Analysis of synaptic weight distribution in an Izhikevich network

Guo, Li, Yang, Zhijun ORCID: https://orcid.org/0000-0003-2615-4297 and Zhu, Qingbao (2013) Analysis of synaptic weight distribution in an Izhikevich network. In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 24-26 Apr 2013, Bruges, Belgium.

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Abstract

Izhikevich network is a relatively new neuronal network, which consists of cortical spiking model neurons with axonal conduction delays and spike-timingdependent
plasticity (STDP) with hard bound adaptation. In this work, we use uniform and Gaussian distributions respectively to initialize the weights of all excitatory neurons. After the network undergoes a few minutes of STDP adaptation, we can see that the weights of all synapses in the network, for both initial weight distributions, form a bimodal distribution, and numerically the established distribution presents dynamic stability.

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