A stochastic multi-scale model of electrical function in normal and depleted ICC networks

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dc.contributor.author Gao, Jerry en
dc.contributor.author Du, Peng en
dc.contributor.author Archer, Rosalind en
dc.contributor.author O'Grady, Gregory en
dc.contributor.author Gibbons, SJ en
dc.contributor.author Farrugia, G en
dc.contributor.author Cheng, Leo en
dc.contributor.author Pullan, Andrew en
dc.date.accessioned 2012-03-15T19:29:24Z en
dc.date.issued 2011 en
dc.identifier.citation IEEE Transactions on Biomedical Engineering 58(12 PART 2):3451-3455 2011 en
dc.identifier.issn 0018-9294 en
dc.identifier.uri http://hdl.handle.net/2292/14445 en
dc.description.abstract Multi-scale modeling has become a productive strategy for quantifying interstitial cells of Cajal (ICC) network structure-function relationships, but the lack of large-scale ICC network imaging data currently limits modeling progress. The SNESIM (Single Normal Equation Simulation) algorithm was utilized to generate realistic virtual images of small real wild-type (WT) and 5-HT2B-receptor knockout (Htr2b−/−) mice ICC networks. Two metrics were developed to validate the performance of the algorithm: (i) network density, which is the proportion of ICC in the tissue; (ii) connectivity, which reflects the degree of connectivity of the ICC network. Following validation, the SNESIM algorithm was modified to allow variation in the degree of ICC network depletion. ICC networks from a range of depletion severities were generated, and the electrical activity over these networks was simulated. The virtual ICC networks generated by the original SNESIM algorithm were similar to that of their real counterparts. The electrical activity simulations showed that the maximum current density magnitude increased as the network density increased. In conclusion, the SNESIM algorithm is an effective tool for generating realistic virtual ICC networks. The modified SNESIM algorithm can be used with simulation techniques to quantify the physiological consequences of ICC network depletion at various physical scales. en
dc.publisher IEEE en
dc.relation.ispartofseries IEEE Transactions on Biomedical Engineering en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from http://www.sherpa.ac.uk/romeo/issn/0018-9294/ en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title A stochastic multi-scale model of electrical function in normal and depleted ICC networks en
dc.type Journal Article en
dc.identifier.doi 10.1109/TBME.2011.2164248 en
pubs.issue 12 en
pubs.begin-page 3451 en
pubs.volume 58 en
dc.rights.holder Copyright: IEEE en
dc.identifier.pmid 21843981 en
pubs.end-page 3455 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Article en
pubs.elements-id 258499 en
pubs.org-id Bioengineering Institute en
pubs.org-id ABI Associates en
pubs.org-id Engineering en
pubs.org-id Engineering Admin en
pubs.org-id Engineering Science en
pubs.org-id Medical and Health Sciences en
pubs.org-id School of Medicine en
pubs.org-id Surgery Department en
pubs.record-created-at-source-date 2011-07-11 en
pubs.dimensions-id 21843981 en


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