Journal of the Korean Physical Society

, Volume 71, Issue 4, pp 222–230 | Cite as

Calculation of precise firing statistics in a neural network model

  • Myoung Won ChoEmail author


A precise prediction of neural firing dynamics is requisite to understand the function of and the learning process in a biological neural network which works depending on exact spike timings. Basically, the prediction of firing statistics is a delicate manybody problem because the firing probability of a neuron at a time is determined by the summation over all effects from past firing states. A neural network model with the Feynman path integral formulation is recently introduced. In this paper, we present several methods to calculate firing statistics in the model. We apply the methods to some cases and compare the theoretical predictions with simulation results.


Neural network model Neural network dynamics Computational methods 


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Copyright information

© The Korean Physical Society 2017

Authors and Affiliations

  1. 1.Department of Global Medical ScienceSungshin Women’s UniversitySeoulKorea

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