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Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time
Neurons’ primary function is to encode and transmit information in the brain and body. The branching architecture of axons and dendrites must compute, respond and make decisions while obeying the rules of the substrate in which they are enmeshed. Thus, it is important to delineate and understand the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10480011/ https://www.ncbi.nlm.nih.gov/pubmed/37669695 http://dx.doi.org/10.1098/rsif.2023.0265 |
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author | Desai-Chowdhry, Paheli Brummer, Alexander B. Mallavarapu, Samhita Savage, Van M. |
author_facet | Desai-Chowdhry, Paheli Brummer, Alexander B. Mallavarapu, Samhita Savage, Van M. |
author_sort | Desai-Chowdhry, Paheli |
collection | PubMed |
description | Neurons’ primary function is to encode and transmit information in the brain and body. The branching architecture of axons and dendrites must compute, respond and make decisions while obeying the rules of the substrate in which they are enmeshed. Thus, it is important to delineate and understand the principles that govern these branching patterns. Here, we present evidence that asymmetric branching is a key factor in understanding the functional properties of neurons. First, we derive novel predictions for asymmetric scaling exponents that encapsulate branching architecture associated with crucial principles such as conduction time, power minimization and material costs. We compare our predictions with extensive data extracted from images to associate specific principles with specific biophysical functions and cell types. Notably, we find that asymmetric branching models lead to predictions and empirical findings that correspond to different weightings of the importance of maximum, minimum or total path lengths from the soma to the synapses. These different path lengths quantitatively and qualitatively affect energy, time and materials. Moreover, we generally observe that higher degrees of asymmetric branching—potentially arising from extrinsic environmental cues and synaptic plasticity in response to activity—occur closer to the tips than the soma (cell body). |
format | Online Article Text |
id | pubmed-10480011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104800112023-09-06 Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time Desai-Chowdhry, Paheli Brummer, Alexander B. Mallavarapu, Samhita Savage, Van M. J R Soc Interface Life Sciences–Mathematics interface Neurons’ primary function is to encode and transmit information in the brain and body. The branching architecture of axons and dendrites must compute, respond and make decisions while obeying the rules of the substrate in which they are enmeshed. Thus, it is important to delineate and understand the principles that govern these branching patterns. Here, we present evidence that asymmetric branching is a key factor in understanding the functional properties of neurons. First, we derive novel predictions for asymmetric scaling exponents that encapsulate branching architecture associated with crucial principles such as conduction time, power minimization and material costs. We compare our predictions with extensive data extracted from images to associate specific principles with specific biophysical functions and cell types. Notably, we find that asymmetric branching models lead to predictions and empirical findings that correspond to different weightings of the importance of maximum, minimum or total path lengths from the soma to the synapses. These different path lengths quantitatively and qualitatively affect energy, time and materials. Moreover, we generally observe that higher degrees of asymmetric branching—potentially arising from extrinsic environmental cues and synaptic plasticity in response to activity—occur closer to the tips than the soma (cell body). The Royal Society 2023-09-06 /pmc/articles/PMC10480011/ /pubmed/37669695 http://dx.doi.org/10.1098/rsif.2023.0265 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Mathematics interface Desai-Chowdhry, Paheli Brummer, Alexander B. Mallavarapu, Samhita Savage, Van M. Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
title | Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
title_full | Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
title_fullStr | Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
title_full_unstemmed | Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
title_short | Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
title_sort | neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time |
topic | Life Sciences–Mathematics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10480011/ https://www.ncbi.nlm.nih.gov/pubmed/37669695 http://dx.doi.org/10.1098/rsif.2023.0265 |
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