title: Modeling of nonlinear physiological systems with fast and slow dynamics. II. Application to cerebral autoregulation.
abstract: Dynamic autoregulation of cerebral hemodynamics in healthy humans is studied using the novel methodology of the Laguerre-Volterra network for systems with fast and slow dynamics (Mitsis, G. D., and V. Z. Marmarelis, Ann. Biomed. Eng. 30:272-281, 2002). Since cerebral autoregulation is mediated by various physiological mechanisms with significantly different time constants, it is used to demonstrate the efficacy of the new method. Results are presented in the time and frequency domains and reveal that cerebral autoregulation is a nonlinear and dynamic (frequency-dependent) system with considerable nonstationarities. Quantification of the latter reveals greater variability in specific frequency bands for each subject in the low and middle frequency range (below 0.1 Hz). The nonlinear dynamics are prominent also in the low and middle frequency ranges, where the frequency response of the system exhibits reduced gain.
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles 90089-1451, USA.
authors.forename: G D
authors.initials: GD
authors.lastname: Mitsis
authors.forename: R
authors.initials: R
authors.lastname: Zhang
authors.forename: B D
authors.initials: BD
authors.lastname: Levine
authors.forename: V Z
authors.initials: VZ
authors.lastname: Marmarelis
mesh_terms: D000328:Adult; D001783:Blood Flow Velocity; D001794:Blood Pressure; D002560:Cerebrovascular Circulation / Q000502:physiology*; D003198:Computer Simulation; D005260:Female; D005583:Fourier Analysis; D006439:Hemodynamics; D006706:Homeostasis / Q000502:physiology*; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013997:Time Factors