Spike Transmission on Diverging/Converging Neural Network and Its Implementation on a Multilevel Modeling Platform
Details
Serval ID
serval:BIB_B001201ED643
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Spike Transmission on Diverging/Converging Neural Network and Its Implementation on a Multilevel Modeling Platform
Title of the conference
Artificial Neural Networks and Machine Learning – ICANN 2012
Publisher
Springer Berlin Heidelberg
Address
Lausanne, Switzerland
ISBN
978-3-642-33268-5
978-3-642-33269-2
978-3-642-33269-2
ISSN
0302-9743
1611-3349
1611-3349
Publication state
Published
Issued date
2012
Peer-reviewed
Oui
Volume
7552
Series
Lecture Notes in Computer Science (LNCS)
Pages
272-279
Language
english
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.
Create date
04/08/2017 9:02
Last modification date
21/08/2019 5:16