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dc.contributor.authorGoodfellow, M
dc.contributor.authorGlendinning, P
dc.date.accessioned2016-04-08T08:33:06Z
dc.date.issued2013-08-14
dc.description.abstractWe investigate the dynamic mechanisms underlying intermittent state transitions in a recently proposed neural mass model of epilepsy. A low dimensional model is constructed, which preserves two key features of the neural mass model, namely (i) coupling between oscillators and (ii) heterogeneous proximity of these oscillators to a bifurcation between distinct limit cycles. We demonstrate that state transitions due to intermittency occur in the abstract model. This suggests that there is a general bifurcation mechanism responsible for this behaviour and that this is independent of the precise form of the evolution equations. Such abstractions of neural mass models allow a deeper insight into underlying dynamic and physiological mechanisms, and also allow the more efficient exploration of large scale brain dynamics in disease.en_GB
dc.description.sponsorshipMG acknowledges funding from the EPSRC through a postdoctoral prize fellowship.en_GB
dc.identifier.citationVol. 3, article 17en_GB
dc.identifier.doi10.1186/2190-8567-3-17
dc.identifier.urihttp://hdl.handle.net/10871/21017
dc.language.isoenen_GB
dc.publisherBioMed Central /SpringerOpenen_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pubmed/23945016en_GB
dc.rightsOpen access. © M. Goodfellow, P. Glendinning; licensee Springer 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_GB
dc.titleMechanisms of intermittent state transitions in a coupled heterogeneous oscillator model of epilepsyen_GB
dc.typeArticleen_GB
dc.date.available2016-04-08T08:33:06Z
exeter.place-of-publicationGermany
dc.descriptionThis is the final version of the article. Available from BioMed Central/SpringerOpen via the DOI in this record.en_GB
dc.identifier.journalJournal of Mathematical Neuroscienceen_GB


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