Experimental active spike responses of analog electrical neuron: beyond “integrate-and-fire” transmission

被引:0
|
作者
Aurélien Serge Tchakoutio Nguetcho
Stéphane Binczak
Victor Borisovich Kazantsev
Sabir Jacquir
Jean-Marie Bilbault
机构
[1] Université de Maroua,Laboratoire Interdisciplinaire des Sciences et Sciences Appliquées du Sahel (LISSAS), Département de Physique, Faculté des Sciences
[2] Univ. Bourgogne Franche-Comté,Laboratoire LE2I UMR 6306, CNRS, Arts et Métiers
[3] Nizhny Novgorod State University,Neuroscience Center
来源
Nonlinear Dynamics | 2015年 / 82卷
关键词
FitzHugh–Nagumo model; Phase portrait; Nonlinear electrical circuit; Electrical neuron; Electrical pulse stimulation; Interspike interval; Spikes response; Transmission coefficient;
D O I
暂无
中图分类号
学科分类号
摘要
Using an analog electrical FitzHugh–Nagumo neuron including complex threshold excitation (CTE) properties, we analyze its spiking responses on pulse stimulation. The system is subjected to external pulse stimulus and can generate nonlinear integrate-and-fire and resonant responses which are typical for excitable neuronal cells. Following earlier theoretical predictions, we found that for certain parameters range, there is a possibility to trigger a spiking sequence with a finite number of spikes in response to a single short stimulus pulse. Hence, active transformation of N incoming pulses to M outgoing spikes is possible. We also show that the nonlinear electrical circuit with the CTE feature can be effectively synchronized by a periodic pulse train with 1 to M spike frequency ratio.
引用
收藏
页码:1595 / 1604
页数:9
相关论文
共 50 条
  • [41] On a Generalized Leaky Integrate-and-Fire Model for Single Neuron Activity
    Buonocore, Aniello
    Caputo, Luigia
    Pirozzi, Enrica
    Ricciardi, Luigi M.
    COMPUTER AIDED SYSTEMS THEORY - EUROCAST 2009, 2009, 5717 : 152 - +
  • [42] Computing with the leaky integrate-and-fire neuron: Logarithmic computation and multiplication
    Tal, D
    Schwartz, EL
    NEURAL COMPUTATION, 1997, 9 (02) : 305 - 318
  • [43] Analysis of the Leaky Integrate-and-Fire neuron model for GPU implementation
    Venetis, Ioannis E.
    Provata, Astero
    Journal of Parallel and Distributed Computing, 2022, 163 : 1 - 19
  • [44] A low-power adaptive integrate-and-fire neuron circuit
    Indiveri, G
    PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL IV: DIGITAL SIGNAL PROCESSING-COMPUTER AIDED NETWORK DESIGN-ADVANCED TECHNOLOGY, 2003, : 820 - 823
  • [45] Approximating the response-stimulus correlation for the integrate-and-fire neuron
    Kanev, J
    Wenning, G
    Obermayer, K
    COMPUTATIONAL NEUROSCIENCE: TRENDS IN RESEARCH 2004, 2004, : 47 - 52
  • [46] Integrate-and-Fire Neuron Circuit Without External Bias Voltages
    Park, Young-Soo
    Woo, Sola
    Lim, Doohyeok
    Cho, Kyoungah
    Kim, Sangsig
    FRONTIERS IN NEUROSCIENCE, 2021, 15
  • [47] PWM characteristics of capacitor-free integrate-and-fire neuron
    Barnes, BC
    Wells, RB
    Frenzel, JF
    ELECTRONICS LETTERS, 2003, 39 (16) : 1191 - 1193
  • [48] Demonstration of integrate-and-fire neuron circuit for spiking neural networks
    Woo, Sung Yun
    Kang, Won-Mook
    Seo, Young-Tak
    Lee, Soochang
    Kwon, Dongseok
    Oh, Seongbin
    Bae, Jong-Ho
    Lee, Jong-Ho
    SOLID-STATE ELECTRONICS, 2022, 198
  • [49] PCMO RRAM for Integrate-and-Fire Neuron in Spiking Neural Networks
    Lashkare, S.
    Chouhan, S.
    Chavan, T.
    Bhat, A.
    Kumbhare, P.
    Ganguly, U.
    IEEE ELECTRON DEVICE LETTERS, 2018, 39 (04) : 484 - 487
  • [50] A Biological Plausible Generalized Leaky Integrate-and-Fire Neuron Model
    Wang, Zhenzhong
    Guo, Lilin
    Adjouadi, Malek
    2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2014, : 6810 - 6813