Fig. 1: The neuronal network model.
From: The small world coefficient 4.8 ± 1 optimizes information processing in 2D neuronal networks
We simulated the transport of information in the networks, with their nodes represented as artificial neurons that integrate over time the current-pulse trains received as an input and produce, as an output, a discrete pattern of action potentials: in the model, the signals are represented as arrays of 0/1 (bits) (a). Information is decoded in the patterns of actions potentials: using information theory approaches and the Shannon information entropy, we obtained the information received and transmitted by each of the nodes of the networks (b).
