Abstract
Integration and reductionism represent two different modeling approaches in understanding the working mechanism of a system. Traditionally, biological modeling has relied on reductionism, which has the advantage of decomposing the intrinsic complexity of biological systems into smaller subsystems to ease understanding. However, as more information accumulates, it becomes increasingly difficult to integrate these components systematically to explain more complex behavior, particularly when multiple determining factors co-exist. In this chapter, we compare the reductionist and integrative views of biological modeling. The value of integrative modeling is discussed from the perspective of engineering and physics point of view. The need for an integrative approach is illustrated in the context of respiratory control.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahn, A.C., Tewari, M., Poon, C.S., Phillips, R.S.: The limits of reductionism in medicine: could systems biology offer an alternative? PLoS Med. 3(6), e208 (2006)
Cannon, W.B.: The Wisdom of the Body. W.W. Norton & Company, New York (1932)
Cherniack, N.: Potential role of optimization in alveolar hypoventilation and respiratory instability. In: von Euler, C., Lagercrantz, H. (eds.) Neurobiology of the control of breathing. Wenner-Gren International Symposium Series, pp. 45–50. Raven Press, New York (1987)
Eldridge, F.L., Morin, D., Romaniuk, J.R., Yamashiro, S., Potts, J.T., Ichiyama, R.M., Bell, H., Phillipson, E.A., Killian, K.J., Jones, N.L., Nattie, E.: Supraspinal locomotor centers do/do not contribute significantly to the hyperpnea of dynamic exercise in humans. J. Appl. Physiol. 100(5), 1743–1747 (2006)
Gerlai, R.: Gene targeting: technical confounds and potential solutions in behavioral brain research. Behav. Brain Res. 125(1-2), 13–21 (2001)
Ghazanshahi, S.D., Khoo, M.C.: Optimal ventilatory patterns in periodic breathing. Ann. Biomed. Eng. 21(5), 517–30 (1993)
Haouzi, P.: Theories on the nature of the coupling between ventilation and gas exchange during exercise. Respir Physiol Neurobiol. 151(2–3), 267–279 (2006)
Hebb, D.O.: The Organization of Behavior. Wiley, New York (1949)
Horig, H., Marincola, E., Marincola, F.M.: Obstacles and opportunities in translational research. Nat. Med. 11(7), 705–708 (2005)
Hunter, P.J., Borg, T.K.: Integration from proteins to organs: the physiome project. Nat. Rev. Mol. Cell Biol. 4(3), 237–243 (2003)
Khoo, M.C., Kronauer, R.E., Strohl, K.P., Slutsky, A.S.: Factors inducing periodic breathing in humans: a general model. J. Appl. Physiol. 53(3), 644–659 (1982)
Lazebnik, Y.: Can a biologist fix a radio? – or, what I learned while studying apoptosis. Canc. Cell 2(3), 179–182 (2002)
Mankoff, S.P., Brander, C., Ferrone, S., Marincola, F.M.: Lost in translation: Obstacles to translational medicine. J. Transl. Med. 2(1), 14 (2004)
Mateika, J.H., Duffin, J.: A review of the control of breathing during exercise. Eur. J. Appl. Physiol. Occup. Physiol. 71(1), 1–27 (1995)
Mead, J.: Control of respiratory frequency. J. Appl. Physiol. 15, 325–336 (1960)
Mitchell, G.S., Babb, T.G.: Layers of exercise hyperpnea: modulation and plasticity. Respir. Physiol. Neurobiol. 151(2-3), 251–266 (2006)
Ogata, K.: Modern Control Engineering. Prentice Hall, Englewood Cliffs, New Jersey (1997)
Ortoleva, P., Adhangale, P., Cheluvaraja, S., Fontus, M., Shreif, Z.: Deriving principles of microbiology by multiscaling laws of molecular physics. IEEE Eng. Med. Biol. Mag. 28(2), 70–79 (2009)
Poon, C.S.: Optimal control of ventilation in hypoxia, hypercapnia and exercise. In: Whipp, B.J., Wiberg, D.W. (eds.) Modelling and Control of Breathing, pp. 189–196. Elsevier, New York (1983)
Poon, C.S.: Ventilatory control in hypercapnia and exercise: optimization hypothesis. J. Appl. Physiol. 62, 2447–2459 (1987)
Poon, C.S.: Effects of inspiratory resistive load on respiratory control in hypercapnia and exercise. J. Appl. Physiol. 66(5), 2391–2399 (1989)
Poon, C.S.: Self-tuning optimal regulation of respiratory motor output by hebbian covariance learning. Neural Netw. 8, 1–17 (1996)
Poon, C.S.: Respiratory models and control. In: Bronzion J.D. (ed.) Biomedical Engineering Handbook, vol. 2, 2nd edn., p. 161. CRC, Boca Raton, Florida (2000)
Poon, C.S., Greene, J.G.: Control of exercise hyperpnea during hypercapnia in humans. J. Appl. Physiol. 59(3), 792–797 (1985)
Poon, C.S., Lin, S.L., Knudson, O.B.: Optimization character of inspiratory neural drive. J. Appl. Physiol. 72(5), 2005–2017 (1992)
Poon, C.S., Tin, C., Yu, Y.: Homeostasis of exercise hyperpnea and optimal sensorimotor integration: the internal model paradigm. Respir. Physiol. Neurobiol. 159(1), 1–13; discussion 14–20 (2007)
Pugh E.N. Jr., Andersen, O.S.: Models and mechanistic insight. J. Gen. Physiol. 131(6), 515–519 (2008)
Purves, M.: What do we breathe for? In: von Euler, C.., Lagercrantz, H. (eds.) Central Nervous Control Mechanisms in Breathing (Wenner-Gren Center Int. Symp. Ser.), vol. 32, pp. 7–12. Pergamon, Oxford, UK (1979)
Qutub, A., Gabhann, F., Karagiannis, E., Vempati, P., Popel, A.: Multiscale models of angiogenesis. IEEE Eng. Med. Biol. Mag. 28(2), 14–31 (2009)
Saijo, N.: Translational study in cancer research. Intern. Med. 41(10), 770–773 (2002)
Secher, N., Poon, C.S., Ward, S., Whipp, B., Duffin, J.: Supraspinal locomotor centers do/do not contribute significantly to the hyperpnea of dynamic exercise in humans. J. Appl. Physiol. 100(4), 1417–1418 (2006)
Slotine, J.J.E., Li, W.: Applied Nonlinear Control. Prentice-Hall, Englewood Cliffs, NJ (1991)
Sorger, P.K.: A reductionist’s systems biology: opinion. Curr. Opin. Cell Biol. 17(1), 9–11 (2005)
Stevens, S.: To honor fechner and repeal his law. Science 133, 80–86 (1961)
Strange, K.: The end of “naive reductionism”: Rise of systems biology or renaissance of physiology? Am. J. Physiol. Cell Physiol. 288(5), C968–C974 (2005)
Taufer, M., Armen, R., Chen, J., Teller, P., Brooks, C.: Computational multiscale modeling in protein–ligand docking. IEEE Eng. Med. Biol. Mag. 28(2), 58–69 (2009)
Tin, C., Poon, C.S.: Internal models in sensorimotor integration: perspectives from adaptive control theory. J. Neural Eng. 2(3), S147–S163 (2005)
Waldrop, T.G., Iwamoto, G.A., Haouzi, P.: Point:counterpoint: supraspinal locomotor centers do/do not contribute significantly to the hyperpnea of dynamic exercise. J. Appl. Physiol. 100(3), 1077–1083 (2006)
Ward, S.A.: Control of the exercise hyperpnoea in humans: a modeling perspective. Respir. Physiol. 122(2-3), 149–166 (2000)
Wasserman, K., Whipp, B.J., Casaburi, R.: Respiratory control during exercise. In: Cherniack, N.S., Widdicombe, J.G. (eds.) Handbook of Physiology, vol. 2, pp. 595–620. American Physiological Society, Bethesda, MD (1986)
Wellstead, P., Bullinger, E., Kalarnatianos, D., Mason, O., Verwoerd, M.: The role of control and system theory in systems biology. Annu. Rev. Contr. 32(1), 33–47 (2008)
White, R., Peng, G., Demir, S.: Multiscale modeling of biomedical, biological, and behavioral systems (part 1). IEEE Eng. Med. Biol. Mag. 28(2), 12–13 (2009)
Wiener, N.: Cybernetics; or, Control and communication in the animal and the machine. Technology Press [Cambridge, MA] (1948)
Young, D.L.: Hebbian covariance learning and self-tuning optimal control. Ph.D. thesis, M.I.T (1997)
Young, D.L., Poon, C.S.: Hebbian covariance learning. a nexus for respiratory variability, memory, and optimization? Adv. Exp. Med. Biol. 450, 73–83 (1998)
Young, D.L., Poon, C.S.: A hebbian feedback covariance learning paradigm for self-tuning optimal control. IEEE Trans. Syst. Man Cybern. B Cybern. 31(2), 173–186 (2001)
Young, D.L., Poon, C.S.: Soul searching and heart throbbing for biological modeling. Behav. Brain Sci. 24(06), 1080–1081 (2002)
Yu, Y., Poon, C.S.: Critique of “control of arterial Pco2 by somatic afferents”. J. Physiol. 572(3), 897–898 (2006)
Acknowledgements
Chung Tin is an American Heart Association predoctoral fellow. The research of Chi-Sang Poon was supported by US National Institutes of Health grants HL067966, HL072849, HL079503 and RR028241.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Tin, C., Poon, CS. (2013). Integrative and Reductionist Approaches to Modeling of Control of Breathing. In: Batzel, J., Bachar, M., Kappel, F. (eds) Mathematical Modeling and Validation in Physiology. Lecture Notes in Mathematics(), vol 2064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32882-4_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-32882-4_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32881-7
Online ISBN: 978-3-642-32882-4
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)