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Bursting types and bifurcation analysis of the temperature-sensitive Purkinje neuron

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Abstract

The bursting discharge behaviour of neurons is affected by many factors, among which temperature is one of the more important factors. In this work, we study the bursting discharge behaviour and dynamics process of two different temperature-sensitive ion channels, the temperature-sensitive potassium current and the temperature-sensitive calcium current. In the case of the temperature-sensitive potassium current, the bursting discharge waveforms, codimension-1 bifurcations and trajectory plots at different temperatures indicate that five different types of bursting discharge (Hopf/Flip, Hopf/Homoclinic, Fold/Homoclinic, Fold/Fold Cycle, Circle/Big Homoclinic) appear with increasing temperature. In the case of temperature-sensitive calcium current, two types of bursting discharge (Circle/Big Homoclinic, Fold/Fold Cycle) emerge. According to the bursting discharge waveforms, the rise in temperature can promote the generation of bursting discharge at the beginning, and finally, the bursting discharge phenomenon disappears. This is consistent with the experimental results that blocking potassium and calcium currents can promote the bursting of Purkinje neurons. Then, it can be seen from the codimension-2 bifurcation and the waveform area distribution diagrams that even if the dynamic paths are consistent, the bursting discharge types and the waveforms may be different. In contrast, even if the bursting discharge type is the same, the dynamic paths and the waveform may be different. These results provide insight into the effect of temperature on the neuronal dynamics and bursting behaviour of temperature-sensitive ion channels.

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References

  1. Cooper, D.C.: The significance of action potential bursting in the brain reward circuit. Neurochem. Int. 41(5), 333–340 (2002)

    Google Scholar 

  2. Jefferys, J.G.R., Haas, H.L.: Synchronized bursting of CA1 hippocampal pyramidal cells in the absence of synaptic transmission. Nature 300(5891), 448–450 (1982)

    Google Scholar 

  3. Li, Y.Y., Gu, H.G., Jia, Y.B., et al.: Fast-slow variable dissection with two slow variables related to calcium concentrations: a case study to bursting in a neural pacemaker model. Nonlinear Dyn. 107(1), 1223–1245 (2022)

    Google Scholar 

  4. Lu, B., Gu, H.G., Wang, X.J., et al.: Paradoxical enhancement of neuronal bursting response to negative feedback of autapse and the nonlinear mechanism. Chaos Soliton Fract. 145, 110817 (2021)

    MathSciNet  Google Scholar 

  5. Guan, L.N., Gu, H.G., Zhao, Z.G.: Paradoxical enhancement of neuronal bursting response to negative feedback of autapse and the nonlinear mechanism. Nonlinear Dyn. 104(1), 577–601 (2021)

    Google Scholar 

  6. 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)

    Google Scholar 

  7. Onimaru, H., Arata, A., Homma, I.: Intrinsic burst generation of preinspiratory neurons in the medulla of brainstem-spinal cord preparations isolated from newborn rats. Exp. Brain Res. 106(1), 57–68 (1995)

    Google Scholar 

  8. Lin, H.R., Wang, C.H., Chen, C.J., et al.: Neural bursting and synchronization emulated by neural networks and circuits. IEEE Trans. Circuits I. 68(8), 3397–3410 (2021)

    Google Scholar 

  9. Postnova, S., Voigt, K., Braun, H.A.: Neural synchronization at tonic-to-bursting transitions. J. Biol. Phys. 33(2), 129–143 (2007)

    Google Scholar 

  10. Yao, Z., Ma, J., Yao, Y.G., et al.: Synchronization realization between two nonlinear circuits via an induction coil coupling. Nonlinear Dyn. 96(1), 205–217 (2019)

    MathSciNet  MATH  Google Scholar 

  11. Ma, J., Wu, F.Q., Alsaedi, A., et al.: Crack synchronization of chaotic circuits under field coupling. Nonlinear Dyn. 93(4), 2057–2069 (2018)

    Google Scholar 

  12. Wu, T.W., Zhang, X.H., Liu, Z.H.: Understanding the mechanisms of brain functions from the angle of synchronization and complex network. Front. Phys. 17(3), 1–23 (2022)

    Google Scholar 

  13. Cao, H.Y., Liu, Z.H.: A novel synchronization transition and amplitude death in the local brain networks of cortical regions. Nonlinear Dyn. 1–14 (2022)

  14. Kepecs, A., Wang, X.J., Lisman, J.: Bursting neurons signal input slope. J. Neurosci. 22(20), 9053–9062 (2002)

    Google Scholar 

  15. Kepecs, A., Lisman, J.: Information encoding and computation with spikes and bursts. Network-Comput. Neural. 14(1), 103 (2003)

    Google Scholar 

  16. Guo, Y.T., Zhou, P., Yao, Z., et al.: Biophysical mechanism of signal encoding in an auditory neuron. Nonlinear Dyn. 105(4), 3603–3614 (2021)

    Google Scholar 

  17. Prince, D.A.: Neurophysiology of epilepsy. Annu. Rev. Neurosci. 1(1), 395–415 (1978)

    Google Scholar 

  18. Traub, R.D., Wong, R.K.S.: Cellular mechanism of neuronal synchronization in epilepsy. Science 216(4547), 745–747 (1982)

    Google Scholar 

  19. Marder, E.: Motor pattern generation. Curr. Opin. Neurobiol. 10(6), 691–698 (2000)

    Google Scholar 

  20. Butera, J., Robert, J., Rinzel, J., et al.: Models of respiratory rhythm generation in the pre-Botzinger complex. I. Bursting pacemaker neurons. J. Neurophysiol. 82(1), 382–397 (1999)

    Google Scholar 

  21. Butera, J., Robert, J., Rinzel, J., et al.: Models of respiratory rhythm generation in the pre-Botzinger complex. II. Populations of coupled pacemaker neurons. J. Neurophysiol. 82(1), 398–415 (1999)

    Google Scholar 

  22. Izhikevich, E.M.: Dynamical systems in neuroscience. MIT Press, Cambridge (2007)

    Google Scholar 

  23. Ma, K.H., Gu, H.G., Zhao, Z.G.: Fast-slow variable dissection with two slow variables: a case study on bifurcations underlying bursting for seizure and spreading depression. Int. J. Bifurcat. Chaos 31(06), 2150096 (2021)

    MathSciNet  MATH  Google Scholar 

  24. Hua, H.T., Gu, H.G., Jia, Y.B., et al.: The nonlinear mechanisms underlying the various stochastic dynamics evoked from different bursting patterns in a neuronal model. Commun. Nonlinear Sci. 110, 106370 (2022)

    MathSciNet  MATH  Google Scholar 

  25. Wang, X.J., Gu, H.G., Lu, B.: Paradoxical reduction and the bifurcations of neuronal bursting activity modulated by positive self-feedback. Nonlinear Dyn. 101(4), 2383–2399 (2020)

    Google Scholar 

  26. Rinzel, J.: Ordinary and Partial Differential Equations. Springer, Berlin (1985)

    Google Scholar 

  27. Rinzel, J.: Mathematical Topics in Population Biology, Morphogenesis and Neurosciences. Springer, Berlin (1987)

    Google Scholar 

  28. Izhikevich, E.M.: Neural excitability, spiking and bursting. Int. J. Bifurcat. Chaos 10(06), 1171–1266 (2000)

    MathSciNet  MATH  Google Scholar 

  29. Huang, Y., Ko, H., Cheung, Z.H., et al.: Dual actions of brain-derived neurotrophic factor on GABAergic transmission in cerebellar Purkinje neurons. Exp. Neurol. 233(2), 791–798 (2012)

    Google Scholar 

  30. Stay, T.L., Laurens, J., Sillitoe, R.V., Angelaki, D.E.: Genetically eliminating Purkinje neuron GABAergic neurotransmission increases their response gain to vestibular motion. Proc. Natl. Acad. Sci. 116(8), 3245–3250 (2019)

    Google Scholar 

  31. Rulkov, N.F.: Modeling of spiking-bursting neural behavior using two-dimensional map. Phys. Rev. E 65(4), 041922 (2002)

    MathSciNet  MATH  Google Scholar 

  32. Bashkirtseva, I., Nasyrova, V., Ryashko, L.: Stochastic spiking-bursting excitability and transition to chaos in a discrete-time neuron model. Int. J. Bifurcat. Chaos 30(10), 2050153 (2020)

    MathSciNet  MATH  Google Scholar 

  33. Yazdi, H.H., Janahmadi, M., Behzadi, G.: The role of small-conductance Ca\(^{2+}\)-activated K\(^{+}\) channels in the modulation of 4-aminopyridine-induced burst firing in rat cerebellar Purkinje cells. Brain Res. 1156, 59–66 (2007)

    Google Scholar 

  34. Womack, M.D., Hoang, C., Khodakhah, K.: Large conductance calcium-activated potassium channels affect both spontaneous firing and intracellular calcium concentration in cerebellar Purkinje neurons. Neuroscience 162(4), 989–1000 (2009)

    Google Scholar 

  35. Womack, M., Khodakhah, K.: Active contribution of dendrites to the tonic and trimodal patterns of activity in cerebellar Purkinje neurons. J. Neurosci. 22(24), 10603–10612 (2002)

    Google Scholar 

  36. Xu, Y., Guo, Y.Y., Ren, G.D., et al.: Dynamics and stochastic resonance in a thermosensitive neuron. Chaos 385, 125427 (2020)

    MathSciNet  MATH  Google Scholar 

  37. Zhang, X.C., Liu, S.Q., Ren, H.X., et al.: Dynamic properties of Purkinje cells having different electrophysiological parameters: a model study. Neurophysiology 47(1), 2–10 (2015)

    Google Scholar 

  38. Ermentrout, B.: Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students. SIAM, Philadelphia (2002)

    MATH  Google Scholar 

  39. De Schutter, E., Bower, J.M.: An active membrane model of the cerebellar Purkinje cell II. Simulation of synaptic responses. J. Neurophysiol. 71, 401–419 (1994)

    Google Scholar 

  40. Khaliq, Z.M., Gouwens, N.W., Raman, I.M.: The contribution of resurgent sodium current to high-frequency firing in Purkinje neurons: an experimental and modeling study. J. Neurosci. 23, 4899–4912 (2003)

    Google Scholar 

  41. Kramer, M.A., Traub, R.D., Kopell, N.J.: New dynamics in cerebellar purkinje cells: torus canards. Phys. Rev. Lett. 101(6), 068103 (2008)

    Google Scholar 

  42. Benes, G.N., Barry, A.M., Kaper, T.J., et al.: An elementary model of torus canards. Chaos 21(2), 023131 (2011)

    MathSciNet  MATH  Google Scholar 

  43. Grandl, J., Kim, S.E., Uzzell, V., et al.: Temperature-induced opening of TRPV1 ion channel is stabilized by the pore domain. Nat. Neurosci. 13(6), 708–714 (2010)

    Google Scholar 

  44. Rinberg, A., Taylor, A.L., Marder, E.: The effects of temperature on the stability of a neuronal oscillator. PLoS Comput. Biol. 9(1), e1002857 (2013)

    Google Scholar 

  45. Womack, M.D., Khodakhah, K.: Somatic and dendritic small-conductance calcium-activated potassium channels regulate the output of cerebellar Purkinje neurons. J. Neurosci. 23(7), 2600–2607 (2003)

    Google Scholar 

  46. Womack, M.D., Chevez, C., Khodakhah, K.: Calcium-activated potassium channels are selectively coupled to P/Q-type calcium channels in cerebellar Purkinje neurons. J. Neurosci. 24(40), 8818–8822 (2004)

    Google Scholar 

  47. Isope, P., Hildebrand, M.E., Snutch, T.P.: Contributions of T-type voltage-gated calcium channels to postsynaptic calcium signaling within Purkinje neurons. Cerebellum 11(3), 651–665 (2012)

    Google Scholar 

  48. Etémé, A.S., Tabi, C.B., Mohamadou, A.: Firing and synchronization modes in neural network under magnetic stimulation. Commun. Nonlinear Sci. 72, 432–440 (2019)

    MathSciNet  MATH  Google Scholar 

  49. Etémé, A.S., Tabi, C.B., Beyala Ateba, J.F., et al.: Chaos break and synchrony enrichment within Hindmarsh-Rose-type memristive neural models. Nonlinear Dyn. 105(1), 785–795 (2021)

    Google Scholar 

  50. Etémé, A.S., Tabi, C.B., Ateba, J.F.B., et al.: Neuronal firing and DNA dynamics in a neural network. J. Phys. Commun. 2(12), 125004 (2018)

    Google Scholar 

  51. Xu, Y., Ma, J.: Control of firing activities in thermosensitive neuron by activating excitatory autapse. Chin. Phys. B 30(10), 100501 (2021)

    Google Scholar 

  52. Qin, H.X., Ma, J., Jin, W.Y., et al.: Dynamics of electric activities in neuron and neurons of network induced by autapses. Sci. China Technol. Sc. 57(5), 936–946 (2014)

    Google Scholar 

  53. Mortensen, L.S., Schmidt, H., Farsi, Z., et al.: K\(_{V}\)10.1 opposes activity-dependent increase in Ca\(^{2+}\) influx into the presynaptic terminal of the parallel fibre-Purkinje cell synapse. Cerebellum 593(1), 181–196 (2015)

    Google Scholar 

  54. Xing, M.M., Song, X.L., Yang, Z.Q., et al.: Bifurcations and excitability in the temperature-sensitive Morris–Lecar neuron. Nonlinear Dyn. 100(3), 2687–2698 (2020)

    Google Scholar 

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Funding

This work was supported by the National Natural Science Foundation of China with Grant No. 11872084 (ZQY), No. 12075017 (YC)

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Xing, M., Yang, Z. & Chen, Y. Bursting types and bifurcation analysis of the temperature-sensitive Purkinje neuron. Nonlinear Dyn 111, 1819–1834 (2023). https://doi.org/10.1007/s11071-022-07917-2

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