Improvement of computational efficiency of a biochemical plasticity model

    Research output: Other conference contributionAbstractScientific

    Abstract

    Multi-scale models in neuroscience integrate detailed neurobiological phenomena from molecular level up to network and system levels. such models are very challenging to simulate despite the availability of massively parallel
    computing systems. model order reduction (mor) is an established method in
    engineering sciences, such as control theory. mor is used in improving
    computational efficiency of simulations of complex nonlinear mathematical
    models. in this study the dimension of a nonlinear mathematical model of
    plasticity in the brain is reduced using mathematical mor methods.

    Traditionally, models are simplified by eliminating variables, such as
    molecular entities and ionic currents, from the system. additionally,
    assumptions of the system behavior can be made, for example regarding the
    steady state of the chemical reactions. however, comprehensive models with full
    system dynamics are needed in order to increase understanding of different
    mechanisms in one brain area. thus the elimination approach is not suitable for
    the consequent analysis of neural phenomena.

    The loss of information induced by eliminating variables of the system can be
    avoided by mathematical mor methods that approximate the entire system with a smaller number of dimensions compared to the original system. here,
    mathematical MOR is applied in the context of an experimentally verified
    signaling pathway model of plasticity (Kim et al., PLoS Comp. Biol., 2013).
    This nonlinear chemical equation based model describes the biochemical calcium signaling steps required for plasticity and learning in the subcortical area of the brain. By applying these methods, the simulation time of the model is radically shortened.
    Original languageEnglish
    Publication statusPublished - 20 Sep 2018
    EventBrain and Mind Symposium 2018 - University of Helsinki, Helsinki, Finland
    Duration: 20 Oct 201821 Oct 2018

    Conference

    ConferenceBrain and Mind Symposium 2018
    Country/TerritoryFinland
    CityHelsinki
    Period20/10/1821/10/18

    Keywords

    • Neuroscience
    • Computational Neuroscience
    • Control theory

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