title: Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.
abstract: 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 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 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.
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089 USA.
authors.forename: B C
authors.initials: BC
authors.lastname: Henley
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089 USA.
authors.forename: D C
authors.initials: DC
authors.lastname: Shin
authors.affiliation: Southwestern Medical Center, University of Texas.
authors.forename: R
authors.initials: R
authors.lastname: Zhang
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089 USA.
authors.forename: V Z
authors.initials: VZ
authors.lastname: Marmarelis
keywords: Cerebral autoregulation; compartmental modeling; nonparametric modeling; vasomotor reactivity