This was the core premise behind my research during grad school and beyond. My favorite project — which ultimately became my dissertation — was a proposal to connect reinforcement learning algorithms, neuronal data, psychological behavior, and phenomenology. Specifically, the idea was the feeling of cognitive fatigue is a mathematical signal to ‘rest’, in which the value of rest is defined by offline mechanisms that contribute to decision-making. I proposed a connection to hippocampal replay, and was able to leverage fMRI and choice data to evaluate the hypothesis.

Zooming out of my specific work, the “best” success stories were connections across math/CS, neuro, and psych and the golden child is the dopamine model of reinforcement learning where firing patterns encode the TD prediction error

Not broad enough. Better: https://en.wikipedia.org/wiki/Calculating_Space

Doesn’t the concept of a subconscious, or inner voice, invalidate any tight analogies to Turing Machines? What logical process is putting the Fur Elise into my head (earworms etc)

I think this article is right that definitions really matter here cause one could argue “CTM is trivial, because we can describe almost any physical system as executing computations.” So we have a dual problem here—not just the difficult discussion of ‘what’s going on in minds’, but also ‘what is computation’.