http://www.cnr.it/ontology/cnr/individuo/prodotto/ID278324
Linear stability in networks of pulse-coupled neurons (Articolo in rivista)
- Type
- Label
- Linear stability in networks of pulse-coupled neurons (Articolo in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.3389/fncom.2014.00008 (literal)
- Alternative label
Simona Olmi (1,2); Alessandro Torcini (1,2); Antonio Politi (1,3) (2014)
Linear stability in networks of pulse-coupled neurons
in Frontiers in computational neuroscience
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Simona Olmi (1,2); Alessandro Torcini (1,2); Antonio Politi (1,3) (literal)
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- This article is part of the Research Topic Application of Nonlinear Analysis to the Study of Complex Systems in Neuroscience and Behavioral Research, edited by Tobias A. Mattei. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00008/abstract (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- (1) Consiglio Nazionale delle Ricerche, Istituto dei Sistemi Complessi, Sesto Fiorentino, Italy
(2) INFN--Sezione di Firenze and CSDC, Sesto Fiorentino, Italy
(3) SUPA and Institute for Complex Systems and Mathematical Biology, King's College, University of Aberdeen, Aberdeen, UK (literal)
- Titolo
- Linear stability in networks of pulse-coupled neurons (literal)
- Abstract
- In a first step toward the comprehension of neural activity, one should focus on the stability of the possible dynamical states. Even the characterization of an idealized regime, such as that of a perfectly periodic spiking activity, reveals unexpected difficulties. In this paper we discuss a general approach to linear stability of pulse-coupled neural networks for generic phase-response curves and post-synaptic response functions. In particular, we present: (1) a mean-field approach developed under the hypothesis of an infinite network and small synaptic conductances; (2) a \"microscopic\" approach which applies to finite but large networks. As a result, we find that there exist two classes of perturbations: those which are perfectly described by the mean-field approach and those which are subject to finite-size corrections, irrespective of the network size. The analysis of perfectly regular, asynchronous, states reveals that their stability depends crucially on the smoothness of both the phase-response curve and the transmitted post-synaptic pulse. Numerical simulations suggest that this scenario extends to systems that are not covered by the perturbative approach. Altogether, we have described a series of tools for the stability analysis of various dynamical regimes of generic pulse-coupled oscillators, going beyond those that are currently invoked in the literature. (literal)
- Prodotto di
- Autore CNR
- Insieme di parole chiave
Incoming links:
- Autore CNR di
- Prodotto
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
- Insieme di parole chiave di