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Input clustering and the microscale structure of local circuits

The recent development of powerful tools for high-throughput mapping of synaptic networks promises major advances in understanding brain function. One open question is how circuits integrate and store information. Competing models based on random vs. structured connectivity make distinct predictions...

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Autores principales: DeBello, William M., McBride, Thomas J., Nichols, Grant S., Pannoni, Katy E., Sanculi, Daniel, Totten, Douglas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4162353/
https://www.ncbi.nlm.nih.gov/pubmed/25309336
http://dx.doi.org/10.3389/fncir.2014.00112
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author DeBello, William M.
McBride, Thomas J.
Nichols, Grant S.
Pannoni, Katy E.
Sanculi, Daniel
Totten, Douglas J.
author_facet DeBello, William M.
McBride, Thomas J.
Nichols, Grant S.
Pannoni, Katy E.
Sanculi, Daniel
Totten, Douglas J.
author_sort DeBello, William M.
collection PubMed
description The recent development of powerful tools for high-throughput mapping of synaptic networks promises major advances in understanding brain function. One open question is how circuits integrate and store information. Competing models based on random vs. structured connectivity make distinct predictions regarding the dendritic addressing of synaptic inputs. In this article we review recent experimental tests of one of these models, the input clustering hypothesis. Across circuits, brain regions and species, there is growing evidence of a link between synaptic co-activation and dendritic location, although this finding is not universal. The functional implications of input clustering and future challenges are discussed.
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spelling pubmed-41623532014-10-10 Input clustering and the microscale structure of local circuits DeBello, William M. McBride, Thomas J. Nichols, Grant S. Pannoni, Katy E. Sanculi, Daniel Totten, Douglas J. Front Neural Circuits Neuroscience The recent development of powerful tools for high-throughput mapping of synaptic networks promises major advances in understanding brain function. One open question is how circuits integrate and store information. Competing models based on random vs. structured connectivity make distinct predictions regarding the dendritic addressing of synaptic inputs. In this article we review recent experimental tests of one of these models, the input clustering hypothesis. Across circuits, brain regions and species, there is growing evidence of a link between synaptic co-activation and dendritic location, although this finding is not universal. The functional implications of input clustering and future challenges are discussed. Frontiers Media S.A. 2014-09-12 /pmc/articles/PMC4162353/ /pubmed/25309336 http://dx.doi.org/10.3389/fncir.2014.00112 Text en Copyright © 2014 DeBello, McBride, Nichols, Pannoni, Sanculi and Totten. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
DeBello, William M.
McBride, Thomas J.
Nichols, Grant S.
Pannoni, Katy E.
Sanculi, Daniel
Totten, Douglas J.
Input clustering and the microscale structure of local circuits
title Input clustering and the microscale structure of local circuits
title_full Input clustering and the microscale structure of local circuits
title_fullStr Input clustering and the microscale structure of local circuits
title_full_unstemmed Input clustering and the microscale structure of local circuits
title_short Input clustering and the microscale structure of local circuits
title_sort input clustering and the microscale structure of local circuits
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4162353/
https://www.ncbi.nlm.nih.gov/pubmed/25309336
http://dx.doi.org/10.3389/fncir.2014.00112
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