Metabolic energy consumption and information transmission of a two-compartment neuron model and its cortical network

The physiological structure of the brain and the morphology of its neurons result from selective pressure, the nervous system must be energy efficient. In this paper, a two compartment model consisting of dendritic and axon compartments is proposed to simulate the effects of morphology and temperature on neuronal kinetics. Based on the equivalent circuit method, we calculated the metabolic energy consumption of neurons with morphological and temperature variations. It is shown that higher temperatures increase the separation of Na+ and K+ currents in the axon, resulting in higher energy efficiency, while neuron with moderate morphological parameter is more likely to fire, but accompanied by a higher energy cost. We integrate this two-compartment model into a feedforward network to simulate changes in network energy consumption affected by neuron morphology and temperature during information propagation. It is found that moderate temperature and morphology allow stable propagation of synchronization spikes in the feedforward network and maximize the energy utilization for information transmission. In addition, we present a simple statistical method to detect the robustness of network information transmission. This paper may provide some insights for further studies on energy consumption in the cerebral cortex.