable to form a match. You need a much larger system with sub-cortical supervision to do any sort of matching of sensation to selecting an appropriate action.
Assuming that I have that larger system - are you saying that GI is just selecting the best learned response for the current collection of inputs? Simple pattern matching?
Not on intra-brain level, obviously. But we have all kinds IQ tests 
I posted on that, it’s actually the reverse of conventional predictive coding. Where prediction is supposed to inhibit the input, while in HTM it reinforces the input to fire the neuron. So, that’s obviously wrong if you want build a hierarchy:
We’ll just have to disagree on that. I don’t think I can get you off that subcortical horse :).
Of course not. Pattern discovery (unsupervised), not pattern matching (supervised). Where pattern is a set of matching inputs, so it all comes down to the definition of match. Mine is different