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