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Palimpsest memories stored in memristive synapses
Biological synapses store multiple memories on top of each other in a palimpsest fashion and at different time scales. Palimpsest consolidation is facilitated by the interaction of hidden biochemical processes governing synaptic efficacy during varying lifetimes. This arrangement allows idle memorie...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9217086/ https://www.ncbi.nlm.nih.gov/pubmed/35731877 http://dx.doi.org/10.1126/sciadv.abn7920 |
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author | Giotis, Christos Serb, Alexander Manouras, Vasileios Stathopoulos, Spyros Prodromakis, Themis |
author_facet | Giotis, Christos Serb, Alexander Manouras, Vasileios Stathopoulos, Spyros Prodromakis, Themis |
author_sort | Giotis, Christos |
collection | PubMed |
description | Biological synapses store multiple memories on top of each other in a palimpsest fashion and at different time scales. Palimpsest consolidation is facilitated by the interaction of hidden biochemical processes governing synaptic efficacy during varying lifetimes. This arrangement allows idle memories to be temporarily overwritten without being forgotten, while previously unseen memories are used in the short term. While embedded artificial intelligence can greatly benefit from this functionality, a practical demonstration in hardware is missing. Here, we show how the intrinsic properties of metal-oxide volatile memristors emulate the processes supporting biological palimpsest consolidation. Our memristive synapses exhibit an expanded doubled capacity and protect a consolidated memory while up to hundreds of uncorrelated short-term memories temporarily overwrite it, without requiring specialized instructions. We further demonstrate this technology in the context of visual working memory. This showcases how emerging memory technologies can efficiently expand the capabilities of artificial intelligence hardware toward more generalized learning memories. |
format | Online Article Text |
id | pubmed-9217086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92170862022-07-07 Palimpsest memories stored in memristive synapses Giotis, Christos Serb, Alexander Manouras, Vasileios Stathopoulos, Spyros Prodromakis, Themis Sci Adv Physical and Materials Sciences Biological synapses store multiple memories on top of each other in a palimpsest fashion and at different time scales. Palimpsest consolidation is facilitated by the interaction of hidden biochemical processes governing synaptic efficacy during varying lifetimes. This arrangement allows idle memories to be temporarily overwritten without being forgotten, while previously unseen memories are used in the short term. While embedded artificial intelligence can greatly benefit from this functionality, a practical demonstration in hardware is missing. Here, we show how the intrinsic properties of metal-oxide volatile memristors emulate the processes supporting biological palimpsest consolidation. Our memristive synapses exhibit an expanded doubled capacity and protect a consolidated memory while up to hundreds of uncorrelated short-term memories temporarily overwrite it, without requiring specialized instructions. We further demonstrate this technology in the context of visual working memory. This showcases how emerging memory technologies can efficiently expand the capabilities of artificial intelligence hardware toward more generalized learning memories. American Association for the Advancement of Science 2022-06-22 /pmc/articles/PMC9217086/ /pubmed/35731877 http://dx.doi.org/10.1126/sciadv.abn7920 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Giotis, Christos Serb, Alexander Manouras, Vasileios Stathopoulos, Spyros Prodromakis, Themis Palimpsest memories stored in memristive synapses |
title | Palimpsest memories stored in memristive synapses |
title_full | Palimpsest memories stored in memristive synapses |
title_fullStr | Palimpsest memories stored in memristive synapses |
title_full_unstemmed | Palimpsest memories stored in memristive synapses |
title_short | Palimpsest memories stored in memristive synapses |
title_sort | palimpsest memories stored in memristive synapses |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9217086/ https://www.ncbi.nlm.nih.gov/pubmed/35731877 http://dx.doi.org/10.1126/sciadv.abn7920 |
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