Skip to main content
Log in

Logical stochastic and vibrational resonances induced by periodic force in the FitzHugh–Nagumo neuron

  • Regular Article
  • Published:
The European Physical Journal Plus Aims and scope Submit manuscript

Abstract

It was demonstrated that a bistable system driven by periodic force can be consistently regarded as a reliable logic gate when the amplitude and frequency of periodic driving force are both in their appropriate ranges. This phenomenon is called noise-free logical stochastic resonance (LSR). Here, the conventional bistable system is extended to an excitable FitzHugh–Nagumo (FHN) neuron model subjected to single or two periodic forces. We have confirmed that periodic force can induce single or multiple LSRs in the FHN neuron model. Interestingly, the forced FHN neuron can optimize simultaneously the reliability of logic operation and energy dissipation. When periodic force is subthreshold, that is, it cannot evoke spikes, the second periodic force can be added into the system to obtain logical vibrational resonance (LVR). In particular, multiple LVRs can also be obtained by altering the frequency of the second periodic force. The results obtained here may have implications in understanding the constructive roles of periodic force in neuro-inspired systems and would be conducive to the development of future computational devices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. This manuscript has associated data in a data repository. [Authors’ comment: All necessary data request can send message to the corresponding author via e-mail.].

References

  1. L. Gammaitoni, P. Hanggi, P. Jung, F. Marchesoni, Stochastic resonance. Rev. Mod. Phys. 70(1), 223–287 (1998). https://doi.org/10.1103/RevModPhys.70.223

    Article  ADS  Google Scholar 

  2. Y. Yao, J. Ma, Weak periodic signal detection by sine-Wiener-noise-induced resonance in the FitzHugh–Nagumo neuron. Cogn. Neurodyn. 12(3), 343–349 (2018). https://doi.org/10.1007/s11571-018-9475-3

    Article  Google Scholar 

  3. P.S. Landa, P.V.E. McClintock, Vibrational resonance. J. Phys. A Math. Gen. 33(45), L433–L438 (2000). https://doi.org/10.1088/0305-4470/33/45/103

    Article  ADS  MathSciNet  MATH  Google Scholar 

  4. Y. Ren, Y. Pan, F. Duan, F. Chapeau-Blondeau, D. Abbott, Exploiting vibrational resonance in weak-signal detection. Phys. Rev. E 96(2), 022141 (2017). https://doi.org/10.1103/PhysRevE.96.022141

    Article  ADS  Google Scholar 

  5. C. Yao, J. Ma, Z. He, Y. Qian, L. Liu, Transmission and detection of biharmonic envelope signal in a feed-forward multilayer neural network. Physica A 523, 797–806 (2019). https://doi.org/10.1016/j.physa.2019.02.053

    Article  ADS  MathSciNet  MATH  Google Scholar 

  6. H. Yu, J. Wang, C. Liu, B. Deng, X. Wei, Vibrational resonance in excitable neuronal systems. Chaos 21(4), 043101 (2011). https://doi.org/10.1063/1.3644390

    Article  ADS  Google Scholar 

  7. M. Ge, L. Lu, Y. Xu, R. Mamatimin, Q. Pei, Y. Jia, Vibrational mono-/bi-resonance and wave propagation in FitzHugh-Nagumo neural systems under electromagnetic induction. Chaos Solitons Fractals 133, 109645 (2020). https://doi.org/10.1016/j.chaos.2020.109645

    Article  MathSciNet  MATH  Google Scholar 

  8. J.P. Baltanas, L. Lopez, I.I. Blechman, P.S. Landa, A. Zaikin, J. Kurths, M.A.F. Sanjuan, Experimental evidence, numerics, and theory of vibrational resonance in bistable systems. Phys. Rev. E 67(6), 066119 (2003). https://doi.org/10.1103/PhysRevE.67.066119

    Article  ADS  Google Scholar 

  9. V.N. Chizhevsky, Experimental evidence of vibrational resonance in a multistable system. Phys. Rev. E 89(6), 062914 (2014). https://doi.org/10.1103/PhysRevE.89.062914

    Article  ADS  Google Scholar 

  10. D. Yu, L. Lu, G. Wang, L. Yang, Y. Jia, Synchronization mode transition induced by bounded noise in multiple time-delays coupled FitzHugh–Nagumo model. Chaos Solitons Fractals 147, 111000 (2021). https://doi.org/10.1016/j.chaos.2021.111000

    Article  MathSciNet  Google Scholar 

  11. Y. Xu, L. Lu, M. Ge, Y. Jia, Effects of temporally correlated noise on coherence resonance chimeras in FitzHugh–Nagumo neurons. Eur. Phys. J. B 92(11), 245 (2019). https://doi.org/10.1140/epjb/e2019-100413-0

    Article  ADS  Google Scholar 

  12. Y. Li, L.B. Kish, Heat, speed and error limits of Moore’s law at the nano scales. Fluct. Noise Lett. 6(2), L127–L131 (2006). https://doi.org/10.1142/s0219477506003215

    Article  Google Scholar 

  13. L. Gammaitoni, Noise limited computational speed. Appl. Phys. Lett. 91(22), 224104 (2007). https://doi.org/10.1063/1.2817968

    Article  ADS  Google Scholar 

  14. K. Murali, S. Sinha, W.L. Ditto, A.R. Bulsara, Reliable logic circuit elements that exploit nonlinearity in the presence of a noise floor. Phys. Rev. Lett. 102(10), 104101 (2009). https://doi.org/10.1103/PhysRevLett.102.104101

    Article  ADS  Google Scholar 

  15. P. Pfeffer, F. Hartmann, S. Hoefling, M. Kamp, L. Worschech, Logical stochastic resonance with a Coulomb-coupled quantum-dot rectifier. Phys. Rev. Appl. 4(1), 014011 (2015). https://doi.org/10.1103/PhysRevApplied.4.014011

    Article  ADS  Google Scholar 

  16. F. Hartmann, A. Forchel, I. Neri, L. Gammaitoni, L. Worschech, Nanowatt logic stochastic resonance in branched resonant tunneling diodes. Appl. Phys. Lett. 98(3), 032110 (2011). https://doi.org/10.1063/1.3548539

    Article  ADS  Google Scholar 

  17. L. Worschech, F. Hartmann, T.Y. Kim, S. Hoefling, M. Kamp, A. Forchel, J. Ahopelto, I. Neri, A. Dari, L. Gammaitoni, Universal and reconfigurable logic gates in a compact three-terminal resonant tunneling diode. Appl. Phys. Lett. 96(4), 042112 (2010). https://doi.org/10.1063/1.3302457

    Article  ADS  Google Scholar 

  18. L. Zhang, W. Zheng, F. Min, A. Song, Realizing reliable logic and memory function with noise-assisted Schmitt trigger circuits. Phys. Lett. A 383(7), 617–621 (2019). https://doi.org/10.1016/j.physleta.2019.01.010

    Article  ADS  Google Scholar 

  19. V. Kohar, K. Murali, S. Sinha, Enhanced logical stochastic resonance under periodic forcing. Commun. Nonlinear Sci. Numer. Simul. 19(8), 2866–2873 (2014). https://doi.org/10.1016/j.cnsns.2013.12.008

    Article  ADS  MathSciNet  MATH  Google Scholar 

  20. A. Gupta, A. Sohane, V. Kohar, K. Murali, S. Sinha, Noise-free logical stochastic resonance. Phys. Rev. E 84(5), 055201 (2011). https://doi.org/10.1103/PhysRevE.84.055201

    Article  ADS  Google Scholar 

  21. P.R. Venkatesh, A. Venkatesan, Vibrational resonance and implementation of dynamic logic gate in a piecewise-linear Murali–Lakshmanan–Chua circuit. Commun. Nonlinear Sci. Numer. Simul. 39, 271–282 (2016). https://doi.org/10.1016/j.cnsns.2016.03.009

    Article  ADS  MathSciNet  MATH  Google Scholar 

  22. Y. Yao, Time-varying coupling-induced logical stochastic resonance in a periodically driven coupled bistable system. Chin. Phys. B 30(6), 060503 (2021). https://doi.org/10.1088/1674-1056/abd76c

    Article  ADS  Google Scholar 

  23. M. Aravind, K. Murali, S. Sinha, Coupling induced logical stochastic resonance. Phys. Lett. A 382(24), 1581–1585 (2018). https://doi.org/10.1016/j.physleta.2018.03.043

    Article  ADS  MathSciNet  Google Scholar 

  24. M. Das, H. Kantz, Logical response induced by temperature asymmetry. Phys. Rev. E 100(3), 032108 (2019). https://doi.org/10.1103/PhysRevE.100.032108

    Article  ADS  Google Scholar 

  25. N. Wang, A. Song, Parameter-induced logical stochastic resonance. Neurocomputing 155, 80–83 (2015). https://doi.org/10.1016/j.neucom.2014.12.045

    Article  Google Scholar 

  26. G. Cheng, S. Zheng, J. Dong, Z. Xu, R. Gui, Effect of time delay in a bistable synthetic gene network. Chaos 31(5), 053105 (2021). https://doi.org/10.1063/5.0046373

    Article  ADS  MathSciNet  Google Scholar 

  27. R. Gui, J. Li, Y. Yao, G. Cheng, Effect of time-delayed feedback in a bistable system inferred by logic operation. Chaos, Solitons Fractals 148, 111043 (2021). https://doi.org/10.1016/j.chaos.2021.111043

    Article  MathSciNet  Google Scholar 

  28. N. Wang, A. Song, B. Yang, The effect of time-delayed feedback on logical stochastic resonance. Eur. Phys. J. B 90(6), 117 (2017). https://doi.org/10.1140/epjb/e2017-80150-4

    Article  ADS  Google Scholar 

  29. Y. Yao, J. Ma, Logical chaotic resonance in a bistable system. Int. J. Bifurc. Chaos 30(13), 2050196 (2020). https://doi.org/10.1142/s0218127420501965

    Article  MathSciNet  MATH  Google Scholar 

  30. Y. Yao, J. Ma, R. Gui, G. Cheng, Enhanced logical chaotic resonance. Chaos 31(2), 023103 (2021). https://doi.org/10.1063/5.0037032

    Article  ADS  MathSciNet  MATH  Google Scholar 

  31. Y. Yao, J. Ma, R. Gui, G. Cheng, Chaos-induced set–reset latch operation. Chaos, Solitons Fractals 152, 111339 (2021). https://doi.org/10.1016/j.chaos.2021.111339

    Article  MathSciNet  Google Scholar 

  32. Y. Yao, Logical chaotic resonance in the FitzHugh–Nagumo neuron. Nonlinear Dyn. 107(4), 3887–3901 (2022). https://doi.org/10.1007/s11071-021-07155-y

    Article  Google Scholar 

  33. R. Storni, H. Ando, K. Aihara, K. Murali, S. Sinha, Manipulating potential wells in logical stochastic resonance to obtain XOR logic. Phys. Lett. A 376(8–9), 930–937 (2012). https://doi.org/10.1016/j.physleta.2011.12.036

    Article  ADS  Google Scholar 

  34. R. Gui, Y. Yang, Y. Yao, G. Cheng, Noise-free logic and set–reset latch operation in a triple-well potential system. Chin. J. Phys. 68, 178–190 (2020). https://doi.org/10.1016/j.cjph.2020.09.009

    Article  MathSciNet  Google Scholar 

  35. H. Zhang, Y. Xu, W. Xu, X. Li, Logical stochastic resonance in triple-well potential systems driven by colored noise. Chaos 22(4), 043130 (2012). https://doi.org/10.1063/1.4768729

    Article  ADS  MathSciNet  Google Scholar 

  36. A.S. Pikovsky, J. Kurths, Coherence resonance in a noise-driven excitable system. Phys. Rev. Lett. 78(5), 775–778 (1997). https://doi.org/10.1103/PhysRevLett.78.775

    Article  ADS  MathSciNet  MATH  Google Scholar 

  37. K. Murali, S. Rajasekar, M.V. Aravind, V. Kohar, W.L. Ditto, S. Sinha, Construction of logic gates exploiting resonance phenomena in nonlinear systems. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 379(2192), 20200238 (2021). https://doi.org/10.1098/rsta.2020.0238

    Article  ADS  MathSciNet  Google Scholar 

  38. F.J. Torrealdea, A. d’Anjou, M. Grana, C. Sarasola, Energy aspects of the synchronization of model neurons. Phys. Rev. E 74(1), 011905 (2006). https://doi.org/10.1103/PhysRevE.74.011905

    Article  ADS  Google Scholar 

  39. C. Sarasola, F.J. Torrealdea, A. d’Anjou, A. Moujahid, M. Grana, Energy balance in feedback synchronization of chaotic systems. Phys. Rev. E 69(1), 011606 (2004). https://doi.org/10.1103/PhysRevE.69.011606

    Article  ADS  MATH  Google Scholar 

  40. X.-L. Song, W.-Y. Jin, J. Ma, Energy dependence on the electric activities of a neuron. Chin. Phys. B 24(12), 128710 (2015). https://doi.org/10.1088/1674-1056/24/12/128710

    Article  ADS  Google Scholar 

  41. P. Zhou, X. Hu, Z. Zhu, J. Ma, What is the most suitable Lyapunov function? Chaos Solitons Fractals 150, 111154 (2021). https://doi.org/10.1016/j.chaos.2021.111154

    Article  MathSciNet  MATH  Google Scholar 

  42. R. Gui, Y. Wang, Y. Yao, G. Cheng, Enhanced logical vibrational resonance in a two-well potential system. Chaos, Solitons Fractals 138, 109952 (2020). https://doi.org/10.1016/j.chaos.2020.109952

    Article  Google Scholar 

  43. L. Yang, W. Liu, M. Yi, C. Wang, Q. Zhu, X. Zhan, Y. Jia, Vibrational resonance induced by transition of phase-locking modes in excitable systems. Phys. Rev. E 86(1), 016209 (2012). https://doi.org/10.1103/PhysRevE.86.016209

    Article  ADS  Google Scholar 

  44. J. Zhu, T. Zhang, Y. Yang, R. Huang, A comprehensive review on emerging artificial neuromorphic devices. Appl. Phys. Rev. 7(1), 011312 (2020). https://doi.org/10.1063/1.5118217

    Article  ADS  Google Scholar 

  45. J. Tang, F. Yuan, X. Shen, Z. Wang, M. Rao, Y. He, Y. Sun, X. Li, W. Zhang, Y. Li, B. Gao, H. Qian, G. Bi, S. Song, J.J. Yang, H. Wu, Bridging biological and artificial neural networks with emerging neuromorphic devices: fundamentals, progress, and challenges. Adv. Mater. 31(49), 1902761 (2019). https://doi.org/10.1002/adma.201902761

    Article  Google Scholar 

  46. D. Rajasekharan, A. Gaidhane, A.R. Trivedi, Y.S. Chauhan, Ferroelectric FET-based implementation of FitzHugh–Nagumo neuron model. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(7), 2107–2114 (2022). https://doi.org/10.1109/tcad.2021.3101407

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

YY contributed to conceptualization, methodology, software, data curation, formal analysis, and writing—original draft. JM performed supervision and writing—review and editing.

Corresponding author

Correspondence to Yuangen Yao.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yao, Y., Ma, J. Logical stochastic and vibrational resonances induced by periodic force in the FitzHugh–Nagumo neuron. Eur. Phys. J. Plus 137, 1214 (2022). https://doi.org/10.1140/epjp/s13360-022-03423-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1140/epjp/s13360-022-03423-x

Navigation