The dynamical role of electromagnetic induction in epileptic seizures: a double-edged sword

Zhao, Jinyi; Wang, Qingyun

doi:10.1007/s11071-021-06855-9

Cited by 16 publications

(16 citation statements)

References 36 publications

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“…In this paper, we introduce the electromagnetic induction mechanism into the coupled cortical thalamus model proposed by Wang et al [ 13 ]. The improved model can be described by the following differential equations [ 12 , 13 , 19 , 28 ]: ε py , ε in , ε tc , ε re are additive constants, τ 1 – τ 4 denote different time scales. k 1 - k 9 represent the strengths of connections between different neuronal populations.…”

Section: Models and Methodsmentioning

confidence: 99%

“…The simulation time is set to 30 s long enough, and the fixed time step of numerical integration is 0.05 ms. Most of the parameters in this paper are taken from previous experimental studies, and the values of all parameters are shown in Table 1 [ 13 , 19 , 32 ]. In order to see more abundant dynamic phenomena, the connection strengths are set within a certain reasonable range ( k 1 – k 9 ).…”

Section: Models and Methodsmentioning

confidence: 99%

“…Vinaya et al demonstrated that memristors played a leading role in controlling the absence seizures and contribute to the alleviation of absence seizures [ 18 ]. By applying the memristor to PY neurons, Zhao et al found that absence seizures were not only inhibited but might have the opposite result under electrical radiation [ 19 ]. In fact, these two arguments are not contradictory.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic effect of electromagnetic induction on epileptic waveform

et al. 2022

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Background Electromagnetic induction has recently been considered as an important factor affecting the activity of neurons. However, as an important form of intervention in epilepsy treatment, few people have linked the two, especially the related dynamic mechanisms have not been explained clearly. Methods Considering that electromagnetic induction has some brain area dependence, we proposed a modified two-compartment cortical thalamus model and set eight different key bifurcation parameters to study the transition mechanisms of epilepsy. We compared and analyzed the application and getting rid of memristors of single-compartment and coupled models. In particular, we plotted bifurcation diagrams to analyze the dynamic mechanisms behind abundant discharge activities, which mainly involved Hopf bifurcations (HB), fold of cycle bifurcations (LPC) and torus bifurcations (TR). Results The results show that the coupled model can trigger more discharge states due to the driving effect between compartments. Moreover, the most remarkable finding of this study is that the memristor shows two sides. On the one hand, it may reduce tonic discharges. On the other hand, it may cause new pathological states. Conclusions The work explains the control effect of memristors on different brain regions and lays a theoretical foundation for future targeted therapy. Finally, it is hoped that our findings will provide new insights into the role of electromagnetic induction in absence seizures.

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Section: Models and Methodsmentioning

confidence: 99%

Section: Models and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic effect of electromagnetic induction on epileptic waveform

et al. 2022

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“…A large number of physical and biological experiments have confirmed that many neurological diseases such as Alzheimer and epilepsy [7] are caused by abnormal discharge of neurons [8,9], and appropriate stimulus helps to reduce the symptoms of psychiatric patients, which is conducive to their health [10]. Hence, studying the firing behavior of neurons under external stimulus plays a positive role in understanding the pathogenesis of neuronal diseases, then contributes to the treatment and prevention of such neurological diseases.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of stimuli-based fractional-order memristor-coupled tabu learning two-neuron model and its engineering applications

et al. 2022

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External stimulus has an impact on the functional behavior of the biological nervous system, and appropriate stimulus helps the organism to maintain neural function. Inspired by this, the effects of different external stimuli on the dynamic behaviors of neuron model are studied in this paper. Firstly, a fractional-order(FO) memristor-coupled tabu learning two-neuron model whose equilibrium points are symmetric about the origin and unstable is constructed. The dynamic behaviors of this neuron model under different stimuli is further discussed, which are no external stimulus, external forced current stimulus and electromagnetic radiation (EMR) respectively. The neuron model without external stimulus has periodic attractors, but applying external stimulus to one of the neurons can produce abundant two-scroll chaotic attractors and multistability. Especially, when the neuron model is stimulated by EMR, it can generate hyperchaotic attractors that have not been observed in the tabu learning neuron model before. Besides, the transient transition behaviors of the model under different stimuli are also studied. Then, a pseudo-random number generator (PRNG) is designed and its random performance is tested with NIST suite. Finally, it is applied to voice encryption, and the result shows that it has good encryption effect. Therefore, it can be said that the FO memristor-coupled tabu learning two-neuron model has superior randomness and is suitable for chaotic-based engineering applications.

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“…Vinaya et al demonstrated that memristors played a leading role in controlling the absence seizures and contribute to the alleviation of absence seizures (Vinaya and Ignatius 2020). By applying the memristor to PY neurons, Zhao et al found that absence seizures were not only inhibited but might have the opposite result under electrical radiation (Zhao and Wang 2021). In fact, these two arguments are not contradictory.…”

Section: Introductionmentioning

confidence: 99%

Dynamic effect of electromagnetic induction on epileptic waveform

Sun

Chen

Zhang

et al. 2022

Preprint

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Background: Electromagnetic induction has recently been considered as an important factor affecting the activity of neurons. However, as an important form of intervention in epilepsy treatment, few people have linked the two, especially the related dynamic mechanisms have not been explained clearly. Methods: Considering that electromagnetic induction has some brain area dependence, we proposed a modified two-compartment cortical thalamus model and set eight different key bifurcation parameters to study the transition mechanisms of epilepsy. We compared and analyzed the application and getting rid of memristors of single-compartment and coupled models. In particular, we plotted bifurcation diagrams to analyze the dynamic mechanisms behind abundant discharge activities, which mainly involved Hopf bifurcations (HB), fold of cycle bifurcations (LPC) and torus bifurcations (TR). Results: The results show that the coupled model can trigger more discharge states due to the driving effect between compartments. Moreover, the most remarkable finding of this study is that the memristor shows two sides. On the one hand, it may reduce tonic discharges. On the other hand, it may cause new pathological states. Conclusions: The work explains the control effect of memristors on different brain regions and lays a theoretical foundation for future targeted therapy. Finally, it is hoped that our findings will provide new insights into the role of electromagnetic induction in absence seizures.

show abstract

The dynamical role of electromagnetic induction in epileptic seizures: a double-edged sword

Cited by 16 publications

References 36 publications

Dynamic effect of electromagnetic induction on epileptic waveform

Dynamic effect of electromagnetic induction on epileptic waveform

Dynamics of stimuli-based fractional-order memristor-coupled tabu learning two-neuron model and its engineering applications

Dynamic effect of electromagnetic induction on epileptic waveform

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