Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/41796

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dc.contributor.authorFerreira, Flora José Rochapor
dc.contributor.authorErlhagen, Wolframpor
dc.contributor.authorBicho, Estelapor
dc.date.accessioned2016-05-25T15:33:19Z-
dc.date.available2016-05-25T15:33:19Z-
dc.date.issued2016-
dc.identifier.citationFerreira, F., Erlhagen, W., & Bicho, E. (2016). Multi-bump solutions in a neural field model with external inputs. Physica D-Nonlinear Phenomena, 326, 32-51. doi: 10.1016/j.physd.2016.01.009-
dc.identifier.issn0167-2789por
dc.identifier.urihttps://hdl.handle.net/1822/41796-
dc.description"Available online 3 March 2016"por
dc.description.abstractWe study the conditions for the formation of multiple regions of high activity or “bumps” in a one-dimensional, homogeneous neural field with localized inputs. Stable multi-bump solutions of the integro-differential equation have been proposed as a model of a neural population representation of remembered external stimuli. We apply a class of oscillatory coupling functions and first derive criteria to the input width and distance, which relate to the synaptic couplings that guarantee the existence and stability of one and two regions of high activity. These input-induced patterns are attracted by the corresponding stable one-bump and two-bump solutions when the input is removed. We then extend our analytical and numerical investigation to NN-bump solutions showing that the constraints on the input shape derived for the two-bump case can be exploited to generate a memory of N>2N>2 localized inputs. We discuss the pattern formation process when either the conditions on the input shape are violated or when the spatial ranges of the excitatory and inhibitory connections are changed. An important aspect for applications is that the theoretical findings allow us to determine for a given coupling function the maximum number of localized inputs that can be stored in a given finite interval.por
dc.description.sponsorshipThe work received financial support from FCT through a PhD grant (SFRH/BD/41179/2007) and from the EU-FP7 ITN project NETT: Neural Engineering Transformative Technologies (nr. 289146).por
dc.language.isoengpor
dc.publisherElsevier 1por
dc.relationinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F41179%2F2007/PTpor
dc.rightsopenAccesspor
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/por
dc.subjectPattern formationpor
dc.subjectWorking memorypor
dc.subjectIntegro-differential equationpor
dc.subjectTransient external inputpor
dc.subjectPersistent population activitypor
dc.subjectPersistent neural population activitypor
dc.titleMulti-bump solutions in a neural field model with external inputspor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S016727891530035Xpor
sdum.publicationstatusinfo:eu-repo/semantics/publishedVersionpor
oaire.citationStartPage32por
oaire.citationEndPage51por
oaire.citationTitlePhysica D: Nonlinear Phenomenapor
oaire.citationVolume326por
dc.identifier.doi10.1016/j.physd.2016.01.009por
dc.subject.fosCiências Naturais::Matemáticaspor
dc.subject.fosCiências Naturais::Outras Ciências Naturaispor
dc.subject.wosScience & Technologypor
sdum.journalPhysica D-Nonlinear Phenomenapor
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals
CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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