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Автор Cohen, O.
Автор Keselman, A.
Автор Moses, E.
Автор Rodríguez Martínez, M.
Автор Soriano, J.
Автор Tlusty, T.
Дата выпуска 2010-01-01
dc.description Cooperative effects in neural networks appear because a neuron fires only if a minimal number m>1 of its inputs are excited. The multiple inputs requirement leads to a percolation model termed quorum percolation. The connectivity undergoes a phase transition as m grows, from a network-spanning cluster at low m to a set of disconnected clusters above a critical m. Both numerical simulations and the model reproduce the experimental results well. This allows a robust quantification of biologically relevant quantities such as the average connectivity and the distribution of connections p<sub>k</sub> from different neural densities.
Формат application.pdf
Издатель Institute of Physics Publishing
Копирайт Europhysics Letters Association
Название Quorum percolation in living neural networks
Тип lett
DOI 10.1209/0295-5075/89/18008
Electronic ISSN 1286-4854
Print ISSN 0295-5075
Журнал EPL (Europhysics Letters)
Том 89
Первая страница 18008
Последняя страница 18013
Аффилиация Cohen, O.; Department of Physics of Complex Systems, Weizmann Institute of Science - Rehovot 76100, Israel
Аффилиация Keselman, A.; Department of Physics of Complex Systems, Weizmann Institute of Science - Rehovot 76100, Israel
Аффилиация Moses, E.; Department of Physics of Complex Systems, Weizmann Institute of Science - Rehovot 76100, Israel
Аффилиация Rodríguez Martínez, M.; Department of Physics of Complex Systems, Weizmann Institute of Science - Rehovot 76100, Israel
Аффилиация Soriano, J.; Department of Physics of Complex Systems, Weizmann Institute of Science - Rehovot 76100, Israel; Departament d'ECM. Facultat de Física, Universitat de Barcelona - Av. Diagonal 647, 08028 Barcelona, Spain, EU
Аффилиация Tlusty, T.; Department of Physics of Complex Systems, Weizmann Institute of Science - Rehovot 76100, Israel
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