Input signal accumulation capability of the FitzHugh-Nagumo neuron

被引:0
|
作者
Bukh, A. V. [1 ]
Shepelev, I. A. [1 ,2 ]
Vadivasova, T. E. [1 ]
机构
[1] Saratov NG Chernyshevskii State Univ, Inst Phys, 83 Astrakhanskaya St, Saratov 410012, Russia
[2] Almetyevsk State Petr Inst, 2 Lenin St, Almetyevsk 423462, Russia
基金
俄罗斯科学基金会;
关键词
NETWORKS; DYNAMICS; SPIKE; EXCITABILITY; OSCILLATIONS; PLASTICITY; COHERENCE;
D O I
10.1063/5.0243083
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Electronic Model of FitzHugh-Nagumo Neuron
    Petrovas, A.
    Lisauskas, S.
    Slepikas, A.
    ELEKTRONIKA IR ELEKTROTECHNIKA, 2012, 122 (06) : 117 - 120
  • [2] On a modification of the FitzHugh-Nagumo neuron model
    S. D. Glyzin
    A. Yu. Kolesov
    N. Kh. Rozov
    Computational Mathematics and Mathematical Physics, 2014, 54 : 443 - 461
  • [3] On a Modification of the FitzHugh-Nagumo Neuron Model
    Glyzin, S. D.
    Kolesov, A. Yu
    Rozov, N. Kh
    COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS, 2014, 54 (03) : 443 - 461
  • [4] Logical chaotic resonance in the FitzHugh-Nagumo neuron
    Yao, Yuangen
    NONLINEAR DYNAMICS, 2022, 107 (04) : 3887 - 3901
  • [5] A CMOS IMPLEMENTATION OF FITZHUGH-NAGUMO NEURON MODEL
    LINARES-BARRANCO, B
    SANCHEZ-SINENCIO, E
    RODRIGUEZVAZQUEZ, A
    HUERTAS, JL
    IEEE JOURNAL OF SOLID-STATE CIRCUITS, 1991, 26 (07) : 956 - 965
  • [6] Harmonics and intermodulation in subthreshold FitzHugh-Nagumo neuron
    Si, Wenjie
    Wang, Jiang
    Tsang, K. M.
    Chan, W. L.
    CHAOS, 2009, 19 (03)
  • [7] Coexisting firing analysis in a FitzHugh-Nagumo neuron system
    Shi, Wei
    Min, Fuhong
    Zhu, Jie
    NONLINEAR DYNAMICS, 2024, 112 (14) : 12469 - 12484
  • [8] Investigation of Microcontroller Based Model of FitzHugh-Nagumo Neuron
    Petrovas, Andrius
    Lisauskas, Saulius
    Slepikas, Alvydas
    PROCEEDINGS OF 15TH INTERNATIONAL CONFERENCE ON MECHATRONICS - MECHATRONIKA 2012, 2012, : 230 - 233
  • [9] Nonadiabatic resonances in a noisy Fitzhugh-Nagumo neuron model
    Massanés, SR
    Vicente, CJP
    PHYSICAL REVIEW E, 1999, 59 (04) : 4490 - 4497
  • [10] Pattern formation in the Fitzhugh-Nagumo neuron with diffusion relaxation
    Tah, Forwah Amstrong
    Tabi, Conrad Bertrand
    Kofane, Timoleon Crepin
    CHAOS SOLITONS & FRACTALS, 2021, 147