Data, models and transitions in computational neuroscience: Bottom-up and top-down approaches

Manu Kalia

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    14 Downloads (Pure)

    Abstract

    This thesis is concerned with building and analyzing mathematical models in computational neuroscience using bottom-up and top-down approaches. Models are constructed using biophysical principles to understand the pathophysiology of cerebral ischemia at different spatial and temporal scales. Data-driven techniques in conjunction with machine learning are used to build compact parameter-dependent models from high-dimensional data. Finally, model maps are introduced to explain the generic unfolding of a newly observed bifurcation.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • University of Twente
    Supervisors/Advisors
    • Brune, Christoph, Supervisor
    • van Putten, Michel J.A.M., Supervisor
    • Meijer, Hil G.E., Co-Supervisor
    Award date14 Jul 2022
    Place of PublicationEnschede
    Publisher
    Print ISBNs978-90-365-5409-1
    DOIs
    Publication statusPublished - 14 Jul 2022

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