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Principles for coding associative memories in a compact neural network
A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10159626/ https://www.ncbi.nlm.nih.gov/pubmed/37140557 http://dx.doi.org/10.7554/eLife.74434 |
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author | Pritz, Christian Itskovits, Eyal Bokman, Eduard Ruach, Rotem Gritsenko, Vladimir Nelken, Tal Menasherof, Mai Azulay, Aharon Zaslaver, Alon |
author_facet | Pritz, Christian Itskovits, Eyal Bokman, Eduard Ruach, Rotem Gritsenko, Vladimir Nelken, Tal Menasherof, Mai Azulay, Aharon Zaslaver, Alon |
author_sort | Pritz, Christian |
collection | PubMed |
description | A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation. |
format | Online Article Text |
id | pubmed-10159626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-101596262023-05-05 Principles for coding associative memories in a compact neural network Pritz, Christian Itskovits, Eyal Bokman, Eduard Ruach, Rotem Gritsenko, Vladimir Nelken, Tal Menasherof, Mai Azulay, Aharon Zaslaver, Alon eLife Computational and Systems Biology A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation. eLife Sciences Publications, Ltd 2023-05-04 /pmc/articles/PMC10159626/ /pubmed/37140557 http://dx.doi.org/10.7554/eLife.74434 Text en © 2023, Pritz et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Pritz, Christian Itskovits, Eyal Bokman, Eduard Ruach, Rotem Gritsenko, Vladimir Nelken, Tal Menasherof, Mai Azulay, Aharon Zaslaver, Alon Principles for coding associative memories in a compact neural network |
title | Principles for coding associative memories in a compact neural network |
title_full | Principles for coding associative memories in a compact neural network |
title_fullStr | Principles for coding associative memories in a compact neural network |
title_full_unstemmed | Principles for coding associative memories in a compact neural network |
title_short | Principles for coding associative memories in a compact neural network |
title_sort | principles for coding associative memories in a compact neural network |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10159626/ https://www.ncbi.nlm.nih.gov/pubmed/37140557 http://dx.doi.org/10.7554/eLife.74434 |
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