1887
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
f
Stochastic vagal modulation of cardiac pacemaking may lead to erroneous identification of cardiac “chaos”
Rent:
Rent this article for
Access full text Article
/content/aip/journal/chaos/19/2/10.1063/1.3141426
1.
1.M. R. Boyett, H. Honjo, and I. Kodama, Cardiovasc. Res. 47, 658 (2000).
http://dx.doi.org/10.1016/S0008-6363(00)00135-8
2.
2.H. Zhang, A. V. Holden, I. Kodama, H. Honjo, M. Lei, T. Vagues, and M. R. Boyett, Am. J. Physiol. Heart Circ. Physiol. 279, H397 (2000).
3.
3.Y. Kurata, I. Hisatome, S. Imanishi, and T. Shibamoto, Am. J. Physiol. Heart Circ. Physiol. 285, H2804 (2003).
4.
4.H. Zhang, Y. Zhao, M. Lei, H. Dobrzynski, J. Liu, A. V. Holden, and M. R. Boyett, Am. J. Physiol. Heart Circ. Physiol. 292, H165 (2007).
http://dx.doi.org/10.1152/ajpheart.01101.2005
5.
5.L. Glass, Nature (London) 410, 277 (2001).
http://dx.doi.org/10.1038/35065745
6.
6.H. C. Routledge, S. Chowdhary, and J. N. Townend, J. Clin. Pharm. Ther. 27, 85 (2002).
http://dx.doi.org/10.1046/j.1365-2710.2002.00404.x
7.
7.L. Glass, Chaos 18, 020201 (2008).
http://dx.doi.org/10.1063/1.2957912
8.
8.C. Lerma, T. K. Madsen, M. Guevara, and L. Glass, J. Stat. Phys. 128, 347 (2007).
http://dx.doi.org/10.1007/s10955-006-9191-y
9.
9.R. Wilders and H. J. Jongsma, Biophys. J. 65, 2601 (1993).
http://dx.doi.org/10.1016/S0006-3495(93)81289-X
10.
10.M. R. Guevara and T. A. Lewis, Chaos 5, 174 (1995).
http://dx.doi.org/10.1063/1.166065
11.
11.L. J. DeFelice and A. Issac, J. Stat. Phys. 70, 339 (1993).
http://dx.doi.org/10.1007/BF01053972
12.
12.M. Pagani, F. Lombardi, S. Guzzetti, O. Rimoldi, R. Furlan, P. Pizzinelli, G. Sandrone, G. Malfatto, S. D. Orto, E. Piccaluga, M. Turiel, G. Baselli, S. Cerutti, and A. Malliani, Circ. Res. 59, 178 (1986).
13.
13.B. Pomeranz, R. J. Macaulay, M. A. Caudill, I. Kutz, D. Adam, D. Gordon, K. M. Kilborn, A. C. Barger, D. C. Shannon, and R. J. Cohen, Am. J. Physiol. Heart Circ. Physiol. 248, H151 (1985).
14.
14.Task Force of the European Society of Cardiology the North American Society of Pacing Heart Rate Variability Standards of Measurement, Physiological Interpretation, and Clinical Use, Circulation 93, 1043 (1996).
15.
15.B. Frey, G. Heger, C. Mayer, B. Kiegler, H. Stöhr, and G. Steurer, Pacing Clin. Electrophysiol. 19, 1882 (1996).
http://dx.doi.org/10.1111/j.1540-8159.1996.tb03245.x
16.
16.Y. Yamamoto and R. L. Hughson, Am. J. Physiol. Regulatory Integrative Comp. Physiol. 266, R40 (1994).
17.
17.Y. Yamamoto, Y. Nakamura, H. Sato, M. Yamamoto, K. Kato, and R. L. Hughson, Am. J. Physiol. Regulatory Integrative Comp. Physiol. 269, R830 (1995).
18.
18.K. Kotani, Z. R. Struzik, K. Takamasu, H. E. Stanley, and Y. Yamamoto, Phys. Rev. E 72, 041904 (2005).
http://dx.doi.org/10.1103/PhysRevE.72.041904
19.
19.T. Kuusela, T. Shepherd, and J. Hietarinta, Phys. Rev. E 67, 061904 (2003).
http://dx.doi.org/10.1103/PhysRevE.67.061904
20.
20.H. Zhang, A. V. Holden, D. Noble, and M. R. Boyett, J. Cardiovasc. Electrophysiol. 13, 465 (2002).
http://dx.doi.org/10.1046/j.1540-8167.2002.00465.x
21.
21.W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C (Cambridge University Press, Cambridge, 1992).
22.
22.A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano, Physica D, 16, 285 (1985).
http://dx.doi.org/10.1016/0167-2789(85)90011-9
23.
23.C. S. Poon and C. K. Merrill, Nature (London) 389, 492 (1997).
http://dx.doi.org/10.1038/39043
24.
24.C. S. Poon and M. Barahona, Proc. Natl. Acad. Sci. U.S.A. 98, 7107 (2001).
http://dx.doi.org/10.1073/pnas.131173198
25.
25.U. S. Freitas, C. Letellier, and L. A. Aguirre, Phys. Rev. E 79, 035201 (2009).
http://dx.doi.org/10.1103/PhysRevE.79.035201
26.
26.J. J. Zebrowski, K. Grudziński, T. Buchner, P. Kuklik, J. Gac, G. Gielerak, P. Sanders, and R. Baranowski, Chaos 17, 015121 (2007).
http://dx.doi.org/10.1063/1.2405128
27.
27.E. A. Raeder, R. D. Berger, R. Kenet, J. P. Kiely, T. H. Lehner, R. J. Cohen, and B. Lown, J. Appl. Cardiol. 2, 283 (1987).
28.
28.M. Toichi, T. Sugiura, T. Murai, and A. Sengoku, J. Auton Nerv. Syst. 62, 79 (1997).
http://dx.doi.org/10.1016/S0165-1838(96)00112-9
http://aip.metastore.ingenta.com/content/aip/journal/chaos/19/2/10.1063/1.3141426
Loading
View: Figures

Figures

Image of FIG. 1.

Click to view

FIG. 1.

Simulated chronotropic effect of a constant and pulselike fluctuation of [ACh] on the pacemaker APs of SA node cells. (a) Time series of simulated APs with a constant [ACh]. (b) Limit cycle attractor from (a) reconstructed in phase space by the time-delay method. (c) Pulselike fluctuation of [ACh]. (d) Measured CL in response to (c).

Image of FIG. 2.

Click to view

FIG. 2.

Effects of stochastic variation in [ACh] on the pacemaking APs of SA node cells. The arrow denotes the time when stochastic [ACh] fluctuation is switched on. (a) Upper panel: [ACh] fluctuates around the central level of . Bottom panel: Measured time series of CL. (b) Time series of RR intervals recorded from Langendorff perfused rabbit heart under application of carbachol (an agent has similar actions to ACh on modulating pacemaking ion channels). (c) Time series of simulated APs. (d) Reconstructed state attractor in phase space.

Image of FIG. 3.

Click to view

FIG. 3.

(a) Time series of computed maximal LE (solid symbol) and NL (open symbol) for constant [ACh]. (b) Time series of computed LE maximal (solid symbol) and NL (open symbol) for stochastic [ACh] [left scale: LE; right scale: NL for (a) and (b)].

Loading

Article metrics loading...

/content/aip/journal/chaos/19/2/10.1063/1.3141426
2009-06-30
2014-04-25

Abstract

Fluctuations in the time interval between two consecutive R-waves of electrocardiogram during normal sinus rhythm may result from irregularities in the autonomic drive of the pacemaking sinoatrial node (SAN). We use a biophysically detailed mathematical model of the action potentials of rabbit SAN to quantify the effects of fluctuations in acetylcholine (ACh) on the pacemaker activity of the SAN and its variability. Fluctuations in ACh concentration model the effect of stochastic activity in the vagal parasympathetic fibers that innervate the SAN and produce varying rates of depolarization during the pacemaker potential, leading to fluctuations in cycle length (CL). Both the estimated maximal Lyapunov exponent and the noise limit of the resultant sequence of fluctuating CLs suggest chaotic dynamics. Apparently chaotic heart rate variability (HRV) seen in sinus rhythm can be produced by stochastic modulation of the SAN. The identification of HRV data as chaotic by use of time series measures such as a positive maximal Lyapunov exponent or positive noise limit requires both caution and a quantitative, predictive mechanistic model that is fully deterministic.

Loading

Full text loading...

/deliver/fulltext/aip/journal/chaos/19/2/1.3141426.html;jsessionid=3mq0pci727i1k.x-aip-live-02?itemId=/content/aip/journal/chaos/19/2/10.1063/1.3141426&mimeType=html&fmt=ahah&containerItemId=content/aip/journal/chaos
true
true
This is a required field
Please enter a valid email address
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Stochastic vagal modulation of cardiac pacemaking may lead to erroneous identification of cardiac “chaos”
http://aip.metastore.ingenta.com/content/aip/journal/chaos/19/2/10.1063/1.3141426
10.1063/1.3141426
SEARCH_EXPAND_ITEM