ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
PUBLISHED
SINCE 1952
 
Proceeding cover
proceedings
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2022): 0.9
On the complexity of signal propagation in nerve fibres; pp. 28–38
PDF | https://doi.org/10.3176/proc.2017.4.28

Authors
Jüri Engelbrecht, Tanel Peets, Kert Tamm, Martin Laasmaa, Marko Vendelin
Abstract

Biological systems are characterized by many interwoven processes over multiple scales where interactions between the various phenomena play a decisive role. These phenomena can be chemical, electrical, and/or mechanical, all embedded into a whole. This paper discusses the propagation of signals in nerve fibres, which exhibits clear signs of complexity: electrical signals (action potentials) are coupled to mechanical waves in the internal axoplasmic fluid and in the surrounding biomembrane. Here the underlying microstructure affects strongly the processes: the existence of ion currents changes the balance of ions within fibres, the opening of ion channels in the surrounding biomembrane is a crucial process, and the biomembrane itself has a microstructure composed of lipids. The whole process is governed by interactions, and the analysis of single processes has demonstrated the importance of nonlinearities. The main challenge is to build up a general model where the coupling of all related phenomena is taken into account. It is proposed that three processes – the propagation of an action potential and mechanical waves in the biomembrane and in the axoplasmatic fluid – be united into a general model with additional interaction forces for reflecting coupling. Such a model results in the emerging of a mutually interacting ensemble of waves. The preliminary numerical simulations cast light onto the possible validation of this general model reflecting the complexity of signal propagation in nerve fibres. The mathematically consistent modelling will allow not only the prediction of process characteristics but gives a possibility of understanding the role of governing factors in the whole complex process.

References

 

1. Prigogine, I. and Stengers, I. Order Out of Chaos. Heinemann, London, 1984.

2. Bak, P. How Nature Works. Oxford University Press, 1996.
https://doi.org/10.1007/978-1-4757-5426-1

3. Nicolis, G. and Nicolis, C. Foundations of Complex Systems. World Scientific, New Jersey, 2007.
https://doi.org/10.1142/6253

4. Érdi, P. Complexity Explained. Springer, Berlin–Heidelberg, 2008.

5. Engelbrecht, J. Complexity in engineering and natural sciences. Proc. Estonian Acad. Sci., 2015, 64, 249–255.
https://doi.org/10.3176/proc.2015.3.07

6. Vendelin, M., Bovendeerd, P. H. M., Arts, T., Engelbrecht, J., and van Campen, D. H. Cardiac mechanoenergetics replicated by cross-bridge model. Ann. Biomed. Eng., 2000, 28(6), 629–640.
https://doi.org/10.1114/1.1305910

7. Kalda, M., Peterson, P., and Vendelin, M. Crossbridge group ensembles describing cooperativity in thermodynamically consistent way. PLoS One, 2015, 10(9), e0137438.
https://doi.org/10.1371/journal.pone.0137438

8. Engelbrecht, J., Vendelin, M., and Maugin, G. A. Hierarchical internal variables reflecting microstructural properties: application to cardiac muscle contraction. J. Non-Equilib. Thermodyn., 2000, 25(2), 119–130.
https://doi.org/10.1515/JNETDY.2000.008

9. Engelbrecht, J. and Berezovski, A. Internal structures and internal variables in solids. J. Mech. Mater. Struct., 2012, 7, 983–996.
https://doi.org/10.2140/jomms.2012.7.983

10. Kaneko, K. Life: An Introduction to Complex Systems Biology. Springer, Berlin–Heidelberg, 2006.
https://doi.org/10.1007/978-3-540-32667-0

11. Scott, A. Nonlinear Science. Emergence & Dynamics of Coherent Structures. Oxford University Press, 1999.

12. Hodgkin, A. L. and Huxley, A. F. A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol., 1952, 117, 500–544.
https://doi.org/10.1113/jphysiol.1952.sp004764

13. FitzHugh, R. Impulses and physiological states in theoretical models of nerve membrane. Biophys. J., 1961, 1, 445–466.
https://doi.org/10.1016/S0006-3495(61)86902-6

14. Heimburg, T. and Jackson, A. D. On soliton propagation in biomembranes and nerves. Proc. Natl. Acad. Sci. USA, 2005, 102, 9790–9795.
https://doi.org/10.1073/pnas.0503823102

15. Scott, A. (ed.). Encyclopedia of Nonlinear Science. Taylor & Francis, New York, 2005.

16. Whitham, G. Linear and Nonlinear Waves. Wiley, New York, 1974.

17. Ablowitz, M. J. Nonlinear Dispersive Waves. Asymptotic Analysis and Solitons. Cambridge University Press, 2011.
https://doi.org/10.1017/CBO9780511998324

18. Salupere, A., Peterson, P., and Engelbrecht, J. Long-time behaviour of soliton ensembles. Part I—Emergence of ensembles. Chaos Soliton. Fract., 2002, 14, 1413–1424.
https://doi.org/10.1016/S0960-0779(02)00069-3

19. Salupere, A., Peterson, P., and Engelbrecht, J. Long-time behaviour of soliton ensembles. Part II—Periodical patterns of trajectories. Chaos Soliton. Fract., 2003, 15, 29–40.
https://doi.org/10.1016/S0960-0779(02)00070-X

20. Peterson, P., Soomere, T., Engelbrecht, J., and Groesen, E. V. Soliton interaction as a possible model for extreme waves in shallow water. Nonlinear Proc. Geoph., 2003, 10, 503–510.
https://doi.org/10.5194/npg-10-503-2003

21. Berezovski, A., Engelbrecht, J., Salupere, A., Tamm, K., Peets, T., and Berezovski, M. Dispersive waves in microstructured solids. Int. J. Solids Struct., 2013, 50, 1981–1990.
https://doi.org/10.1016/j.ijsolstr.2013.02.018

22. Engelbrecht, J. and Khamidullin, Y. On the possible amplification of nonlinear seismic waves. Phys. Earth Planet. Inter., 1988, 50, 39–45.
https://doi.org/10.1016/0031-9201(88)90089-1

23. Mai, P. M. Ground motion: complexity and scaling in the near field of earthquake ruptures. In Extreme Environmental Events. Springer, New York, 2009, 4435–4474.
https://doi.org/10.1007/978-0-387-30440-3_263

24. Vendelin, M., Saks, V., and Engelbrecht, J. Principles of mathematical modeling and in silico studies of integrated cellular energetics. In Molecular System Bioenergetics: Energy for Life (Saks, V., ed.). Wiley, Weinheim, 2007, 407–433.
https://doi.org/10.1002/9783527621095.ch12

25. Birkedal, R., Laasmaa, M., and Vendelin, M. The location of energetic compartments affects energetic communication in cardiomyocytes. Front. Physiol., 2014, 5, 376.
https://doi.org/10.3389/fphys.2014.00376

26. Simson, P., Jepihhina, N., Laasmaa, M., Peterson, P., Birkedal, R., and Vendelin, M. Restricted ADP movement in cardiomyocytes: Cytosolic diffusion obstacles are complemented with a small number of open mitochondrial voltage-dependent anion channels. J. Mol. Cell. Cardiol., 2016, 97, 197–203.
https://doi.org/10.1016/j.yjmcc.2016.04.012

27. Laasmaa, M., Birkedal, R., and Vendelin, M. Revealing calcium fluxes by analyzing inhibition dynamics in action potential clamp. J. Mol. Cell. Cardiol., 2016, 100, 93–108.
https://doi.org/10.1016/j.yjmcc.2016.08.015

28. Sepp, M., Vendelin, M., Vija, H., and Birkedal, R. ADP compartmentation analysis reveals coupling between pyruvate kinase and ATPases in heart muscle. Biophys. J., 2010, 98, 2785–2793.
https://doi.org/10.1016/j.bpj.2009.12.4027
https://doi.org/10.1016/j.bpj.2010.03.025

29. Illaste, A., Laasmaa, M., Peterson, P., and Vendelin, M. Analysis of molecular movement reveals latticelike obstructions to diffusion in heart muscle cells. Biophys. J., 2012, 102(4), 739–748.
https://doi.org/10.1016/j.bpj.2012.01.012

30. Vendelin, M., Hoerter, J. A., Mateo, P., Soboll, S., Gillet, B., and Mazet, J.-L. Modulation of energy transfer pathways between mitochondria and myofibrils by changes in performance of perfused heart. J. Biol. Chem., 2010, 285, 37240–37250.
https://doi.org/10.1074/jbc.M110.147116

31. Ramay, H. R. and Vendelin, M. Diffusion restrictions surrounding mitochondria: a mathematical model of heart muscle fibers. Biophys. J., 2009, 97, 443–452. Edition) (Sperelakis, N., ed.). Elsevier, 2012, 493–505.

32. Hille, B. Ionic Channels of Excitable Membranes. Sinauer Associates, Sunderland, MA, 2001.

33. Clay, J. R. Axonal excitability revisited. Prog. Biophys. Mol. Biol., 2005, 88, 59–90.
https://doi.org/10.1016/j.pbiomolbio.2003.12.004

34. George, S., Foster, J. M., and Richardson, G. Modelling in vivo action potential propagation along a giant axon. J. Math. Biol., 2015, 70, 237–263.
https://doi.org/10.1007/s00285-013-0751-x

35. Nagumo, J., Arimoto, S., and Yoshizawa, S. An active pulse transmission line simulating nerve axon. Proc. IRE, 1962, 50, 2061–2070.
https://doi.org/10.1109/JRPROC.1962.288235

36. Engelbrecht, J. On theory of pulse transmission in a nerve fibre. Proc. R. Soc. London, 1981, 375, 195–209.
https://doi.org/10.1098/rspa.1981.0047

37. Courtemanche, M., Ramirez, R. J., and Nattel, S. Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. Am. J. Physiol., 1998, 275, H301–H321.

38. Appali, R., Van Rienen, U., and Heimburg, T. A comparison of the Hodgkin–Huxley model and the soliton theory for the action potential in nerves. In Advances in Planar Lipid Bilayers and Liposomes, Vol. 16 (Iglic, A., ed.). Academic Press, 2012, 275–299.
https://doi.org/10.1016/B978-0-12-396534-9.00009-X

39. Hodgkin, A. L. and Huxley, A. F. Resting and action potentials in single nerve fibres. J. Physiol., 1945, 104, 176–195.
https://doi.org/10.1113/jphysiol.1945.sp004114

40. Gilbert, D. S. Axoplasm architecture and physical properties as seen in the Myxicola giant axon. J.Physiol., 1975, 253, 257–301.
https://doi.org/10.1113/jphysiol.1975.sp011190

41. Terakawa, S. Potential-dependent variations of the intracellular pressure in the intracellularly perfused squid giant axon. J. Physiol., 1985, 369, 229–248.
https://doi.org/10.1113/jphysiol.1985.sp015898

42. Biondi, R., Levy, M., and Weiss, P. An engineering study of the peristaltic drive of axonal flow. Proc. Natl. Acad. Sci. USA, 1972, 69, 1732–1736.
https://doi.org/10.1073/pnas.69.7.1732

43. Rvachev, M. M. On axoplasmic pressure waves and their possible role in nerve impulse propagation. Biophys. Rev. Lett., 2010, 5, 73–88.
https://doi.org/10.1142/S1793048010001147

44. El Hady, A. and Machta, B. B. Mechanical surface waves accompany action potential propagation. Nat. Commun., 2015, 6, 6697.
https://doi.org/10.1038/ncomms7697

45. Pedley, T. The Fluid Mechanics of Large Blood Vessels. Cambridge University Press, 1980.
https://doi.org/10.1017/CBO9780511896996

46. Tritton, J. Physical Fluid Dynamics. Oxford Science Publications, 1988.

47. Lin, T. and Morgan, G. Wave propagation through fluid contained in a cylindrical elastic shell. J. Acoust. Soc. Am., 1956, 28, 1165–1176.
https://doi.org/10.1121/1.1908583

48. Mueller, J. K. and Tyler, W. J. A quantitative overview of biophysical forces impinging on neural function. Phys. Biol., 2014, 11, 051001.
https://doi.org/10.1088/1478-3975/11/5/051001

49. Petrov, A. G. Flexoelectricity of model and living membranes. Biochim. Biophys. Acta, 2001, 1561, 1–25.
https://doi.org/10.1016/S0304-4157(01)00007-7

50. Griesbauer, J., Bössinger, S., Wixforth, A., and Schneider, M. F. Propagation of 2D pressure pulses in lipid monolayers and its possible implications for biology. Phys. Rev. Lett., 2012, 108, 198103.
https://doi.org/10.1103/PhysRevLett.108.198103

51. Shrivastava, S. and Schneider, M. F. Evidence for twodimensional solitary sound waves in a lipid controlled interface and its implications for biological signalling. J. R. Soc. Interface, 2014, 11, 20140098.
https://doi.org/10.1098/rsif.2014.0098

52. Andersen, S. S. L., Jackson, A. D., and Heimburg, T. Towards a thermodynamic theory of nerve pulse propagation. Prog. Neurobiol., 2009, 88, 104–113.
https://doi.org/10.1016/j.pneurobio.2009.03.002

53. Shillcock, J. C. and Lipowsky, R. Equilibrium structure and lateral stress distribution of amphiphilic bilayers from dissipative particle dynamics simulations. J. Chem. Phys., 2002, 117, 5048–5061.
https://doi.org/10.1063/1.1498463

54. Engelbrecht, J., Tamm, K., and Peets, T. On mathematical modelling of solitary pulses in cylindrical biomembranes. Biomech. Model. Mechanobiol., 2015, 14, 159–167.
https://doi.org/10.1007/s10237-014-0596-2

55. Tasaki, I. A macromolecular approach to excitation phenomena: mechanical and thermal changes in nerve during excitation. Physiol. Chem. Phys. Med. NMR, 1988, 20, 251–268.

56. Porubov, A. V. Amplification of Nonlinear Strain Waves in Solids. World Scientific, Singapore, 2003.
https://doi.org/10.1142/5238

57. Heimburg, T. Mechanical aspects of membrane thermodynamics. Estimation of the mechanical properties of lipid membranes close to the chain melting transition from calorimetry. Biochim. Biophys. Acta, 1998, 1415, 147–162.
https://doi.org/10.1016/S0005-2736(98)00189-8

58. Engelbrecht, J., Tamm, K., and Peets, T. On solutions of a Boussinesq-type equation with amplitude-dependent nonlinearities: the case of biomembranes. Philos. Mag., 2017, 97(12), 967–987.
https://doi.org/10.1080/14786435.2017.1283070

59. Maugin, G. A. Solitons in elastic solids (1938–2010). Mech. Res. Commun., 2011, 38, 341–349.
https://doi.org/10.1016/j.mechrescom.2011.04.009

60. Wilke, E. On the problem of nerve excitation in the light of the theory of waves. Pfl¨ugers Arch., 1912, 144, 35–38.
https://doi.org/10.1007/BF01681175

61. Bennett, M. V. L. Electrical synapses, a personal perspective (or history). Brain Res. Rev., 2000, 32, 16–28.
https://doi.org/10.1016/S0165-0173(99)00065-X

62. Debanne, D., Campanac, E., Bialowas, A., Carlier, E., and Alcaraz, G. Axon physiology. Physiol. Rev., 2011, 91, 555–602.
https://doi.org/10.1152/physrev.00048.2009

63. Contreras, F., Cervantes, H., Aguero, M., and Najera, M. Classic and non-classic soliton like structures for traveling nerve pulses. Int. J. Mod. Nonlinear Theory Appl., 2013, 2, 7–13.
https://doi.org/10.4236/ijmnta.2013.21002

64. Brown, F. L. H. Elastic modeling of biomembranes and lipid bilayers. Annu. Rev. Phys. Chem., 2008, 59, 685–712.
https://doi.org/10.1146/annurev.physchem.59.032607.093550

65. Barz, H., Schreiber, A., and Barz, U. Impulses and pressure waves cause excitement and conduction in the nervous system. Med. Hypotheses, 2013, 81, 768–772.
https://doi.org/10.1016/j.mehy.2013.07.049

66. Hormuzdi, S. G., Filippov, M. A., Mitropoulou, G., Monyer, H., and Bruzzone, R. Electrical synapses: a dynamic signaling system that shapes the activity of neuronal networks. BBA Biomembr., 2004, 1662, 113–137.

67. Barz, H. and Barz, U. Pressure waves in neurons and their relationship to tangled neurons and plaques. Med. Hypotheses, 2014, 82, 563–566.
https://doi.org/10.1016/j.mehy.2014.02.012

68. Morris, C. E. Why are so many ion channels mechanosensitive? In Cell Physiology Source Book (Fourth Edition) (Sperelakis, N., ed.). Elsevier, 2012, 493–505.
https://doi.org/10.1016/B978-0-12-387738-3.00027-5

69. Physics of cellular materials: biomembranes [lecture notes]. http://faculty.biomath.ucla.edu/tchou/pdffiles/lecture3.pdf, 2002 (accessed 2017-06-03).

70. Lomholt, M. A. and Miao, L. Descriptions of membrane mechanics from microscopic and effective twodimensional perspectives. J. Phys. A. Math. Gen., 2006, 39, 10323–10354.
https://doi.org/10.1088/0305-4470/39/33/005

71. Deseri, L. and Zurlo, G. The stretching elasticity of biomembranes determines their line tension and bending rigidity. Biomech. Model. Mechanobiol., 2013, 12, 1233–1242.
https://doi.org/10.1007/s10237-013-0478-z

72. Tieleman, D. P., Leontiadou, H., Mark, A. E., and Marrink, S. J. Simulation of pore formation in lipid bilayers by mechanical stress and electric fields. J. Am. Chem. Soc., 2003, 125, 6382–6383.
https://doi.org/10.1021/ja029504i

73. Heimburg, T. Lipid ion channels. Biophys. Chem., 2010, 150, 2–22.
https://doi.org/10.1016/j.bpc.2010.02.018

74. Mosgaard, L. D., Zecchi, K. A., and Heimburg, T. Mechano-capacitive properties of polarized membranes. Soft Matter, 2015, 11, 7899–7910.
https://doi.org/10.1039/C5SM01519G

75. Engelbrecht, J. and Salupere, A. On the problem of periodicity and hidden solitons for the KdV model. Chaos, 2005, 15, 015114.
https://doi.org/10.1063/1.1858781

76. Barashenkov, I. V. and Zemlyanaya, E. V. Soliton complexity in the damped-driven nonlinear Schr¨odinger equation: stationary to periodic to quasiperiodic complexes. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 2011, 83, 1–8.
https://doi.org/10.1103/PhysRevE.83.056610
https://doi.org/10.1103/PhysRevE.83.056609

77. Berezovski, A., Engelbrecht, J., and V´an, P. Weakly nonlocal thermoelasticity for microstructured solids: microdeformation and microtemperature. Arch. Appl. Mech., 2014, 84, 1249–1261.
https://doi.org/10.1007/s00419-014-0858-6

78. Petrov, A. G. and Sachs, F. Flexoelectricity and elasticity of asymmetric biomembranes. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 2002, 65, 1–5.
https://doi.org/10.1103/PhysRevE.65.021905

79. Blicher, A. and Heimburg, T. Voltage-gated lipid ion channels. PLoS One, 2013, 8, e65707.
https://doi.org/10.1371/journal.pone.0065707

80. Jérusalem, A., García-Grajales, J. A., Merchán-Pérez, A., and Peña, J. M. A computational model coupling mechanics and electrophysiology in spinal cord injury. Biomech. Model. Mechanobiol., 2014, 13, 883–896.
https://doi.org/10.1007/s10237-013-0543-7

81. Gonzalez-Perez, A., Mosgaard, L., Budvytyte, R., Villagran-Vargas, E., Jackson, A., and Heimburg, T. Solitary electromechanical pulses in lobster neurons. Biophys. Chem., 2016, 216, 51–59.
https://doi.org/10.1016/j.bpc.2016.06.005

82. Fillafer, C., Mussel, M., Muchowski, J., and Schneider, M. On cell surface deformation during an action potential. arXiv:1703.04608 [physics.bio-ph], 2017.

83. Barclay, D. W. and Moodie, T. B. Pulse propagation in a viscoelastic tube containing a viscous liquid. Appl. Math. Model., 1987, 11, 215–218.
https://doi.org/10.1016/0307-904X(87)90006-0

84. Horsten, J. B. A. M., Van Steenhoven, A. A., and Van Dongen, M. E. H. Linear propagation of pulsatile waves in viscoelastic tubes. J. Biomech., 1989, 22, 477–484.
https://doi.org/10.1016/0021-9290(89)90208-X

85. Ruch, T. C. and Patton, H. D. (eds). Physiology and Biophysics, 20th ed. W. B. Saunders, Philadelphia, 1982.

86. McIntyre, C. C. Richardson, A. G., and Grill, W. M. Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. J. Neurophysiol., 2002, 87, 995–1006.
https://doi.org/10.1152/jn.00353.2001

87. Sasaki, T. The axon as a unique computational unit in neurons. Neurosci. Res., 2013, 75, 83–88.
https://doi.org/10.1016/j.neures.2012.12.004

 

Back to Issue