关键词: 神经元模型/
电导依赖模型/
非电导依赖模型/
TrueNorth
English Abstract
Contrastive analysis of neuron model
Xu Ling-Feng1,2,Li Chuan-Dong1,
Chen Ling1
1.College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China;
2.School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China
Fund Project:Project supported by the National Natural Science Foundation of China (Grant Nos. 61374078, 61503307), the Chongqing Research Program of Basic Research and Frontier Technology, China (Grant Nos. cstc2015jcyjBX0052, cstc2016jcyjA0261), the Fundamental Research Funds for the Central Universities, China (Grant No. XDJK2015C079), and the China Postdoctoral Science Foundation (Grant No. 2016M590854).Received Date:23 July 2016
Accepted Date:30 August 2016
Published Online:05 December 2016
Abstract:In recent years,the modeling and application of biological neurons have gained more and more attention.By now, the research on neuron models has become one of the most important branches of neuroscience.Neuron models can be used in various areas,such as biomimetic applications,memory design,logical computing,and signal processing. Furthermore,it is significant to study the dynamic characteristics of neural system by using neuron models.In this paper,the historical development of neuron models is reviewed.The neuron models have experienced three development stages.In the pioneering stage,a group of scientists laid the experimental and theoretical foundation for later research. Then,the whole study started to blossom after the publication of Hodgkin-Huxley model.In the 1970s and 1980s,various models were proposed.One of the research focuses was the simulation of neural repetitive spiking.Since the 1990s, researchers have paid more attention to setting up models that are both physiologically meaningful and computationally effective.The model put forward by Izhikevich E M has been proved to solve the problem successfully.Recently,IBM presented a versatile spiking neuron model based on 1272 ASIC gates.The model,both theoretically understandable and physically implementable,has been used as a basic building block in IBM's neuro-chip TrueNorth.In the paper, seventeen neuron models worth studying are listed.To give a more explicit explanation,these models are classified as two groups,namely conductance-dependent and conductance-independent models.The former group's goal is to model the electrophysiology of neuronal membrane,while the latter group is only to seek for capturing the input-output behavior of a neuron by using simple mathematical abstractions.The complexity and features of each model are illustrated in a chart,while the prominent repetitive spiking curves of each model are also exhibited.Five of the models are further detailed,which are the Hodgkin-Huxley model,the Integrate-and-fire model,the Fitzhugh-Nagumo model,the Izhikevich model,and the most recent model used by IBM in its neuro-chip TrueNorth.Finally,three questions are put forward at the end of the paper,which are the most important problems that today's researchers must consider when setting up new neuron models.In conclusion,the feasibility of physical implementation remains to be a challenge to all researchers. Through the aforementioned work,the authors aim to provide a reference for the study that follows,helping researchers to compare those models in order to choose the properest one.
Keywords: neuron model/
conductance-dependent model/
conductance-independent model/
TrueNorth
