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

Manu Kalia

Research output: ThesisPhD Thesis - Research UT, graduation UT

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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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