A comparison of learning abilities of spiking networks with different spike timing-dependent plasticity forms

International Conference on Computer Simulation in Physics and Beyond 2015

物理学;计算机科学

Sboev, Alexander^1,2 ; Vlasov, Danila^1 ; Serenko, Alexey^2 ; Rybka, Roman^2 ; Moloshnikov, Ivan^2

MEPhI National Research Nuclear University, Moscow, Russia^1

NRC Kurchatov Institute, Moscow, Russia^2

关键词: Comparison of performance;    Integrate and fires;    Learning abilities;    Learning process;    Neuron model;    Spike timing dependent plasticities;    Spiking networks;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/681/1/012013/pdf
DOI  :  10.1088/1742-6596/681/1/012013

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

A study of possibility to model the learning process on base of different forms of timing-dependent plasticity (STDP) was performed. It is shown that the learning ability depends on the choice of spike pairing scheme and the type of input signal used for learning. The comparison of performance of several STDP rules along with several neuron models (leaky integrate-and-fire, static, Izhikevich and Hodgkin-Huxley) was carried out using the NEST simulator. The combinations of input signal and STDP spike pairing scheme, which demonstrate the best learning abilities, were extracted.