Literature DB >> 12900179

Linearity and non-linearity in cerebral hemodynamics.

Cole A Giller1, Martin Mueller.   

Abstract

BACKGROUND: Transcranial Doppler ultrasound has been extensively used to study cerebral hemodynamics, and yet the basic characteristics of the input/output system of blood pressure/velocity are little known. We examine whether this system can best be considered linear or non-linear.
METHODS: We assessed the adequacy of linear modeling in four ways: (1) Known properties of cerebral blood flow were reviewed and analyzed from a systems standpoint; (2) 1100 ARX & OE model types were tested with data from 29 normal subjects, with and without lowpass filtering; (3) time-frequency analysis was used to identify nonstationary behavior and markers of non-linearity (such as bifurcations, chirps, and intermittent autoregulatory impairment) in the same data sets; (4) simple computer models of autoregulation incorporating time delays and non-linear elements were tested for production of spontaneous oscillations.
RESULTS: (1) Several aspects of cerebral hemodynamics are poorly described by linear models, (2) the ARX & OE models performed poorly, (3) time-frequency analysis showed non-linear and nonstationary behavior, (4) the computer models produced spontaneous oscillations similar to those observed in humans.
CONCLUSIONS: There is strong evidence that the blood pressure/velocity system is non-linear.

Entities:  

Mesh:

Year:  2003        PMID: 12900179     DOI: 10.1016/s1350-4533(03)00028-6

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  29 in total

1.  Spectral indices of human cerebral blood flow control: responses to augmented blood pressure oscillations.

Authors:  J W Hamner; Michael A Cohen; Seiji Mukai; Lewis A Lipsitz; J Andrew Taylor
Journal:  J Physiol       Date:  2004-07-14       Impact factor: 5.182

2.  The "time" to timely predict ischemic deficit after subarachnoid hemorrhage.

Authors:  Alfredo Conti; Francesco Tomasello
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Review 3.  Model-based indices describing cerebrovascular dynamics.

Authors:  Georgios V Varsos; Magdalena Kasprowicz; Peter Smielewski; Marek Czosnyka
Journal:  Neurocrit Care       Date:  2014-02       Impact factor: 3.210

4.  Effects of heat stress on dynamic cerebral autoregulation during large fluctuations in arterial blood pressure.

Authors:  R Matthew Brothers; Rong Zhang; Jonathan E Wingo; Kimberly A Hubing; Craig G Crandall
Journal:  J Appl Physiol (1985)       Date:  2009-10-01

5.  Revisiting human cerebral blood flow responses to augmented blood pressure oscillations.

Authors:  J W Hamner; Keita Ishibashi; Can Ozan Tan
Journal:  J Physiol       Date:  2019-01-31       Impact factor: 5.182

6.  Closed-loop dynamic modeling of cerebral hemodynamics.

Authors:  V Z Marmarelis; D C Shin; M E Orme; R Zhang
Journal:  Ann Biomed Eng       Date:  2013-01-05       Impact factor: 3.934

7.  Phase-amplitude investigation of spontaneous low-frequency oscillations of cerebral hemodynamics with near-infrared spectroscopy: a sleep study in human subjects.

Authors:  Michele L Pierro; Angelo Sassaroli; Peter R Bergethon; Bruce L Ehrenberg; Sergio Fantini
Journal:  Neuroimage       Date:  2012-07-20       Impact factor: 6.556

Review 8.  Neonatal cerebrovascular autoregulation.

Authors:  Christopher J Rhee; Cristine Sortica da Costa; Topun Austin; Ken M Brady; Marek Czosnyka; Jennifer K Lee
Journal:  Pediatr Res       Date:  2018-09-08       Impact factor: 3.756

9.  Parametric transfer function analysis and modeling of blood flow autoregulation in the optic nerve head.

Authors:  Jintao Yu; Yi Liang; Simon Thompson; Grant Cull; Lin Wang
Journal:  Int J Physiol Pathophysiol Pharmacol       Date:  2014-03-13

Review 10.  Integrative physiological and computational approaches to understand autonomic control of cerebral autoregulation.

Authors:  Can Ozan Tan; J Andrew Taylor
Journal:  Exp Physiol       Date:  2013-10-04       Impact factor: 2.969

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