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Various dynamics of a ring of non-identical attention deficit disorder maps

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Abstract

Various regimes of a ring of non-identical attention deficit disorder (ADD) models are studied in this paper. The ADD model used in this paper can show multistability. The dynamics of the coupled maps are investigated by changing the coupling strength and parameter mismatch. In this study, a similarity function is used for the lag synchronization analysis of the coupled maps. To explore the dynamics, state space, bifurcation diagram, and largest Lyapunov exponent are analyzed. By investigating the control parameters of the map, different bifurcations, including a transition from periodic dynamics to quasiperiodic and chaotic behavior, transition from chaotic to periodic and periodic to chaotic attractors are observed. The results show exciting dynamics in the ring of non-identical ADD maps. However, proper lag synchronization is not observed in the chaotic regions; the periodic and quasiperiodic areas demonstrate an appealing lag synchronization. Furthermore, the ring of non-identical ADD maps can illustrate multistability similar to the uncoupled ADD model.

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Data generated during the current study will be made available upon reasonable request.

References

  1. J. Ma, J. Tang, A review for dynamics in neuron and neuronal network. Nonlinear Dyn. 89, 1569–1578 (2017)

    Article  MathSciNet  Google Scholar 

  2. L. Khaleghi et al., Chimera states in a ring of map-based neurons. Physica A 536, 122596 (2019)

    Article  MathSciNet  Google Scholar 

  3. B. Ibarz, J.M. Casado, M.A. Sanjuán, Map-based models in neuronal dynamics. Phys. Rep. 501(1–2), 1–74 (2011)

    Article  ADS  Google Scholar 

  4. Y. Liu et al., Detecting bifurcation points in a memristive neuron model. Euro. Phys. J. Spec. Topics 228, 1943–1950 (2019)

    Article  ADS  Google Scholar 

  5. M. Mehrabbeik et al., Synchronization and chimera states in the network of electrochemically coupled memristive Rulkov neuron maps. Math. Biosci. Eng. 18(6), 9394–9409 (2021)

    Article  Google Scholar 

  6. I.A. Bashkirtseva, L.B. Ryashko, A.N. Pisarchik, Ring of map-based neural oscillators: From order to chaos and back. Chaos Solitons Fractals 136, 109830 (2020)

    Article  MathSciNet  Google Scholar 

  7. H. Cao, M.A. Sanjuan, A mechanism for elliptic-like bursting and synchronization of bursts in a map-based neuron network. Cogn. Process. 10(Suppl 1), S23-31 (2009)

    Article  Google Scholar 

  8. N.F. Rulkov, Regularization of synchronized chaotic bursts. Phys. Rev. Lett. 86(1), 183–186 (2001)

    Article  ADS  Google Scholar 

  9. N.F. Rulkov, Modeling of spiking-bursting neural behavior using two-dimensional map. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 65(4 Pt 1), 041922 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  10. Courbage, M., V. Nekorkin, and L. Vdovin, Chaotic oscillations in a map-based model of neural activity. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2007. 17(4): p. 043109.

  11. D.R. Chialvo, Generic excitable dynamics on a two-dimensional map. Chaos Solitons Fractals 5(3–4), 461–479 (1995)

    Article  ADS  Google Scholar 

  12. K. Aihara, T. Takabe, M. Toyoda, Chaotic neural networks. Phys. Lett. A 144(6–7), 333–340 (1990)

    Article  ADS  MathSciNet  Google Scholar 

  13. H. Tanaka, T. Ushio, S. Kawanami, A high-dimensional chaotic discrete-time neuron model and bursting phenomena. Phys. Lett. A 308(1), 41–46 (2003)

    Article  ADS  MathSciNet  Google Scholar 

  14. E.M. Izhikevich, F. Hoppensteadt, Classification of bursting mappings. Int. J. Bifurcation Chaos 14(11), 3847–3854 (2004)

    Article  ADS  MathSciNet  Google Scholar 

  15. J. Nagumo, S. Sato, On a response characteristic of a mathematical neuron model. Kybernetik 10(3), 155–164 (1972)

    Article  Google Scholar 

  16. G. Baghdadi et al., A chaotic model of sustaining attention problem in attention deficit disorder. Commun. Nonlinear Sci. Numer. Simul. 20(1), 174–185 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  17. B. Ibarz, H. Cao, M.A. Sanjuan, Bursting regimes in map-based neuron models coupled through fast threshold modulation. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 77(5 Pt 1), 051918 (2008)

    Article  ADS  MathSciNet  Google Scholar 

  18. N.N. Moghadam et al., How can the networks with various topologies change the occurrence of bifurcation points in a period-doubling route to chaos: a case study of neural networks in the presence and absence of disturbance. Euro. Phys. J. Plus 138(4), 362 (2023)

    Article  Google Scholar 

  19. Boccaletti, S., et al., Synchronization: from coupled systems to complex networks. 2018: Cambridge University Press.

  20. Moehlis, J., Dynamical Systems in Neuroscience: The geometry of excitability and bursting. 2008, JSTOR.

  21. P.J. Uhlhaas, W. Singer, Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52(1), 155–168 (2006)

    Article  Google Scholar 

  22. T. Wang et al., Distinct changes in global brain synchronization in early-onset vs. Late-Onset Parkinson Disease. Front Aging Neurosci 12, 604995 (2020)

    Article  Google Scholar 

  23. C. Hammond, H. Bergman, P. Brown, Pathological synchronization in Parkinson’s disease: networks, models and treatments. Trends Neurosci. 30(7), 357–364 (2007)

    Article  Google Scholar 

  24. D. Hu, H. Cao, Stability and synchronization of coupled Rulkov map-based neurons with chemical synapses. Commun. Nonlinear Sci. Numer. Simul. 35, 105–122 (2016)

    Article  ADS  MathSciNet  Google Scholar 

  25. M. Courbage, O. Maslennikov, V. Nekorkin, Synchronization in time-discrete model of two electrically coupled spike-bursting neurons. Chaos Solitons Fractals 45(5), 645–659 (2012)

    Article  ADS  Google Scholar 

  26. S. Li, Y. He, H. Cao, Necessary conditions for complete synchronization of a coupled chaotic Aihara neuron network with electrical synapses. Int J Bifurcation Chaos 29(05), 1950063 (2019)

    Article  MathSciNet  Google Scholar 

  27. I. Bashkirtseva, L. Ryashko, A.N. Pisarchik, Stochastic transitions between in-phase and anti-phase synchronization in coupled map-based neural oscillators. Commun. Nonlinear Sci. Numer. Simul. 95, 105611 (2021)

    Article  MathSciNet  Google Scholar 

  28. A. Ouannas et al., On the dynamics, control and synchronization of fractional-order Ikeda map. Chaos Solitons Fractals 123, 108–115 (2019)

    Article  ADS  MathSciNet  Google Scholar 

  29. S. Rakshit et al., Synchronization and firing patterns of coupled Rulkov neuronal map. Nonlinear Dyn. 94, 785–805 (2018)

    Article  Google Scholar 

  30. A. Arenas et al., Synchronization in complex networks. Phys. Rep. 469(3), 93–153 (2008)

    Article  ADS  MathSciNet  Google Scholar 

  31. A. Pisarchik, I. Bashkirtseva, L. Ryashko, Noise-induced quasiperiodicity in a ring of unidirectionally-coupled nonidentical maps. Phys. Lett. A 383(14), 1571–1577 (2019)

    Article  ADS  MathSciNet  Google Scholar 

  32. N. Sasano, K. Saeki, Y. Sekine, Short-term memory circuit using hardware ring neural networks. Artificial Life and Robotics 9, 81–85 (2005)

    Article  Google Scholar 

  33. O.L. Rourke, D.A. Butts, Cortical computations via transient attractors. PLoS ONE 12(12), e0188562 (2017)

    Article  Google Scholar 

  34. A. Sajedin et al., Cholinergic modulation promotes attentional modulation in primary visual cortex-a modeling study. Sci. Rep. 9(20186), 2019 (2019)

    Google Scholar 

  35. Majhi, S., S. Rakshit, and D. Ghosh, Oscillation suppression and chimera states in time-varying networks. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022. 32(4).

  36. S. Rakshit et al., Neuronal synchronization in long-range time-varying networks. Chaos 31(7), 073129 (2021)

    Article  ADS  MathSciNet  Google Scholar 

  37. V.V. Klinshov et al., Rate chaos and memory lifetime in spiking neural networks. Chaos Solitons Fractals 158, 112011 (2022)

    Article  MathSciNet  Google Scholar 

  38. I. Franović, V. Klinshov, Stimulus-evoked activity in clustered networks of stochastic rate-based neurons. Euro Phys J Spec Topics 227, 1063–1076 (2018)

    Article  ADS  Google Scholar 

  39. S. Boccaletti et al., The synchronization of chaotic systems. Phys. Rep. 366(1–2), 1–101 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  40. M.A. Khan, B. Sahoo, Temporospatial synchronization of discrete Logistic map through complex network. Optik 127(3), 1526–1531 (2016)

    Article  ADS  Google Scholar 

  41. S.N. Chowdhury et al., Synchronization to extreme events in moving agents. New J. Phys. 21(7), 073048 (2019)

    Article  ADS  MathSciNet  Google Scholar 

  42. A. Calim et al., Chimera states in hybrid coupled neuron populations. Neural Netw. 126, 108–117 (2020)

    Article  Google Scholar 

  43. J. Keppler, A new perspective on the functioning of the brain and the mechanisms behind conscious processes. Front. Psychol. 4, 242 (2013)

    Article  Google Scholar 

Download references

Funding

This work is funded by the Center for Nonlinear Systems, Chennai Institute of Technology, India, vide funding number CIT/CNS/2023/RP/006.

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Correspondence to Sajad Jafari.

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Massihi, N., Sriram, G., Nazarimehr, F. et al. Various dynamics of a ring of non-identical attention deficit disorder maps. Eur. Phys. J. Spec. Top. (2024). https://doi.org/10.1140/epjs/s11734-024-01168-5

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