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Multi-time scale dynamics of mixed depolarization block bursting

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Abstract

Two-coupled excitatory neurons model containing both calcium-activated non-specific cationic and persistent sodium current in the pre-Bötzinger complex (pre-BötC) is studied. A new type of mixed burst similar to a depolarization block bursting (DB-bursting) is observed in the model of pre-BötC neurons. The multi-time scale dynamics, one- and two-parameter bifurcation analysis, are used to study the types of mixed burst and their transition mechanisms. The results show that the periodic fluctuation of calcium concentration has a great influence on the generation of mixed bursting. The change of time scale caused by fluctuation of calcium concentration and the relative position of bifurcation curves have great influence on patterns of bursting.

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References

  1. Smith, J.C., Ellenberger, H.H., Ballanyi, K., et al.: Pre-Bötzinger complex: a brainstem region that may generate respiratory rhythm in mammals. Science 254(5032), 726–729 (1991)

    Article  Google Scholar 

  2. Smith, J.C.: Realistic computational models of respiratory neurons and networks. In: Bioengineering Approaches to Pulmonary Physiology and Medicine, pp. 77–92. Springer, Boston (1996)

  3. Mellen, N.M., Janczewski, W.A., Bocchiaro, C.M., et al.: Opioid-induced quantal slowing reveals dual networks for respiratory rhythm generation. Neuron 37(5), 821–826 (2003)

    Article  Google Scholar 

  4. Feldman, J.L., Smith, J.C.: Cellular mechanisms underlying modulation of breathing pattern in mammals. Ann. N. Y. Acad. Sci. 563(1), 114–130 (1989)

    Article  Google Scholar 

  5. Brockhaus, J., Ballanyi, K.: Synaptic inhibition in the isolated respiratory network of neonatal rats. Eur. J. Neurosci. 10(12), 3823–3839 (1998)

    Article  Google Scholar 

  6. Shao, X.M., Feldman, J.L.: Respiratory rhythm generation and synaptic inhibition of expiratory neurons in pre-Bötzinger complex: differential roles of glycinergic and GABAergic neural transmission. J. Neurophysiol. 77(4), 1853–1860 (1997)

    Article  Google Scholar 

  7. Ren, J., Greer, J.J.: Modulation of respiratory rhythmogenesis by chloride-mediated conductances during the perinatal period. J. Neurosci. 26(14), 3721–3730 (2006)

    Article  Google Scholar 

  8. Butera, R.J., John, R., Smith, J.C.: Models of respiratory rhythm generation in the pre-Bötzinger complex. I. Bursting pacemaker neurons. J. Neurophysiol. 82(1), 382–397 (1999)

    Article  Google Scholar 

  9. Butera, R.J., John, R., Smith, J.C.: Models of respiratory rhythm generation in the pre-Bötzinger complex. II. Populations of coupled pacemaker neurons. J. Neurophysiol. 82(1), 398–415 (1999)

    Article  Google Scholar 

  10. Rubin, J.E., Hayes, J.A., Mendenhall, J.L., et al.: Calcium-activated nonspecific cation current and synaptic depression promote network-dependent burst oscillations. Proc. Natl. Acad. Sci. 106(8), 2939–2944 (2009)

    Article  Google Scholar 

  11. Negro, C.A.D., Koshiya, N., Butera, R.J., et al.: Persistent sodium current, membrane properties and bursting behavior of pre-Bötzinger complex inspiratory neurons in vitro. J. Neurophysiol. 88(5), 2242–2250 (2002)

    Article  Google Scholar 

  12. Ptak, K., Zummo, G.G., Alheid, G.F., et al.: Sodium currents in medullary neurons isolated from the pre-Bötzinger complex region. J. Neurosci. 25(21), 5159–5170 (2005)

    Article  Google Scholar 

  13. Koizumi, H., Smith, J.C.: Persistent \(\text{ Na }^+\) and \(\text{ K }^+\)-dominated leak currents contribute to respiratory rhythm generation in the pre-Bötzinger complex in vitro. J. Neurosci. 28(7), 1773–1785 (2008)

    Article  Google Scholar 

  14. Pace, R.W., Mackay, D.D., Feldman, J.L., et al.: Inspiratory bursts in the pre-Bötzinger complex depend on a calcium activated nonspecific cation current linked to glutamate receptors in neonatal mice. J. Physiol. 582(1), 113–125 (2007)

    Article  Google Scholar 

  15. Toporikova, N., Butera, R.J.: Two types of independent bursting mechanisms in inspiratory neurons: an integrative model. J. Comput. Neurosci. 30(3), 515–528 (2011)

    Article  MathSciNet  Google Scholar 

  16. Park, C., Rubin, J.E.: Cooperation of intrinsic bursting and calcium oscillations underlying activity patterns of model pre-Bötzinger complex neurons. J. Comput. Neurosci. 34(2), 345–366 (2013)

    Article  MathSciNet  Google Scholar 

  17. Duan, L., Zhai, D., Tang, X.: Bursting induced by excitatory synaptic coupling in the pre-Bötzinger complex. Int. J. Bifurc. Chaos 22(05), 1107–283 (2012)

    Article  Google Scholar 

  18. Duan, L., Liu, J., Chen, X., et al.: Dynamics of in-phase and anti-phase bursting in the coupled pre-Bötzinger complex cells. Cogn. Neurodyn. 11(1), 1–7 (2017)

    Article  Google Scholar 

  19. Wang, Z., Duan, L., Cao, Q., et al.: Multi-stability involved mixed bursting within the coupled pre-Bötzinger complex neurons. Chin. Phys. B 27(7), 70502–070502 (2018)

    Article  Google Scholar 

  20. Dunmyre, J.R., Negro, C.A.D., Rubin, J.E.: Interactions of persistent sodium and calcium-activated nonspecific cationic currents yield dynamically distinct bursting regimes in a model of respiratory neurons. J. Comput. Neurosci. 31(2), 305–328 (2011)

    Article  Google Scholar 

  21. Liu, X., Liu, S.: Codimension-two bifurcation analysis in two-dimensional Hindmarsh–Rose model. Nonlinear Dyn. 67(1), 847–857 (2012)

    Article  MathSciNet  Google Scholar 

  22. Huang, C., Sun, W., Zheng, Z., et al.: Hopf bifurcation control of the M–L neuron model with type I. Nonlinear Dyn. 87(2), 755–766 (2017)

    Article  Google Scholar 

  23. Wechselberger, M., Weckesser, W.: Bifurcations of mixed-mode oscillations in a stellate cell model. Physica D 238(16), 1598–1614 (2009)

    Article  Google Scholar 

  24. Desroches, M., Guckenheimer, J., Krauskopf, B., et al.: Mixed-mode oscillations with multiple time scales. SIAM Rev. 54(2), 211–288 (2012)

    Article  MathSciNet  Google Scholar 

  25. Feibiao, Z., Shenquan, L., Xiaohan, Z., et al.: Mixed-mode oscillations and bifurcation analysis in a pituitary model. Nonlinear Dyn. 94(2), 807–826 (2018)

    Article  Google Scholar 

  26. Wang, Y., Rubin, J.E.: Multiple timescale mixed bursting dynamics in a respiratory neuron model. J. Comput. Neurosci. 41(3), 245–268 (2016)

    Article  MathSciNet  Google Scholar 

  27. Lu, Z., Chen, L., Duan, L.: Bifurcation analysis of mixed bursting in the pre-Bötzinger complex. Appl. Math. Modell. 67, 234–251 (2019)

    Article  Google Scholar 

  28. Ge, M., Jia, Y., Xu, Y., et al.: Mode transition in electrical activities of neuron driven by high and low frequency stimulus in the presence of electromagnetic induction and radiation. Nonlinear Dyn. 91(1), 515–523 (2018)

    Article  Google Scholar 

  29. Sun, X., Li, G.: Synchronization transitions induced by partial time delay in a excitatory-inhibitory coupled neuronal network. Nonlinear Dyn. 89(4), 2509–2520 (2017)

    Article  MathSciNet  Google Scholar 

  30. Yoshioka, M.: Cluster synchronization in an ensemble of neurons interacting through chemical synapses. Phys. Rev. E 71(6), 061914 (2005)

    Article  Google Scholar 

  31. Shi, X., Lu, Q.: Complete synchronization of coupled Hindmarsh-Rose neurons with ring structure. Chin. Phys. Lett. 21(9), 1695–1698 (2004)

    Article  Google Scholar 

  32. Mainieri, M.S., Erichsen, R., Brunnet, L.G.: Time evolution of coherent structures in networks of Hindmarch–Rose neurons. Phys. A 354, 663–671 (2005)

    Article  Google Scholar 

  33. Best, J., Borisyuk, A., Rubin, J., et al.: The dynamic range of bursting in a model respiratory pacemaker network. SIAM J. Appl. Dyn. Syst. 4(4), 1107–1139 (2005)

    Article  MathSciNet  Google Scholar 

  34. Kenny, A., Plank, M.J., David, T.: Minimal model of calcium dynamics in two heterogeneous coupled cells. Neurocomputing 323, 128–138 (2019)

    Article  Google Scholar 

  35. Yilmaz, E., Ozer, M., Baysal, V., et al.: Autapse-induced multiple coherence resonance in single neurons and neuronal networks. Sci. Rep. 6, 30914 (2016)

    Article  Google Scholar 

  36. Yilmaz, E., Baysal, V., Ozer, M., et al.: Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks. Physica A 444, 538–546 (2016)

    Article  MathSciNet  Google Scholar 

  37. Erkan, Y., Sarac, Z., Yilmaz, E.: Effects of astrocyte on weak signal detection performance of Hodgkin–Huxley neuron. Nonlinear Dyn. 95(4), 3411–3421 (2019)

    Article  Google Scholar 

  38. Duan, L., Yuan, D., Chen, X., et al.: Transition mechanisms of bursting in a two-cell network model of the pre-Bötzinger complex. Int. J. Bifurc. Chaos 25(05), 1550069 (2015)

    Article  Google Scholar 

  39. Rubin, J.E., Krauskopf, B., Osinga, H.M.: Natural extension of fast-slow decomposition for dynamical systems. Phys. Rev. E 97(1), 012215 (2018)

    Article  MathSciNet  Google Scholar 

  40. Barreto, E., Cressman, J.R.: Ion concentration dynamics as a mechanism for neuronal bursting. J. Biol. Phys. 37(3), 361–373 (2011)

    Article  Google Scholar 

  41. Lieske, S., Thoby-Brisson, M., Telgkamp, P., et al.: Reconfiguration of the neural network controlling multiple breathing patterns: eupnea, sighs and gasps. Nat. Neurosci. 3, 600–607 (2000)

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 11872003), Cultivation Plan for “Yujie” Team of North China University of Technology (No. 107051360019XN137/002).

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Correspondence to Lixia Duan.

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Appendix

Appendix

For \(x\in \{mp,m,h,n,s\}\), the function of \(x_{\infty }(V)\) takes the form \(x_{\infty }(V)=\{1+exp(V-\theta _{x}/\sigma _{x})\}^{-1}\). For \(x\in \{h,n,s\}\), the function of \(\tau _{x}(V)\) takes the form \(\tau _{x}(V)= {\bar{\tau }}_{x}/\cosh [(V-\theta _{x})/2\sigma _{x}]\). The parameter values are shown in Table 1.

Table 1 Parameter values used in the model

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Duan, L., Liang, T., Zhao, Y. et al. Multi-time scale dynamics of mixed depolarization block bursting. Nonlinear Dyn 103, 1043–1053 (2021). https://doi.org/10.1007/s11071-020-05744-x

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