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Face familiarity detection with complex synapses
Synaptic plasticity is a complex phenomenon involving multiple biochemical processes that operate on different timescales. Complexity can greatly increase memory capacity when the variables characterizing the synaptic dynamics have limited precision, as shown in simple memory retrieval problems invo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829748/ https://www.ncbi.nlm.nih.gov/pubmed/36636347 http://dx.doi.org/10.1016/j.isci.2022.105856 |
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author | Ji-An, Li Stefanini, Fabio Benna, Marcus K. Fusi, Stefano |
author_facet | Ji-An, Li Stefanini, Fabio Benna, Marcus K. Fusi, Stefano |
author_sort | Ji-An, Li |
collection | PubMed |
description | Synaptic plasticity is a complex phenomenon involving multiple biochemical processes that operate on different timescales. Complexity can greatly increase memory capacity when the variables characterizing the synaptic dynamics have limited precision, as shown in simple memory retrieval problems involving random patterns. Here we turn to a real-world problem, face familiarity detection, and we show that synaptic complexity can be harnessed to store in memory a large number of faces that can be recognized at a later time. The number of recognizable faces grows almost linearly with the number of synapses and quadratically with the number of neurons. Complex synapses outperform simple ones characterized by a single variable, even when the total number of dynamical variables is matched. Complex and simple synapses have distinct signatures that are testable in experiments. Our results indicate that a system with complex synapses can be used in real-world tasks such as face familiarity detection. |
format | Online Article Text |
id | pubmed-9829748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-98297482023-01-11 Face familiarity detection with complex synapses Ji-An, Li Stefanini, Fabio Benna, Marcus K. Fusi, Stefano iScience Article Synaptic plasticity is a complex phenomenon involving multiple biochemical processes that operate on different timescales. Complexity can greatly increase memory capacity when the variables characterizing the synaptic dynamics have limited precision, as shown in simple memory retrieval problems involving random patterns. Here we turn to a real-world problem, face familiarity detection, and we show that synaptic complexity can be harnessed to store in memory a large number of faces that can be recognized at a later time. The number of recognizable faces grows almost linearly with the number of synapses and quadratically with the number of neurons. Complex synapses outperform simple ones characterized by a single variable, even when the total number of dynamical variables is matched. Complex and simple synapses have distinct signatures that are testable in experiments. Our results indicate that a system with complex synapses can be used in real-world tasks such as face familiarity detection. Elsevier 2022-12-22 /pmc/articles/PMC9829748/ /pubmed/36636347 http://dx.doi.org/10.1016/j.isci.2022.105856 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Ji-An, Li Stefanini, Fabio Benna, Marcus K. Fusi, Stefano Face familiarity detection with complex synapses |
title | Face familiarity detection with complex synapses |
title_full | Face familiarity detection with complex synapses |
title_fullStr | Face familiarity detection with complex synapses |
title_full_unstemmed | Face familiarity detection with complex synapses |
title_short | Face familiarity detection with complex synapses |
title_sort | face familiarity detection with complex synapses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829748/ https://www.ncbi.nlm.nih.gov/pubmed/36636347 http://dx.doi.org/10.1016/j.isci.2022.105856 |
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