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Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex

The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex...

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Autores principales: Zheng, Pengsheng, Dimitrakakis, Christos, Triesch, Jochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3536614/
https://www.ncbi.nlm.nih.gov/pubmed/23300431
http://dx.doi.org/10.1371/journal.pcbi.1002848
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author Zheng, Pengsheng
Dimitrakakis, Christos
Triesch, Jochen
author_facet Zheng, Pengsheng
Dimitrakakis, Christos
Triesch, Jochen
author_sort Zheng, Pengsheng
collection PubMed
description The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number of synaptic connections of very large efficacy. At the same time, new synaptic connections are constantly being created and individual synaptic connection strengths show substantial fluctuations across time. It remains unclear through what mechanisms these properties of neural circuits arise and how they contribute to learning and memory. In this study we show that fundamental characteristics of excitatory synaptic connections in cortex and hippocampus can be explained as a consequence of self-organization in a recurrent network combining spike-timing-dependent plasticity (STDP), structural plasticity and different forms of homeostatic plasticity. In the network, associative synaptic plasticity in the form of STDP induces a rich-get-richer dynamics among synapses, while homeostatic mechanisms induce competition. Under distinctly different initial conditions, the ensuing self-organization produces long-tailed synaptic strength distributions matching experimental findings. We show that this self-organization can take place with a purely additive STDP mechanism and that multiplicative weight dynamics emerge as a consequence of network interactions. The observed patterns of fluctuation of synaptic strengths, including elimination and generation of synaptic connections and long-term persistence of strong connections, are consistent with the dynamics of dendritic spines found in rat hippocampus. Beyond this, the model predicts an approximately power-law scaling of the lifetimes of newly established synaptic connection strengths during development. Our results suggest that the combined action of multiple forms of neuronal plasticity plays an essential role in the formation and maintenance of cortical circuits.
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spelling pubmed-35366142013-01-08 Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex Zheng, Pengsheng Dimitrakakis, Christos Triesch, Jochen PLoS Comput Biol Research Article The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number of synaptic connections of very large efficacy. At the same time, new synaptic connections are constantly being created and individual synaptic connection strengths show substantial fluctuations across time. It remains unclear through what mechanisms these properties of neural circuits arise and how they contribute to learning and memory. In this study we show that fundamental characteristics of excitatory synaptic connections in cortex and hippocampus can be explained as a consequence of self-organization in a recurrent network combining spike-timing-dependent plasticity (STDP), structural plasticity and different forms of homeostatic plasticity. In the network, associative synaptic plasticity in the form of STDP induces a rich-get-richer dynamics among synapses, while homeostatic mechanisms induce competition. Under distinctly different initial conditions, the ensuing self-organization produces long-tailed synaptic strength distributions matching experimental findings. We show that this self-organization can take place with a purely additive STDP mechanism and that multiplicative weight dynamics emerge as a consequence of network interactions. The observed patterns of fluctuation of synaptic strengths, including elimination and generation of synaptic connections and long-term persistence of strong connections, are consistent with the dynamics of dendritic spines found in rat hippocampus. Beyond this, the model predicts an approximately power-law scaling of the lifetimes of newly established synaptic connection strengths during development. Our results suggest that the combined action of multiple forms of neuronal plasticity plays an essential role in the formation and maintenance of cortical circuits. Public Library of Science 2013-01-03 /pmc/articles/PMC3536614/ /pubmed/23300431 http://dx.doi.org/10.1371/journal.pcbi.1002848 Text en © 2013 Zheng et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zheng, Pengsheng
Dimitrakakis, Christos
Triesch, Jochen
Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
title Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
title_full Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
title_fullStr Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
title_full_unstemmed Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
title_short Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
title_sort network self-organization explains the statistics and dynamics of synaptic connection strengths in cortex
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3536614/
https://www.ncbi.nlm.nih.gov/pubmed/23300431
http://dx.doi.org/10.1371/journal.pcbi.1002848
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