Form of presentation | Articles in international journals and collections |
Year of publication | 2016 |
Язык | английский |
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Gafarova Vilyuza Robertovna, author
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Bibliographic description in the original language |
F. M. Gafarov and V. R. Gafarova, The effect of the neural activity on topological properties of growing neural networks, ,Journal of Integrative Neuroscience. 15 (3), 1-15 DOI: http://dx.doi.org/10.1142/S0219635216500187 |
Annotation |
The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network?s development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences to the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network?s activity influence on its topological properties we compared it with the random growth network not depending on network?s activity. By using the random graphs theory methods for the analysis of the network?s connections structure it is shown that the growth in neural networks results in the formation of a well-known ?small-world? network.
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Keywords |
Small-world network, average shortest path lengths, node degree distribution, axon guidance, average clustering coefficient |
The name of the journal |
Journal of Integrative Neuroscience
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URL |
http://www.worldscientific.com/doi/abs/10.1142/S0219635216500187 |
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=135950&p_lang=2 |
Full metadata record |
Field DC |
Value |
Language |
dc.contributor.author |
Gafarova Vilyuza Robertovna |
ru_RU |
dc.date.accessioned |
2016-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2016-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2016 |
ru_RU |
dc.identifier.citation |
F. M. Gafarov and V. R. Gafarova, The effect of the neural activity on topological properties of growing neural networks, ,Journal of Integrative Neuroscience. 15 (3), 1-15 DOI: http://dx.doi.org/10.1142/S0219635216500187 |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=135950&p_lang=2 |
ru_RU |
dc.description.abstract |
Journal of Integrative Neuroscience |
ru_RU |
dc.description.abstract |
The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network?s development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences to the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network?s activity influence on its topological properties we compared it with the random growth network not depending on network?s activity. By using the random graphs theory methods for the analysis of the network?s connections structure it is shown that the growth in neural networks results in the formation of a well-known ?small-world? network.
|
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
Small-world network |
ru_RU |
dc.subject |
average shortest path lengths |
ru_RU |
dc.subject |
node degree distribution |
ru_RU |
dc.subject |
axon guidance |
ru_RU |
dc.subject |
average clustering coefficient |
ru_RU |
dc.title |
The effect of the neural activity on topological properties of growing neural networks |
ru_RU |
dc.type |
Articles in international journals and collections |
ru_RU |
|