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Nonrandom network connectivity comes in pairs

Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, P(ij)...

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Detalles Bibliográficos
Autores principales: Hoffmann, Felix Z., Triesch, Jochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869014/
https://www.ncbi.nlm.nih.gov/pubmed/29601066
http://dx.doi.org/10.1162/NETN_a_00004
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author Hoffmann, Felix Z.
Triesch, Jochen
author_facet Hoffmann, Felix Z.
Triesch, Jochen
author_sort Hoffmann, Felix Z.
collection PubMed
description Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, P(ij) = P(ji), the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric.
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spelling pubmed-58690142018-03-27 Nonrandom network connectivity comes in pairs Hoffmann, Felix Z. Triesch, Jochen Netw Neurosci Research Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, P(ij) = P(ji), the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric. MIT Press 2017-02-01 /pmc/articles/PMC5869014/ /pubmed/29601066 http://dx.doi.org/10.1162/NETN_a_00004 Text en © 2017 Massachusetts Institute of Technology http://creativecommons.org/licenses/by/3.0/ 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 work is properly cited.
spellingShingle Research
Hoffmann, Felix Z.
Triesch, Jochen
Nonrandom network connectivity comes in pairs
title Nonrandom network connectivity comes in pairs
title_full Nonrandom network connectivity comes in pairs
title_fullStr Nonrandom network connectivity comes in pairs
title_full_unstemmed Nonrandom network connectivity comes in pairs
title_short Nonrandom network connectivity comes in pairs
title_sort nonrandom network connectivity comes in pairs
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869014/
https://www.ncbi.nlm.nih.gov/pubmed/29601066
http://dx.doi.org/10.1162/NETN_a_00004
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