Theory of dynamic similarity in neuronal systems

1. The techniques of dynamic similarity from the engineering science of fluid mechanics are applied to neuronal systems to suggest how to scale down critical parameters (such as numbers of constituent cells and synapses, synaptic strengths, thresholds, etc.) from naturally occurring systems to computer models. 2. The interconnectivity of a prototypical neuronal junction is defined in terms of the total number of projecting fibers, receiving cells, synapses, and directly connected cell fiber pairs. Critical derivative parameters are defined in terms of these, including: a global convergence factor, alpha ij, which is the ratio of the numbers of projecting fibers to receiving cells; and an interconnectivity completeness parameter or microscopic convergence/divergence parameter, gamma ij, which measures both the percentage of cells to which a given sending fiber projects (and the percentage of fibers from which a given cell receives) and the percentage of cell fiber combinations which are directly connected....