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Specificity and robustness of long-distance connections in weighted, interareal connectomes

Brain areas’ functional repertoires are shaped by their incoming and outgoing structural connections. In empirically measured networks, most connections are short, reflecting spatial and energetic constraints. Nonetheless, a small number of connections span long distances, consistent with the notion...

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Detalles Bibliográficos
Autores principales: Betzel, Richard F., Bassett, Danielle S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003515/
https://www.ncbi.nlm.nih.gov/pubmed/29739890
http://dx.doi.org/10.1073/pnas.1720186115
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author Betzel, Richard F.
Bassett, Danielle S.
author_facet Betzel, Richard F.
Bassett, Danielle S.
author_sort Betzel, Richard F.
collection PubMed
description Brain areas’ functional repertoires are shaped by their incoming and outgoing structural connections. In empirically measured networks, most connections are short, reflecting spatial and energetic constraints. Nonetheless, a small number of connections span long distances, consistent with the notion that the functionality of these connections must outweigh their cost. While the precise function of long-distance connections is unknown, the leading hypothesis is that they act to reduce the topological distance between brain areas and increase the efficiency of interareal communication. However, this hypothesis implies a nonspecificity of long-distance connections that we contend is unlikely. Instead, we propose that long-distance connections serve to diversify brain areas’ inputs and outputs, thereby promoting complex dynamics. Through analysis of five weighted interareal network datasets, we show that long-distance connections play only minor roles in reducing average interareal topological distance. In contrast, areas’ long-distance and short-range neighbors exhibit marked differences in their connectivity profiles, suggesting that long-distance connections enhance dissimilarity between areal inputs and outputs. Next, we show that—in isolation—areas’ long-distance connectivity profiles exhibit nonrandom levels of similarity, suggesting that the communication pathways formed by long connections exhibit redundancies that may serve to promote robustness. Finally, we use a linearization of Wilson–Cowan dynamics to simulate the covariance structure of neural activity and show that in the absence of long-distance connections a common measure of functional diversity decreases. Collectively, our findings suggest that long-distance connections are necessary for supporting diverse and complex brain dynamics.
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spelling pubmed-60035152018-06-18 Specificity and robustness of long-distance connections in weighted, interareal connectomes Betzel, Richard F. Bassett, Danielle S. Proc Natl Acad Sci U S A PNAS Plus Brain areas’ functional repertoires are shaped by their incoming and outgoing structural connections. In empirically measured networks, most connections are short, reflecting spatial and energetic constraints. Nonetheless, a small number of connections span long distances, consistent with the notion that the functionality of these connections must outweigh their cost. While the precise function of long-distance connections is unknown, the leading hypothesis is that they act to reduce the topological distance between brain areas and increase the efficiency of interareal communication. However, this hypothesis implies a nonspecificity of long-distance connections that we contend is unlikely. Instead, we propose that long-distance connections serve to diversify brain areas’ inputs and outputs, thereby promoting complex dynamics. Through analysis of five weighted interareal network datasets, we show that long-distance connections play only minor roles in reducing average interareal topological distance. In contrast, areas’ long-distance and short-range neighbors exhibit marked differences in their connectivity profiles, suggesting that long-distance connections enhance dissimilarity between areal inputs and outputs. Next, we show that—in isolation—areas’ long-distance connectivity profiles exhibit nonrandom levels of similarity, suggesting that the communication pathways formed by long connections exhibit redundancies that may serve to promote robustness. Finally, we use a linearization of Wilson–Cowan dynamics to simulate the covariance structure of neural activity and show that in the absence of long-distance connections a common measure of functional diversity decreases. Collectively, our findings suggest that long-distance connections are necessary for supporting diverse and complex brain dynamics. National Academy of Sciences 2018-05-22 2018-05-08 /pmc/articles/PMC6003515/ /pubmed/29739890 http://dx.doi.org/10.1073/pnas.1720186115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle PNAS Plus
Betzel, Richard F.
Bassett, Danielle S.
Specificity and robustness of long-distance connections in weighted, interareal connectomes
title Specificity and robustness of long-distance connections in weighted, interareal connectomes
title_full Specificity and robustness of long-distance connections in weighted, interareal connectomes
title_fullStr Specificity and robustness of long-distance connections in weighted, interareal connectomes
title_full_unstemmed Specificity and robustness of long-distance connections in weighted, interareal connectomes
title_short Specificity and robustness of long-distance connections in weighted, interareal connectomes
title_sort specificity and robustness of long-distance connections in weighted, interareal connectomes
topic PNAS Plus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003515/
https://www.ncbi.nlm.nih.gov/pubmed/29739890
http://dx.doi.org/10.1073/pnas.1720186115
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