Optimal Channel Efficiency in a Sensory Network

TL;DR

This paper demonstrates that in the Kinouchi-Copelli model, the entropy of avalanche lifetimes maximizes alongside the dynamic range, indicating optimal information processing linked to dynamical rules rather than network size.

Contribution

It reveals that the entropy of avalanche lifetimes peaks with the dynamic range across various topologies, highlighting the importance of dynamical rules for efficient sensory networks.

Findings

Entropy of avalanche lifetimes maximizes with dynamic range

Optimization occurs across all tested topologies

Proper temporal matching of neuronal states is key

Abstract

We show that the entropy of the distribution of avalanche lifetimes in the Kinouchi-Copelli model always achieves a maximum jointly with the dynamic range. This is noteworthy and nontrivial because while the dynamic range is an equilibrium average measure of the sensibility of a sensory system to a stimulus, the entropy of relaxation times is a purely dynamical quantity, independent of the stimulus rate, that can be interpreted as the efficiency of the network seen as a communication channel. The newly found optimization occurs for all topologies we tested, even when the distribution of avalanche lifetimes itself is not a power-law and when the entropy of the size distribution of avalanches is not concomitantly maximized, strongly suggesting that dynamical rules allowing a proper temporal matching of the states of the interacting neurons is the key for achieving good performance in information processing, rather than increasing the number of available units.