Pattern control of external electromagnetic stimulation to neuronal networks

Qu, Lianghui; Du, Lin; Hu, Haiwei; Cao, Zilu; Deng, Zichen

doi:10.1007/s11071-020-06076-6

Cited by 10 publications

(2 citation statements)

References 66 publications

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“…Theoretical studies on neuromodulation have recently demonstrated that physical stimulations can change the rhythm of neuronal firing. External electromagnetic stimulation was used to regulate neuronal network patterns (Qu et al 2020). Liu et al discovered the modulatory effect of transcranial magnetic-acoustic stimulation on neuronal firing (Liu et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Desynchronization of neuronal firing in multiparameter transcranial ultrasound stimulation

Bian

Ai²,

Yuan

2023

Preprint

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Low-intensity transcranial ultrasound stimulation, a novel neuromodulation technique, that possesses the advantages of non-invasiveness, high penetration depth, and high spatial resolution, has achieved positive neuromodulation effects in animal studies. But the regulatory mechanism remains controversial. The intramembrane cavitation effect is considered one of the mechanisms for ultrasound neuromodulation. In this study, the modified equations of ultrasonic cavitation bubble dynamics were coupled with the dual-coupled neuron Hindmarsh-Rose model, small-world neural network model, and the Jansen-Rit neural mass model, which simulate simple coupled neurons, complex neuronal networks, and discharge signals in epileptic disorders respectively. The results demonstrated that transcranial ultrasound stimulation has an appreciable modulatory effect on neuronal firing desynchronization in Hindmarsh-Rose model and small-world neural network model. The desynchronization effect is related to the stimulation frequency and intensity. Furthermore, ultrasound stimulation has an inhibitory effect on epileptic seizures, and the effect is enhanced by increasing ultrasound frequency from 0.1-1.0MHz. This is the first combination of ultrasonic intramembrane cavitation effect theory with neurons and neural network firing desynchronization, which can provide guidance of parametric and theories support for the studies of neurological diseases such as epilepsy and Parkinson's disease.

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Section: Introductionmentioning

confidence: 99%

Desynchronization of neuronal firing in multiparameter transcranial ultrasound stimulation

Bian

Ai²,

Yuan

2023

Preprint

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“…[31] To further reveal the effectiveness of electromagnetic treatment of mental diseases, the regulatory abilities of external electromagnetic stimulus on the dynamical properties of a small-world Newman-Watts network were explored. [32] Specially, the coexistence of spiking and bursting behaviors in a Leech neuron model was revealed and the synchronization of the two behaviors was investigated by coupling two identical Leech neurons. [33] After that, to mimic the threshold effect of electromagnetic induction, a threshold flux-controlled memristor-based HR neuron model was considered, from which the coexisting hidden bursting patterns were disclosed.…”

Section: Introductionmentioning

confidence: 99%

Continuous non-autonomous memristive Rulkov model with extreme multistability*

Liu

Feng

et al. 2021

Chinese Phys. B

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Based on the two-dimensional (2D) discrete Rulkov model that is used to describe neuron dynamics, this paper presents a continuous non-autonomous memristive Rulkov model. The effects of electromagnetic induction and external stimulus are simultaneously considered herein. The electromagnetic induction flow is imitated by the generated current from a flux-controlled memristor and the external stimulus is injected using a sinusoidal current. Thus, the presented model possesses a line equilibrium set evolving over the time. The equilibrium set and their stability distributions are numerically simulated and qualitatively analyzed. Afterwards, numerical simulations are executed to explore the dynamical behaviors associated to the electromagnetic induction, external stimulus, and initial conditions. Interestingly, the initial conditions dependent extreme multistability is elaborately disclosed in the continuous non-autonomous memristive Rulkov model. Furthermore, an analog circuit of the proposed model is implemented, upon which the hardware experiment is executed to verify the numerically simulated extreme multistability. The extreme multistability is numerically revealed and experimentally confirmed in this paper, which can widen the future engineering employment of the Rulkov model.

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Stochastic analysis of the electromagnetic induction effect on a neuron’s action potential dynamics

2021

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This paper examines the effect of electromagnetic induction on the electrophysiology of a single cortex neuron through two different modes associated with the nature of the external neuronal stimulus. By using the recently extended induction-based variant of the well-known and biologically plausible Hodgkin-Huxley neuron model, bifurcation analysis is performed. Electromagnetic induction caused by magnetic flux is captured using a polynomial approximation of a memristor embedded into the neuron model. In order to determine true influence of the variability of ion channels conductivity, the stochastic sensitivity analysis is performed post hoc. Additionally, numerical simulations are enriched with uncertainty quantification, observing values of ion channels conductivity as random variables. The aim of the study is to computationally determine the sensitivity of the action potential dynamics with respect to the changes in conductivity of each ion channel so that the future experimental procedures, most often medical treatments, may be adapted to different individuals in various environmental conditions.

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Pattern control of external electromagnetic stimulation to neuronal networks

Cited by 10 publications

References 66 publications

Desynchronization of neuronal firing in multiparameter transcranial ultrasound stimulation

Desynchronization of neuronal firing in multiparameter transcranial ultrasound stimulation

Continuous non-autonomous memristive Rulkov model with extreme multistability*

Stochastic analysis of the electromagnetic induction effect on a neuron’s action potential dynamics

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