Emulating short-term synaptic dynamics with memristive devices

Emulating short-term synaptic dynamics with memristive devices

Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state Ti...

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Main Authors: Berdan, Radu, Vasilaki, Eleni, Khiat, Ali, Indiveri, Giacomo, Serb, Alexandru, Prodromakis, Themistoklis
Format: Online
Language:English
Published: Nature Publishing Group 2016
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4698662/
id pubmed-4698662
recordtype oai_dc
spelling pubmed-46986622016-01-13 Emulating short-term synaptic dynamics with memristive devices Berdan, Radu Vasilaki, Eleni Khiat, Ali Indiveri, Giacomo Serb, Alexandru Prodromakis, Themistoklis Article Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems. Nature Publishing Group 2016-01-04 /pmc/articles/PMC4698662/ /pubmed/26725838 http://dx.doi.org/10.1038/srep18639 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Berdan, Radu
Vasilaki, Eleni
Khiat, Ali
Indiveri, Giacomo
Serb, Alexandru
Prodromakis, Themistoklis
spellingShingle Berdan, Radu
Vasilaki, Eleni
Khiat, Ali
Indiveri, Giacomo
Serb, Alexandru
Prodromakis, Themistoklis
Emulating short-term synaptic dynamics with memristive devices
author_facet Berdan, Radu
Vasilaki, Eleni
Khiat, Ali
Indiveri, Giacomo
Serb, Alexandru
Prodromakis, Themistoklis
author_sort Berdan, Radu
title Emulating short-term synaptic dynamics with memristive devices
title_short Emulating short-term synaptic dynamics with memristive devices
title_full Emulating short-term synaptic dynamics with memristive devices
title_fullStr Emulating short-term synaptic dynamics with memristive devices
title_full_unstemmed Emulating short-term synaptic dynamics with memristive devices
title_sort emulating short-term synaptic dynamics with memristive devices
description Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.
publisher Nature Publishing Group
publishDate 2016
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4698662/
_version_ 1613519062310060032

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