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Emulating the Electrical Activity of the Neuron Using a Silicon Oxide RRAM Cell

Mehonic, A; Kenyon, AJ; (2016) Emulating the Electrical Activity of the Neuron Using a Silicon Oxide RRAM Cell. Frontiers in Neuroscience , 10 , Article 57. 10.3389/fnins.2016.00057. Green open access

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Abstract

In recent years, formidable effort has been devoted to exploring the potential of Resistive RAM (RRAM) devices to model key features of biological synapses. This is done to strengthen the link between neuro-computing architectures and neuroscience, bearing in mind the extremely low power consumption and immense parallelism of biological systems. Here we demonstrate the feasibility of using the RRAM cell to go further and to model aspects of the electrical activity of the neuron. We focus on the specific operational procedures required for the generation of controlled voltage transients, which resemble spike-like responses. Further, we demonstrate that RRAM devices are capable of integrating input current pulses over time to produce thresholded voltage transients. We show that the frequency of the output transients can be controlled by the input signal, and we relate recent models of the redox-based nanoionic resistive memory cell to two common neuronal models, the Hodgkin-Huxley (HH) conductance model and the leaky integrate-and-fire model. We employ a simplified circuit model to phenomenologically describe voltage transient generation.

Type: Article
Title: Emulating the Electrical Activity of the Neuron Using a Silicon Oxide RRAM Cell
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fnins.2016.00057
Publisher version: http://dx.doi.org/10.3389/fnins.2016.00057
Language: English
Additional information: © 2016 Mehonic and Kenyon. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: resistive switching, neuronal dynamics, Hodgkin-Huxley, leaky integrate-and-fire, memristor
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1475214
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