The goal was set decades ago: ”The ultimate aim of computational neuroscience is to explain how electrical and chemical signals are used in the brain to represent and process information” [14]. Today, computational neuroscience turned into introducing mathematical models, slightly or not related to reality, giving up entirely the above goal. The worst inheritances of neuroscience are the static view from anatomy and classical physiology; omitting to revisit the primary hypotheses in light of new research results periodically; applying the abstractions of classical science (single speed, isolated, pair-wise, instant interactions in a homogeneous and isotropic infinite medium) to biological materials without revisiting their validity. We agree that ”the basic structural units of the nervous system are individual neurons” [2], but we are also aware that neurons ”are linked together by dynamically changing constellations of synaptic weights” and ”cell assemblies are best understood in light of their output product” [15, 16], so we also model multiple neurons.