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菲茨休-纳古莫神经元的输入信号积累能力。

Input signal accumulation capability of the FitzHugh-Nagumo neuron.

作者信息

Bukh A V, Shepelev I A, Vadivasova T E

机构信息

Institute of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov 410012, Russia.

Almetyevsk State Petroleum Institute, 2 Lenin Street, Almetyevsk 423462, Russia.

出版信息

Chaos. 2024 Dec 1;34(12). doi: 10.1063/5.0243083.

Abstract

We present numerical results on the effects of two presynaptic FitzHugh-Nagumo neurons on a postsynaptic neuron under unidirectional electrical coupling. The presynaptic neurons affect the postsynaptic neuron not simultaneously but with a certain time shift. We consider cases where the amplitudes of the presynaptic spikes can be both higher and lower than the excitation threshold level. The latter case receives the main attention in our work. We carefully examine the conditions under which the postsynaptic neuron is excited by the two asynchronous external spikes. With arbitrarily chosen parameters, the FitzHugh-Nagumo neuron is almost incapable of accumulating the energy of external signals, unlike, for example, the leaky integrate-and-fire neuron. In this case, the postsynaptic neuron only excites with a very short time delay between external impulses. However, we have discovered, for the first time, a parameter region where neuron excitation is possible even with significant time delays between presynaptic impulses with subthreshold amplitudes. We explain this effect in detail and describe the mechanism behind its occurrence. We identify the boundaries of this region in the parameter plane of time delay and coupling coefficient by varying the control parameter values of the neurons. The FitzHugh-Nagumo neuron has not previously been used as a node in spiking neural networks for training via spike-timing-dependent plasticity due to the lack of an integrate-and-fire effect. However, the detection of a certain range of parameters makes the potential application of this neuron for STDP training possible.

摘要

我们给出了在单向电耦合下,两个突触前FitzHugh-Nagumo神经元对一个突触后神经元影响的数值结果。突触前神经元对突触后神经元的影响不是同时发生的,而是有一定的时间延迟。我们考虑了突触前尖峰幅度高于和低于兴奋阈值水平的情况。后一种情况是我们工作中的主要关注点。我们仔细研究了突触后神经元被两个异步外部尖峰激发的条件。与例如漏电积分发放神经元不同,在任意选择参数的情况下,FitzHugh-Nagumo神经元几乎无法积累外部信号的能量。在这种情况下,突触后神经元仅在外部脉冲之间有非常短的时间延迟时才会激发。然而,我们首次发现了一个参数区域,即使突触前脉冲幅度低于阈值且存在显著的时间延迟,神经元激发也是可能的。我们详细解释了这种效应,并描述了其发生背后的机制。通过改变神经元的控制参数值,我们在时间延迟和耦合系数的参数平面中确定了该区域的边界。由于缺乏积分发放效应,FitzHugh-Nagumo神经元此前未被用作通过依赖于脉冲时间的可塑性进行训练的脉冲神经网络中的节点。然而,特定参数范围的发现使得该神经元在STDP训练中的潜在应用成为可能。

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