Impact Factor 3.566

The Frontiers in Neuroscience journal series is the 1st most cited in Neurosciences

Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Neurosci. | doi: 10.3389/fnins.2018.00122

The energy coding of a structural neural network based on the Hodgkin–Huxley model

 Zhenyu Zhu1,  Rubin Wang1* and Fengyun Zhu1
  • 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

Reviewed by:

Jan Lauwereyns, Kyushu University, Japan
Huaguang Gu, Tongji 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, rbwang@163.com