Original Research ARTICLE
The energy coding of a structural neural network based on the Hodgkin–Huxley model
- 1East China University of Science and Technology, China
Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the cortex network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.
Keywords: neural energy coding, energy distribution, Synchronous oscillation, negative energy, structural neural networks
Received: 30 Aug 2017;
Accepted: 15 Feb 2018.
Edited by:Yu-Guo Yu, Fudan University, China
Copyright: © 2018 Zhu, Wang and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Rubin Wang, East China University of Science and Technology, Shanghai, China, firstname.lastname@example.org