Emulating the electrical activity of the neuron using a silicon oxide RRAM cell

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...

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Main Authors: Adnan eMehonic, Anthony eKenyon
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-02-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00057/full
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spelling doaj-17b6ed6f3b314a2f9811ed8582d97ce22020-11-25T00:34:38ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2016-02-011010.3389/fnins.2016.00057174123Emulating the electrical activity of the neuron using a silicon oxide RRAM cellAdnan eMehonic0Anthony eKenyon1University College LondonUniversity College LondonIn 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.http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00057/fullneuromorphic engineeringMemristorNeuronal dynamicsHodgkin-Huxleyresistive switchingRRAM
collection DOAJ
language English
format Article
sources DOAJ
author Adnan eMehonic
Anthony eKenyon
spellingShingle Adnan eMehonic
Anthony eKenyon
Emulating the electrical activity of the neuron using a silicon oxide RRAM cell
Frontiers in Neuroscience
neuromorphic engineering
Memristor
Neuronal dynamics
Hodgkin-Huxley
resistive switching
RRAM
author_facet Adnan eMehonic
Anthony eKenyon
author_sort Adnan eMehonic
title Emulating the electrical activity of the neuron using a silicon oxide RRAM cell
title_short Emulating the electrical activity of the neuron using a silicon oxide RRAM cell
title_full Emulating the electrical activity of the neuron using a silicon oxide RRAM cell
title_fullStr Emulating the electrical activity of the neuron using a silicon oxide RRAM cell
title_full_unstemmed Emulating the electrical activity of the neuron using a silicon oxide RRAM cell
title_sort emulating the electrical activity of the neuron using a silicon oxide rram cell
publisher Frontiers Media S.A.
series Frontiers in Neuroscience
issn 1662-453X
publishDate 2016-02-01
description 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.
topic neuromorphic engineering
Memristor
Neuronal dynamics
Hodgkin-Huxley
resistive switching
RRAM
url http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00057/full
work_keys_str_mv AT adnanemehonic emulatingtheelectricalactivityoftheneuronusingasiliconoxiderramcell
AT anthonyekenyon emulatingtheelectricalactivityoftheneuronusingasiliconoxiderramcell
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