Title |
Organization of Excitable Dynamics in Hierarchical Biological Networks
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Published in |
PLoS Computational Biology, September 2008
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DOI | 10.1371/journal.pcbi.1000190 |
Pubmed ID | |
Authors |
Mark Müller-Linow, Claus C. Hilgetag, Marc-Thorsten Hütt |
Abstract |
This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 10 | 4% |
United States | 7 | 3% |
Germany | 4 | 2% |
Netherlands | 2 | <1% |
Australia | 2 | <1% |
Canada | 2 | <1% |
Hungary | 2 | <1% |
Spain | 1 | <1% |
Korea, Republic of | 1 | <1% |
Other | 2 | <1% |
Unknown | 194 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 64 | 28% |
Student > Ph. D. Student | 52 | 23% |
Student > Master | 23 | 10% |
Professor | 18 | 8% |
Professor > Associate Professor | 17 | 7% |
Other | 38 | 17% |
Unknown | 15 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 58 | 26% |
Physics and Astronomy | 31 | 14% |
Neuroscience | 27 | 12% |
Computer Science | 22 | 10% |
Engineering | 16 | 7% |
Other | 43 | 19% |
Unknown | 30 | 13% |