In this paper we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph selforganization phenomena emerging in complex nervous systems at a mesoscale level. In our model each unit corresponds to a mber of neurons and may be roughly seen as abstracting the functional behavior exhibited by a single voxel under the fMRI imaging. In the course of the dynamics the units exchange portions of formal charge which correspond to waves of activity in the underlying microscale neuronal circuit. The geometric model s away the neuronal complexity and is mathematically tractable which allows us to establish explicit results on its ground states and the resulting charge transfer graph modeling functional graph of the network. We show that for a wide choice of parameters and geometrical set-ups our model yields a scale-free functional connectivity with exponent approaching 2 in agreement with prev...
J. Piersa, Filip Piekniewski, Tomasz Schreiber