This is accepted as a truism by the majority of neuroscientists.” [24] However, even after many years and grandiose projects, ”Yet for the most part, we still do not understand the brain’s underlying computational logic” [5]. To understand how ”computation is done”, we generalized computing [25], in close cooperation with communication [26], for biology. We understand that ”a piecemeal approach will not yield the major jumps in understanding for which the BRAIN Initiative was designed” [27]. We synthesize the available knowledge with a fresh eye and intend to leap forward in understanding neural computing, scrutinizing our knowledge pieces one by one for credibility, relation to other pieces, other disciplines (furthermore, disciplinarity itself), finding contradictions and their resolutions, defying fallacies. We show how an elementary neuronal operation carries out computing, why biological computing is by orders of magnitude more effective than the technical one, how the biological implementation enables learning, how and why do the features of the two computing systems differ.