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The generation and conduction of action potentials represents a fundamentalmeans of communication in the nervous system, and is a metabolically expensiveprocess. In this paper, we investigate the energy efficiency of neural systemsin a process of transfer pulse signals with action potentials. By computersimulation of a stochastic version of Hodgkin-Huxley model with detaileddescription of ion channel random gating, and analytically solve a bistableneuron model that mimic the action potential generation with a particlecrossing the barrier of a double well, we find optimal number of ion channelsthat maximize energy efficiency for a neuron. We also investigate the energyefficiency of neuron population in which input pulse signals are representedwith synchronized spikes and read out with a downstream coincidence detectorneuron. We find an optimal combination of the number of neurons in neuronpopulation and the number of ion channels in each neuron that maximize theenergy efficiency. The energy efficiency depends on the characters of the inputsignals, e.g., the pulse strength and the inter-pulse intervals. We argue thattrade-off between reliability of signal transmission and energy cost mayinfluence the size of the neural systems if energy use is constrained.

The Optimal Size of Stochastic Hodgkin-Huxley Neuronal Systems for Maximal Energy Efficiency in Coding of Pulse Signals