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How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output
Neurons integrate from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the few ‘strong’ synapses are formed between similarly tuned cells, suggesting they determine spiking output. This raises the question of how other computational primitives, inc...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153727/ https://www.ncbi.nlm.nih.gov/pubmed/37068099 http://dx.doi.org/10.1371/journal.pcbi.1011046 |
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author | Buchholz, Moritz O. Gastone Guilabert, Alexandra Ehret, Benjamin Schuhknecht, Gregor F. P. |
author_facet | Buchholz, Moritz O. Gastone Guilabert, Alexandra Ehret, Benjamin Schuhknecht, Gregor F. P. |
author_sort | Buchholz, Moritz O. |
collection | PubMed |
description | Neurons integrate from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the few ‘strong’ synapses are formed between similarly tuned cells, suggesting they determine spiking output. This raises the question of how other computational primitives, including ‘background’ activity from the many ‘weak’ synapses, short-term plasticity, and temporal factors contribute to spiking. We used paired recordings and extracellular stimulation experiments to map excitatory postsynaptic potential (EPSP) amplitudes and paired-pulse ratios of synaptic connections formed between pyramidal neurons in layer 2/3 (L2/3) of barrel cortex. While net short-term plasticity was weak, strong synaptic connections were exclusively depressing. Importantly, we found no evidence for clustering of synaptic properties on individual neurons. Instead, EPSPs and paired-pulse ratios of connections converging onto the same cells spanned the full range observed across L2/3, which critically constrains theoretical models of cortical filtering. To investigate how different computational primitives of synaptic information processing interact to shape spiking, we developed a computational model of a pyramidal neuron in the excitatory L2/3 circuitry, which was constrained by our experiments and published in vivo data. We found that strong synapses were substantially depressed during ongoing activation and their ability to evoke correlated spiking primarily depended on their high temporal synchrony and high firing rates observed in vivo. However, despite this depression, their larger EPSP amplitudes strongly amplified information transfer and responsiveness. Thus, our results contribute to a nuanced framework of how cortical neurons exploit synergies between temporal coding, synaptic properties, and noise to transform synaptic inputs into spikes. |
format | Online Article Text |
id | pubmed-10153727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-101537272023-05-03 How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output Buchholz, Moritz O. Gastone Guilabert, Alexandra Ehret, Benjamin Schuhknecht, Gregor F. P. PLoS Comput Biol Research Article Neurons integrate from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the few ‘strong’ synapses are formed between similarly tuned cells, suggesting they determine spiking output. This raises the question of how other computational primitives, including ‘background’ activity from the many ‘weak’ synapses, short-term plasticity, and temporal factors contribute to spiking. We used paired recordings and extracellular stimulation experiments to map excitatory postsynaptic potential (EPSP) amplitudes and paired-pulse ratios of synaptic connections formed between pyramidal neurons in layer 2/3 (L2/3) of barrel cortex. While net short-term plasticity was weak, strong synaptic connections were exclusively depressing. Importantly, we found no evidence for clustering of synaptic properties on individual neurons. Instead, EPSPs and paired-pulse ratios of connections converging onto the same cells spanned the full range observed across L2/3, which critically constrains theoretical models of cortical filtering. To investigate how different computational primitives of synaptic information processing interact to shape spiking, we developed a computational model of a pyramidal neuron in the excitatory L2/3 circuitry, which was constrained by our experiments and published in vivo data. We found that strong synapses were substantially depressed during ongoing activation and their ability to evoke correlated spiking primarily depended on their high temporal synchrony and high firing rates observed in vivo. However, despite this depression, their larger EPSP amplitudes strongly amplified information transfer and responsiveness. Thus, our results contribute to a nuanced framework of how cortical neurons exploit synergies between temporal coding, synaptic properties, and noise to transform synaptic inputs into spikes. Public Library of Science 2023-04-17 /pmc/articles/PMC10153727/ /pubmed/37068099 http://dx.doi.org/10.1371/journal.pcbi.1011046 Text en © 2023 Buchholz et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Buchholz, Moritz O. Gastone Guilabert, Alexandra Ehret, Benjamin Schuhknecht, Gregor F. P. How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
title | How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
title_full | How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
title_fullStr | How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
title_full_unstemmed | How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
title_short | How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
title_sort | how synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153727/ https://www.ncbi.nlm.nih.gov/pubmed/37068099 http://dx.doi.org/10.1371/journal.pcbi.1011046 |
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