Spike transmission on diverging/converging neural network and its implementation on a multilevel modeling platform

Authors:
Yoshiyuki Asai;Alessandro E. P. Villa
Affiliations:
Open Biology Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan,Neuroheuristic Research Group, HEC-ISI, University of Lausanne, Switzerland;INSERM UMRS 836/ Université/ Joseph Fourier, Grenoble, France,Neuroheuristic Research Group, HEC-ISI, University of Lausanne, Switzerland
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

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Abstract

A multiple layers neural network characterized by diverging/converging projections between successive layers activated by an external spatio-temporal input pattern in presence of stochastic background activities was considered. In the previous studies we reported the properties and performance of spike information transmission in the network depending on neuron model type, inputed information type and background activity level. The models were rather simple and can be more detailed and bigger in size for further investigation. Based on a technology developed in the integrated physiology, we have implemented the network model on PhysioDesigner, a platform for multilevel mathematical modeling of physiological systems. This article instructs a use case of PhysioDesigner and the assistive function of PhysioDesigner especially for large size neuronal network modeling is demonstrated.