Vibrational resonance in a scale-free network with different coupling schemes

Show simple item record

dc.contributor.author Agaoglu, Sukriye Nihal
dc.contributor.author Calim, Ali
dc.contributor.author Hövel, Philipp
dc.contributor.author Ozer, Mahmut
dc.contributor.author Uzuntarla, Muhammet
dc.date.accessioned 2020-02-13T14:55:50Z
dc.date.available 2020-02-13T14:55:50Z
dc.date.issued 2018-10-05
dc.identifier.citation Agaoglu, S. N., Calim, A., Hövel, P., Ozer, M. and Uzuntarla, M. (2019) 'Vibrational resonance in a scale-free network with different coupling schemes', Neurocomputing, 325, pp. 59-66. doi: 10.1016/j.neucom.2018.09.070 en
dc.identifier.volume 325 en
dc.identifier.startpage 59 en
dc.identifier.endpage 66 en
dc.identifier.issn 0925-2312
dc.identifier.uri http://hdl.handle.net/10468/9646
dc.identifier.doi 10.1016/j.neucom.2018.09.070 en
dc.description.abstract We investigate the phenomenon of vibrational resonance (VR) in neural populations, whereby weak low-frequency signals below the excitability threshold can be detected with the help of additional high-frequency driving. The considered dynamical elements consist of excitable FitzHugh–Nagumo neurons connected by electrical gap junctions and chemical synapses. The VR performance of these populations is studied in unweighted and weighted scale-free networks. We find that although the characteristic network features – coupling strength and average degree – do not dramatically affect the signal detection quality in unweighted electrically coupled neural populations, they have a strong influence on the required energy level of the high-frequency driving force. On the other hand, we observe that unweighted chemically coupled populations exhibit the opposite behavior, and the VR performance is significantly affected by these network features whereas the required energy remains on a comparable level. Furthermore, we show that the observed VR performance for unweighted networks can be either enhanced or worsened by degree-dependent coupling weights depending on the amount of heterogeneity. en
dc.description.sponsorship Deutsche Forschungsgemeinschaft (DFG in the framework of Collaborative Research Center 910) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Elsevier en
dc.relation.uri http://www.sciencedirect.com/science/article/pii/S0925231218311512
dc.rights © 2018 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC BY-NC-ND 4.0 licence. en
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/ en
dc.subject Vibrational resonance en
dc.subject Weighted networks en
dc.subject Chemical synapses en
dc.subject Gap junctions en
dc.title Vibrational resonance in a scale-free network with different coupling schemes en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Philipp Hövel, School Of Mathematical Sciences, University College Cork, Cork, Ireland. +353-21-490-3000 Email: philipp.hoevel@ucc.ie en
dc.internal.availability Full text available en
dc.check.info Access to this article is restricted until 24 months after publication by request of the publisher. en
dc.check.date 2020-10-05
dc.date.updated 2020-02-13T14:49:04Z
dc.description.version Accepted Version en
dc.internal.rssid 460208412
dc.contributor.funder Deutsche Forschungsgemeinschaft en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Neurocomputing en
dc.internal.copyrightchecked Yes
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress philipp.hoevel@ucc.ie en


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

© 2018 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC BY-NC-ND 4.0 licence. Except where otherwise noted, this item's license is described as © 2018 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC BY-NC-ND 4.0 licence.
This website uses cookies. By using this website, you consent to the use of cookies in accordance with the UCC Privacy and Cookies Statement. For more information about cookies and how you can disable them, visit our Privacy and Cookies statement