http://www.cnr.it/ontology/cnr/individuo/prodotto/ID18610
Vesicular mechanisms and estimates of firing probability in a network of spiking neurons (Articolo in rivista)
- Type
- Label
- Vesicular mechanisms and estimates of firing probability in a network of spiking neurons (Articolo in rivista) (literal)
- Anno
- 2003-01-01T00:00:00+01:00 (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Rodriguez R.; Lansky P.; Di Maio V. (literal)
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- Impact Factor e altri parametri valutati in base al 2002 poiche' non sono disponibili i dati 2003 (literal)
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- Physica D- ISSN: 0167-2789, Total Cites: 7164, ImpactFactor(2002): 1.655, ImmediacyIndex: 0.210, Articles in 2002: 186, Citing Half life: 8.9, Ranking basato su Impact Factor: 5 su 156 riviste \"Applied Math.\" (literal)
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- Neural model of small neural network which simulate the releasing synaptic activity and its effect on behaviour of the network. Particular attention is given to the syncronization of the neural activity. (literal)
- Note
- ISI Web of Science (WOS) (literal)
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- 1.Centre de Physique Théorique, CNRS-Luminy, Faculté des Sciences de Luminy, Université de la Méditerranée, Case 907, F-13288 Marseille Cedex 09, France
b Institute of Physiology, Academy of Sciences of the Czech Republic, Videnska 1083, 142
2. Institute of Physiology of Czech Academi of Sciences, Prague, The Czech Rep.
3. Istituto di Cibernetica E. Caianiello, CNR, Pozzuoli, Naples, Italy (literal)
- Titolo
- Vesicular mechanisms and estimates of firing probability in a network of spiking neurons (literal)
- Abstract
- MorrisLecar neurons. The synaptic transmission is described at the vesicular level. Random number of activated vesicles
at synaptic contacts and random quanta of released transmitter are considered. These fluctuations are applied in a form of
inhomogeneous Poisson processes, at the time scale of the spike duration. The parameters of these processes depend on the
presynaptic spiking activity and on the strength of afferent connections. It is shown how synchronization of the activity in the
network appears. A statistical analysis of spiking times is performed, showing smooth mean behavior of response frequencies.
Adiffusion approximation of the network Poissonian process is derived from which an analytical formula for firing probability
is calculated. (literal)
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