Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16186
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Guo, Li
Yang, Zhijun
Graham, Bruce
Zhang, Daqiang
Contact Email: b.p.graham@stir.ac.uk
Title: Characterisation of information flow in an Izhikevich network
Editors: Huang, T
Zeng, Z
Li, C
Leung, CS
Citation: Guo L, Yang Z, Graham B & Zhang D (2012) Characterisation of information flow in an Izhikevich network In: Huang T, Zeng Z, Li C, Leung CS (ed.) Neural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part I, Berlin Heidelberg: Springer. 19th International Conference on Neural Information Processing, ICONIP 2012, 12.11.2012 - 15.11.2012, Doha, Qatar, pp. 392-400.
Issue Date: 2012
Series/Report no.: Lecture Notes in Computer Science, 7663
Conference Name: 19th International Conference on Neural Information Processing, ICONIP 2012
Conference Dates: 2012-11-12T00:00:00Z
Conference Location: Doha, Qatar
Abstract: Izhikevich network is a relatively new neuronal network, which consists of cortical spiking model neurons with axonal conduction delays and spike-timing-dependent plasticity (STDP). In this network polychrony is identified which is neither synchrony nor asynchrony, but a phenomenon of occurence and transmission of a sequence of firing patterns with specific inter-firing intervals. In this work we use van Rossum's distance to measure the correlation between spike trains issued by neurons in a testing polychromous group and analyse the characterisation of information flow in the group of the network.
Type: Conference Paper
Status: Book Chapter: publisher version
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
URI: http://hdl.handle.net/1893/16186
URL: http://link.springer.com/chapter/10.1007/978-3-642-34475-6_47#
Affiliation: Nanjing Normal University, China
University of Stirling
Computing Science - CSM Dept
Nanjing Normal University, China

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