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Asymmetric effects of fractional orders on synchronization in a periodically forced FitzHugh–Nagumo system

Author

Listed:
  • Telksnienė, Inga
  • Coccolo, Mattia
  • Prado-Reynoso, Miguel A.
  • Čiegis, Raimondas
  • Sanjuán, Miguel A.F.

Abstract

Synchronization of a neuron with a periodic external input is a fundamental process in neuroscience, critical for information processing, network coordination, and therapeutic neuromodulation. In this work, we use the periodically forced fractional-order FitzHugh–Nagumo system to investigate how this phenomenon is affected by memory asymmetry, modeled by distinct fractional orders, α and β, of the Caputo derivatives governing the voltage and recovery variables. The system is numerically explored across a biologically plausible range of forcing parameters to identify a spectrum of dynamical responses, including phase-locking, complex dynamics, and quiescence. Phase-locking structures (Arnold tongues) are systematically mapped using the rotation number and inter-spike interval statistics, revealing how the asymmetry in memory reshapes the entrainment landscape. We find that memory in the fast voltage variable has a simplifying effect, suppressing complex firing patterns and promoting 1:1 synchronization. In contrast, memory in the slow recovery variable regulates the system’s frequency preference, shifting the entire entrainment window. These results demonstrate that the fractional orders have distinct, non-interchangeable roles, suggesting that memory asymmetry could serve as a biophysical mechanism for modulating the complexity and frequency selectivity of neuronal response to rhythmic input, with potential relevance to neural processing and neuromodulation strategies.

Suggested Citation

  • Telksnienė, Inga & Coccolo, Mattia & Prado-Reynoso, Miguel A. & Čiegis, Raimondas & Sanjuán, Miguel A.F., 2026. "Asymmetric effects of fractional orders on synchronization in a periodically forced FitzHugh–Nagumo system," Chaos, Solitons & Fractals, Elsevier, vol. 202(P1).
  • Handle: RePEc:eee:chsofr:v:202:y:2026:i:p1:s0960077925014882
    DOI: 10.1016/j.chaos.2025.117475
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    References listed on IDEAS

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    1. Roberto Garrappa, 2018. "Numerical Solution of Fractional Differential Equations: A Survey and a Software Tutorial," Mathematics, MDPI, vol. 6(2), pages 1-23, January.
    2. repec:plo:pone00:0138919 is not listed on IDEAS
    3. Lukas Ramlow & Benjamin Lindner, 2021. "Interspike interval correlations in neuron models with adaptation and correlated noise," PLOS Computational Biology, Public Library of Science, vol. 17(8), pages 1-35, August.
    4. Coccolo, Mattia & Seoane, Jesús M. & Lenci, Stefano & Sanjuán, Miguel A.F., 2024. "Phase control of escapes in the fractional damped Helmholtz oscillator," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    5. repec:plo:pcbi00:1003526 is not listed on IDEAS
    6. Bao, Bocheng & Chen, Liuhui & Bao, Han & Chen, Mo & Xu, Quan, 2024. "Bifurcations to bursting oscillations in memristor-based FitzHugh-Nagumo circuit," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    7. Brian Nils Lundstrom & Thomas J Richner, 2023. "Neural adaptation and fractional dynamics as a window to underlying neural excitability," PLOS Computational Biology, Public Library of Science, vol. 19(2), pages 1-17, February.
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