NDLI: Active spike responses of analog electrical neuron: Theory and experiments

Content Provider	IEEE Xplore Digital Library
Author	Binczak, S. Nguetcho, A.S.T. Jacquir, S. Bilbault, J.M. Kazantsev, V.B.
Copyright Year	2010
Description	Author affiliation: Laboratoire LE2I, CNRS UMR 5158, Aile des Sciences de l'lngenieur, Universite de Bourgogne, BP 47870, Dijon Cedex, France (Binczak, S.; Nguetcho, A.S.T.; Jacquir, S.; Bilbault, J.M.) \|\| Institute of Applied Physics of RAS, 46 Uljanov str., 603950 Nizhny Novgorod, Russia (Kazantsev, V.B.)
Abstract	Using an analog electrical FitzHugh-Nagumo neuron including complex threshold excitation (CTE) properties, we analyze its spiking responses under pulse stimulation corresponding to oscillating threshold manifold. The system is subjected to outside pulse stimulus and can generate nonlinear integrate-and-flre and resonant responses which are typical for excitable neuronal cells ("all-or-none"). The answer of the neuron strongly depends on the number and the characteristics of incoming impulses (amplitude, width, strength and frequency). For certain parameters range, there is a possibility to trigger a spiking sequence with a finite number of spikes in response of a single short stimulus pulse. Thus active transformation of N incoming pulses to M outgoing spikes is possible. The predicted theoretical results are found and observed in a nonlinear electrical circuit mimicking the CTE mode, which enlighten the robustness of these phenomena.
Starting Page	2550
Ending Page	2553
File Size	777862
Page Count	4
File Format	PDF
ISBN	9781424453085
DOI	10.1109/ISCAS.2010.5537112
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-30
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Circuits Biomembranes Robustness Shape control Physics Pulse generation Resonance Frequency Intersymbol interference interspike interval (ISI) Nonlinear electrical circuit FitzHugh-Nagumo model Neuron Nonlinear waves
Content Type	Text
Resource Type	Article

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