Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network

Frontiers in Cellular Neuroscience
Lianchun YuYuguo Yu

Abstract

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. ...Continue Reading

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Citations

Oct 28, 2019·Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism·Matilda K DahlqvistMartin J Lauritzen
Jul 19, 2019·Frontiers in Neuroscience·Jeffrey L KrichmarJames L Olds
Jul 28, 2020·Nature Reviews. Drug Discovery·Stephen C CunnaneMark J Millan
Nov 30, 2019·Frontiers in Neuroscience·Guosheng YiJiang Wang

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