well if it learns by remembering sets of features and matching new stimuli against this "database" than we can talk about distance functions in associative memo

well if it learns by remembering sets of features and matching new stimuli against this "database" than we can talk about distance functions in associative memory, and the problem of optimization reduces to a problem of matching (as well as generalizing, i.e constructing abstract representations from simpler ones, as in "chunking"). brain priors would be the distributed representations of stimulus-response pairs stored in memory