The FitzHugh-Nagumo model: Firing modes with time-varying parameters & parameter estimation

Rose T. Faghih, Ketan Savla, Munther A. Dahleh, Emery N. Brown

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, we revisit the issue of the utility of the FitzHugh-Nagumo (FHN) model for capturing neuron firing behaviors. It has been noted (e.g., see [6]) that the FHN model cannot exhibit certain interesting firing behaviors such as bursting. We illustrate that, by allowing time-varying parameters for the FHN model, one could overcome such limitations while still retaining the low order complexity of the FHN model. We also highlight the utility of the FHN model from an estimation perspective by presenting a novel parameter estimation method that exploits the multiple time scale feature of the FHN model, and compare the performance of this method with the Extended Kalman Filter through illustrative examples.

    Original languageEnglish (US)
    Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    Pages4116-4119
    Number of pages4
    DOIs
    StatePublished - 2010
    Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
    Duration: Aug 31 2010Sep 4 2010

    Publication series

    Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

    Other

    Other2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    Country/TerritoryArgentina
    CityBuenos Aires
    Period8/31/109/4/10

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Signal Processing
    • Health Informatics

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