Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Nonlinear Analysis.

Objective: As an extension to our study comparing a putative compartmental and data-based model of linear dynamic cerebral autoregulation (CA) and CO-vasomotor reactivity (VR), we study the CA-VR process in a nonlinear context.

Methods: We use the concept of principal dynamic modes (PDM) in order to obtain a compact and more easily interpretable input-output model. This in silico study permits the use of input data with a dynamic range large enough to simulate the classic homeostatic CA and VR curves using a putative structural model of the regulatory control of the cerebral circulation.