Love it, and love the general idea of seeing more ml-like interpretations of neuroscience knowledge.
One disagreement (but maybe I should say: one addition to a good first-order approximation) is over local information: I think it includes some global information, such as sympathetic/parasympathetic level through heart beat, and that the brain may may actually use that to help construct/stabilize long range networks, such as the default node network.
Love it, and love the general idea of seeing more ml-like interpretations of neuroscience knowledge.
One disagreement (but maybe I should say: one addition to a good first-order approximation) is over local information: I think it includes some global information, such as sympathetic/parasympathetic level through heart beat, and that the brain may may actually use that to help construct/stabilize long range networks, such as the default node network.
Yes, good point! I had that in an earlier draft and then removed it for simplicity and for the other argument you’re making!