A Qualitative Approach for the Design of a Locally Active Memristor Based Neuron Circuit

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Beitragende

Abstract

Neuromorphic circuit design utilizing emergent memory technologies has been recently popular due to the rich intrinsic dynamics accommodating in nanoscale devices, namely in threshold switches or locally active memristors (LAMs). In this work, we introduce a qualitative approach for the design of a locally active memristor based 2nd order bio-inspired neuron circuit. We initially examine the phase plane characteristics of the 2nd order biologically plausible INa,p + IK neuron model and compare them with the same characteristics of the LAM based Leaky integrate and Fire (LIF) neuron circuit. Consequently, we define the current of the LAM as the spiking variable and voltage of the parallel capacitor as the recovery variable for the LIF circuit. Then, in order to match the phase plane characteristics of the INa,p + IK model, we adopt a qualitative approach and modify the LIF circuit by replacing the linear bias resistor with a nonlinear counterpart with a sinh nonlinearity. This way, we show that the proposed circuit can better capture the neuronal dynamics of the INa,p + IK model and exhibit distinctive features such as the co-existence of resting and limit cycle states. Our future work should cover quantitative analysis for the precise implementation of the neuronal dynamical features.

Details

OriginalspracheEnglisch
TitelICECS 2023 - 2023 30th IEEE International Conference on Electronics, Circuits and Systems
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten1-4
ISBN (elektronisch)9798350326499
PublikationsstatusVeröffentlicht - 2023
Peer-Review-StatusJa

Publikationsreihe

ReiheIEEE International Conference on Electronics, Circuits and Systems (ICECS)

Konferenz

Titel30th IEEE International Conference on Electronics, Circuits and Systems
KurztitelICECS 2023
Veranstaltungsnummer30
Dauer4 - 7 Dezember 2023
Webseite
OrtHilton Maslak
StadtIstanbul
LandTürkei

Externe IDs

ORCID /0000-0001-7436-0103/work/172081489
ORCID /0000-0002-1236-1300/work/172082271

Schlagworte

Schlagwörter

  • biological plausibility, INa,p + IK model, Locally active memristor, neuron circuit model, threshold switch