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The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations
Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear whether simple neurons, consisting of a few or even a single neurite, may perform local computations as well. To ad...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934027/ https://www.ncbi.nlm.nih.gov/pubmed/36630454 http://dx.doi.org/10.1073/pnas.2201699120 |
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author | Ruach, Rotem Ratner, Nir Emmons, Scott W. Zaslaver, Alon |
author_facet | Ruach, Rotem Ratner, Nir Emmons, Scott W. Zaslaver, Alon |
author_sort | Ruach, Rotem |
collection | PubMed |
description | Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear whether simple neurons, consisting of a few or even a single neurite, may perform local computations as well. To address this question, we focused on the compact neural network of Caenorhabditis elegans animals for which the full wiring diagram is available, including the coordinates of individual synapses. We find that the positions of the chemical synapses along the neurites are not randomly distributed nor can they be explained by anatomical constraints. Instead, synapses tend to form clusters, an organization that supports local compartmentalized computations. In mutually synapsing neurons, connections of opposite polarity cluster separately, suggesting that positive and negative feedback dynamics may be implemented in discrete compartmentalized regions along neurites. In triple-neuron circuits, the nonrandom synaptic organization may facilitate local functional roles, such as signal integration and coordinated activation of functionally related downstream neurons. These clustered synaptic topologies emerge as a guiding principle in the network, presumably to facilitate distinct parallel functions along a single neurite, which effectively increase the computational capacity of the neural network. |
format | Online Article Text |
id | pubmed-9934027 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-99340272023-07-11 The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations Ruach, Rotem Ratner, Nir Emmons, Scott W. Zaslaver, Alon Proc Natl Acad Sci U S A Biological Sciences Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear whether simple neurons, consisting of a few or even a single neurite, may perform local computations as well. To address this question, we focused on the compact neural network of Caenorhabditis elegans animals for which the full wiring diagram is available, including the coordinates of individual synapses. We find that the positions of the chemical synapses along the neurites are not randomly distributed nor can they be explained by anatomical constraints. Instead, synapses tend to form clusters, an organization that supports local compartmentalized computations. In mutually synapsing neurons, connections of opposite polarity cluster separately, suggesting that positive and negative feedback dynamics may be implemented in discrete compartmentalized regions along neurites. In triple-neuron circuits, the nonrandom synaptic organization may facilitate local functional roles, such as signal integration and coordinated activation of functionally related downstream neurons. These clustered synaptic topologies emerge as a guiding principle in the network, presumably to facilitate distinct parallel functions along a single neurite, which effectively increase the computational capacity of the neural network. National Academy of Sciences 2023-01-11 2023-01-17 /pmc/articles/PMC9934027/ /pubmed/36630454 http://dx.doi.org/10.1073/pnas.2201699120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Ruach, Rotem Ratner, Nir Emmons, Scott W. Zaslaver, Alon The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations |
title | The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations |
title_full | The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations |
title_fullStr | The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations |
title_full_unstemmed | The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations |
title_short | The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations |
title_sort | synaptic organization in the caenorhabditis elegans neural network suggests significant local compartmentalized computations |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934027/ https://www.ncbi.nlm.nih.gov/pubmed/36630454 http://dx.doi.org/10.1073/pnas.2201699120 |
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