Entrainment of a network of interacting neurons with minimum stimulating charge.,Physical Review E

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Entrainment of a network of interacting neurons with minimum stimulating charge.
Physical Review E ( IF 2.2 ) Pub Date : 2020-07-30 , DOI: 10.1103/physreve.102.012221
Kestutis Pyragas ₁ , Augustinas P Fedaravičius ₁ , Tatjana Pyragienė ₁ , Peter A Tass ₂

Affiliation

Periodic pulse train stimulation is generically used to study the function of the nervous system and to counteract disease-related neuronal activity, e.g., collective periodic neuronal oscillations. The efficient control of neuronal dynamics without compromising brain tissue is key to research and clinical purposes. We here adapt the minimum charge control theory, recently developed for a single neuron, to a network of interacting neurons exhibiting collective periodic oscillations. We present a general expression for the optimal waveform, which provides an entrainment of a neural network to the stimulation frequency with a minimum absolute value of the stimulating current. As in the case of a single neuron, the optimal waveform is of bang-off-bang type, but its parameters are now determined by the parameters of the effective phase response curve of the entire network, rather than of a single neuron. The theoretical results are confirmed by three specific examples: two small-scale networks of FitzHugh-Nagumo neurons with synaptic and electric couplings, as well as a large-scale network of synaptically coupled quadratic integrate-and-fire neurons.

中文翻译：

带有最小刺激电荷的相互作用神经元网络的夹带。

周期性脉冲序列刺激通常用于研究神经系统的功能并抵消与疾病相关的神经元活动，例如集体性周期性神经元振荡。在不损害脑组织的情况下有效控制神经元动力学是研究和临床目的的关键。我们在这里将最近针对单个神经元开发的最小电荷控制理论调整为具有集体周期性振荡的相互作用神经元网络。我们提出了最佳波形的一般表达式，它以最小的刺激电流绝对值为刺激频率提供了神经网络的夹带。与单个神经元的情况一样，最佳波形是爆炸式的，但其参数现在由整个网络而不是单个神经元的有效相位响应曲线的参数确定。理论结果由三个具体示例证实：两个具有突触和电耦合的FitzHugh-Nagumo神经元的小规模网络，以及一个由突触耦合的二次积分和发射神经元的大规模网络。

更新日期：2020-07-30

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