DocumentCode
464315
Title
Synchronization in Complex Dynamical Networks
Author
Kube, Karsten ; Herzog, Andreas ; Michaelis, Bernd ; De Lima, Ana D. ; Voigt, Thomas
Author_Institution
Inst. of Electron., Signal Process. & Commun., Otto-von-Guericke Univ., Magdeburg
fYear
2007
fDate
1-5 April 2007
Firstpage
426
Lastpage
431
Abstract
Excitatory recurrent networks, while confirmed in theory, have not been intensely studied by simulation focused on synchronization properties. In our research, we validate on the basis of complex network models, the refinement of degree and link-level deepness, which embodies principles of topological structural nature with emphasis on the relationship between the topology and the dynamics of such complex networks. Biologically plausible excitatory networks that are maintaining this structure, develop a stable synchronized pattern of activity depending on spontaneous activity and synaptic refractoriness. We show that by fixed synaptic weights the synchronous bursts of oscillatory activity are stable and involve the whole network. As a result, by investigating conditions for synchronized oscillatory activity in several types of networks, we found that ´small world´ networks with a higher proportion of long connections can sustain a higher degree of synchronization
Keywords
graph theory; neural nets; complex dynamical networks; complex network models; excitatory networks; excitatory recurrent networks; small world networks; synchronization properties; Bioinformatics; Biological system modeling; Biomembranes; Complex networks; Computational biology; Computational intelligence; Computational modeling; Equations; Neurons; Virtual manufacturing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on
Conference_Location
Honolulu, HI
Print_ISBN
1-4244-0710-9
Type
conf
DOI
10.1109/CIBCB.2007.4221253
Filename
4221253
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