DocumentCode :
2773337
Title :
Bistable properties of a memory-related gene regulatory network
Author :
Nido, Gonzalo S. ; Williams, Joanna M. ; Benuskova, Lubica
Author_Institution :
Dept. of Comput. Sci., Univ. of Otago, Dunedin, New Zealand
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
6
Abstract :
Long-term potentiation (LTP) is a long-lasting enhancement in signal transmission between two neurons, and represents a widely accepted experimental model for long-term memory processes. Although it is now clear that the maintenance of LTP requires new gene transcription, little is known on the genetic mechanisms underlying these changes. We assume that an LTP-related gene regulatory network has two equilibrium states in terms of gene expression levels which correspond to a pre- and post-LTP states. This network is shifted from the first to the latter by means of a perturbation, which experimentally corresponds to the high-frequency stimulus necessary to induce LTP in vivo. Based on this assumption and by means of modeling the transcriptional regulation with weight matrices, we study the properties of the main LTP-related network recently proposed in [1]. First, we classify the LTP-related genes according to their relevance to the bistable dynamic output of the network. In addition, we demonstrate how the LTP gene regulatory network architecture holds a higher tendency towards bistable behaviours than we should expect of a random network.
Keywords :
genetics; matrix algebra; LTP-related gene regulatory network; bistable properties; gene transcription; genetic mechanisms; long-term potentiation; memory-related gene regulatory network; random network; signal transmission; weight matrices; Gene expression; In vivo; Maintenance engineering; Network topology; Neurons; Proteins; Biology and genetics; Computational neuroscience; Systems theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
ISSN :
2161-4393
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
Type :
conf
DOI :
10.1109/IJCNN.2012.6252588
Filename :
6252588
Link To Document :
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