Nonlinear identification of the total baroreflex arc: higher-order nonlinearity

被引:12
|
作者
Moslehpour, Mohsen [1 ]
Kawada, Toru [2 ]
Sunagawa, Kenji [3 ]
Sugimachi, Masaru [2 ]
Mukkamala, Ramakrishna [1 ]
机构
[1] Michigan State Univ, Dept Elect & Comp Engn, 428 S Shaw Lane,Rm 2120,Engn Bldg, E Lansing, MI 48824 USA
[2] Natl Cerebral & Cardiovasc Ctr, Dept Cardiovasc Dynam, Osaka, Japan
[3] Kyushu Univ, Grad Sch Med Sci, Dept Cardiovasc Med, Fukuoka, Japan
基金
美国国家卫生研究院;
关键词
arterial baroreflex; Gaussian white noise; system identification; higher-order nonlinear model; hypertension; NEURAL ARC; BARORECEPTOR REFLEX; ARTERIAL-PRESSURE;
D O I
10.1152/ajpregu.00101.2016
中图分类号
Q4 [生理学];
学科分类号
071003 ;
摘要
The total baroreflex arc is the openloop system relating carotid sinus pressure (CSP) to arterial pressure (AP). The nonlinear dynamics of this system were recently characterized. First, Gaussian white noise CSP stimulation was employed in open-loop conditions in normotensive and hypertensive rats with sectioned vagal and aortic depressor nerves. Nonparametric system identification was then applied to measured CSP and AP to establish a second-order nonlinear Uryson model. The aim in this study was to assess the importance of higher-order nonlinear dynamics via development and evaluation of a third-order nonlinear model of the total arc using the same experimental data. Third-order Volterra and Uryson models were developed by employing nonparametric and parametric identification methods. The R-2 values between the AP predicted by the best third-order Volterra model and measured AP in response to Gaussian white noise CSP not utilized in developing the model were 0.69 +/- 0.03 and 0.70 +/- 0.03 for normotensive and hypertensive rats, respectively. The analogous R-2 values for the best third-order Uryson model were 0.71 +/- 0.03 and 0.73 +/- 0.03. These R-2 values were not statistically different from the corresponding values for the previously established second-order Uryson model, which were both 0.71 +/- 0.03 (P > 0.1). Furthermore, none of the third-order models predicted well-known nonlinear behaviors including thresholding and saturation better than the second-order Uryson model. Additional experiments suggested that the unexplained AP variance was partly due to higher brain center activity. In conclusion, the second-order Uryson model sufficed to represent the sympathetically mediated total arc under the employed experimental conditions.
引用
收藏
页码:R994 / R1003
页数:10
相关论文
共 50 条
  • [1] Nonlinear Identification of the Total Baroreflex Arc
    Moslehpour, Mohsen
    Kawada, Toru
    Sunagawa, Kenji
    Sugimachi, Masaru
    Mukkamala, Ramakrishna
    FASEB JOURNAL, 2015, 29
  • [2] Nonlinear identification of the total baroreflex arc
    Moslehpour, Mohsen
    Kawada, Toru
    Sunagawa, Kenji
    Sugimachi, Masaru
    Mukkamala, Ramakrishna
    AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY, 2015, 309 (12) : R1479 - R1489
  • [3] Nonlinear identification of the total baroreflex arc: chronic hypertension model
    Moslehpour, Mohsen
    Kawada, Toru
    Sunagawa, Kenji
    Sugimachi, Masaru
    Mukkamala, Ramakrishna
    AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY, 2016, 310 (09) : R819 - R827
  • [4] Higher-order spectra for identification of nonlinear modal coupling
    Hickey, Daryl
    Worden, Keith
    Platten, Michael F.
    Wright, Jan R.
    Cooper, Jonathan E.
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (04) : 1037 - 1061
  • [5] Higher-order nonlinearity of refractive index
    Tarazkar, Maryam
    Romanov, Dmitri A.
    Levis, Robert J.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2013, 246
  • [6] On Higher-Order Nonlinear Fractional Elastic Equations with Dependence on Lower Order Derivatives in Nonlinearity
    Cui, Yujun
    Liang, Chunyu
    Zou, Yumei
    FRACTAL AND FRACTIONAL, 2024, 8 (07)
  • [7] Higher-order spectral estimators and nonlinear system identification
    Birkelund, Y
    Powers, EJ
    PROCEEDINGS OF THE ELEVENTH (2001) INTERNATIONAL OFFSHORE AND POLAR ENGINEERING CONFERENCE, VOL III, 2001, : 78 - 84
  • [8] NEURAL NETWORKS WITH HIGHER-ORDER NONLINEARITY
    TAI, HM
    JONG, TL
    ELECTRONICS LETTERS, 1988, 24 (19) : 1225 - 1226
  • [9] Higher-order nonlinearity of Kasami functions
    Garg, Manish
    Khalyavin, Andrey
    INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2012, 89 (10) : 1311 - 1318
  • [10] Dark soliton dynamics for quantum systems with higher-order dispersion and higher-order nonlinearity
    Chen, Chen
    Gao, Guojun
    Wang, Ying
    Pan, Yuqi
    Zhou, Shuyu
    MODERN PHYSICS LETTERS B, 2021, 35 (17):