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Cited by 26stochastic dynamics and bifurcationNeural dynamics and brain functionChaos control and synchronization

Subcritical Hopf Bifurcation and Stochastic Resonance of Electrical Activities in Neuron under Electromagnetic Induction

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Fu, Yu-Xuan, Kang, Yan-Mei, Xie, Yong·2018·Frontiers in Computational Neuroscience
DOI 10.3389/fncom.2018.00006PMC PMC5808182
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Abstract

The FitzHugh-Nagumo model is improved to consider the effect of the electromagnetic induction on single neuron. On the basis of investigating the Hopf bifurcation behavior of the improved model, stochastic resonance in the stochastic version is captured near the bifurcation point. It is revealed that a weak harmonic oscillation in the electromagnetic disturbance can be amplified through stochastic resonance, and it is the cooperative effect of random transition between the resting state and the large amplitude oscillating state that results in the resonant phenomenon. Using the noise dependence of the mean of interburst intervals, we essentially suggest a biologically feasible clue for detecting weak signal by means of neuron model with subcritical Hopf bifurcation. These observations should be helpful in understanding the influence of the magnetic field to neural electrical activity.

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  • Experimental and computational studies show that SR enhances phase locking, coherence, and synchronization across neuronal populations and sensorimotor networks, promoting transient coordination without requiring strong coupling or direct forcing.

    “At a systems level, experimental and computational studies show that SR enhances phase locking, coherence, and synchronization across neuronal populations and sensorimotor networks, promoting transient coordination without requiring strong coupling or direct forcing [37,38,39,40].”

    From The Heart’s Electromagnetic Field in Emotions, Empathy and Human Connection: Biosensor-Derived Insights into Heart–Brain Axis Mechanisms and a Basis for Novel BioMagnetoTherapies (2026) · cites this paper as [40]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • Cardiac and neural systems satisfy the key conditions required for SR.

    “Cardiac and neural systems satisfy the key conditions required for SR, including nonlinear excitability, intrinsic oscillations, threshold-dependent firing, and substantial background variability arising from ion channel noise, synaptic activity, and autonomic modulation [37,38,39,40].”

    From The Heart’s Electromagnetic Field in Emotions, Empathy and Human Connection: Biosensor-Derived Insights into Heart–Brain Axis Mechanisms and a Basis for Novel BioMagnetoTherapies (2026) · cites this paper as [40]

    The Introduction describes stochastic resonance in neural systems, and the Stochastic resonance section shows noise enabling a subthreshold signal to cross a neuron's firing threshold in a nonlinear model. The paper does not establish the claim for cardiac systems or identify autonomic modulation as a source of background variability; its periodic signal is externally applied rather than an intrinsic oscillation. No page numbers are available in our copy. (LLM, conf=0.88)

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Cited by

Sorted by citations

Authors
Fu, Y.-X., Kang, Y.-M., & Xie, Y.
Affiliations
State Key Laboratory of Mechanical Structure Strength and Vibration (CN)
ORCID
Xie, Yong
Venue
Frontiers in Computational Neuroscience
Publisher
Frontiers Media SA
Published
2018-02-06
Volume
12
Pages
6-6
ISSN
1662-5188 (ISSN-L)
DOI
10.3389/fncom.2018.00006
PMC
PMC5808182
OpenAlex
W2790819906
Cited by
26
References
3
Citations by year
2026: 2 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 2 · 2021: 2 · 2020: 4 · 2019: 6 · 2018: 3
FWCI
1.91
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Computational Neuroscience (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Natural Science Foundation of China (11772241, 11672219)
Topics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Chaos control and synchronization
Keywords
subcritical Hopf bifurcation, stochastic resonance, FitzHugh-Nagumo model, electromagnetic induction, neuronal electrical activity, weak signal detection, interburst interval, stochastic neural models

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