Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis

Brandon C. Henley, Dae C. Shin, Rong Zhang, Vasilis Z. Marmarelis

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and dynamic CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with the data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.

Original languageEnglish (US)
Article number7300387
Pages (from-to)2317-2332
Number of pages16
JournalIEEE Access
StatePublished - 2015


  • Cerebral autoregulation
  • compartmental modeling
  • nonparametric modeling
  • reactivity
  • vasomotor

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)


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