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Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish

Mapping the detailed connectivity patterns (connectomes) of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line...

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Autores principales: Stobb, Michael, Peterson, Joshua M., Mazzag, Borbala, Gahtan, Ethan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3356276/
https://www.ncbi.nlm.nih.gov/pubmed/22624008
http://dx.doi.org/10.1371/journal.pone.0037292
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author Stobb, Michael
Peterson, Joshua M.
Mazzag, Borbala
Gahtan, Ethan
author_facet Stobb, Michael
Peterson, Joshua M.
Mazzag, Borbala
Gahtan, Ethan
author_sort Stobb, Michael
collection PubMed
description Mapping the detailed connectivity patterns (connectomes) of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line sensorimotor pathway in zebrafish. The model includes 2,616 neurons and 167,114 synaptic connections. Model neurons represent known cell types in zebrafish larvae, and connections were set stochastically following rules based on biological literature. Thus, our model is a uniquely detailed computational representation of a vertebrate connectome. The connectome has low overall connection density, with 2.45% of all possible connections, a value within the physiological range. We used graph theoretical tools to compare the zebrafish connectome graph to small-world, random and structured random graphs of the same size. For each type of graph, 100 randomly generated instantiations were considered. Degree distribution (the number of connections per neuron) varied more in the zebrafish graph than in same size graphs with less biological detail. There was high local clustering and a short average path length between nodes, implying a small-world structure similar to other neural connectomes and complex networks. The graph was found not to be scale-free, in agreement with some other neural connectomes. An experimental lesion was performed that targeted three model brain neurons, including the Mauthner neuron, known to control fast escape turns. The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome.
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spelling pubmed-33562762012-05-23 Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish Stobb, Michael Peterson, Joshua M. Mazzag, Borbala Gahtan, Ethan PLoS One Research Article Mapping the detailed connectivity patterns (connectomes) of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line sensorimotor pathway in zebrafish. The model includes 2,616 neurons and 167,114 synaptic connections. Model neurons represent known cell types in zebrafish larvae, and connections were set stochastically following rules based on biological literature. Thus, our model is a uniquely detailed computational representation of a vertebrate connectome. The connectome has low overall connection density, with 2.45% of all possible connections, a value within the physiological range. We used graph theoretical tools to compare the zebrafish connectome graph to small-world, random and structured random graphs of the same size. For each type of graph, 100 randomly generated instantiations were considered. Degree distribution (the number of connections per neuron) varied more in the zebrafish graph than in same size graphs with less biological detail. There was high local clustering and a short average path length between nodes, implying a small-world structure similar to other neural connectomes and complex networks. The graph was found not to be scale-free, in agreement with some other neural connectomes. An experimental lesion was performed that targeted three model brain neurons, including the Mauthner neuron, known to control fast escape turns. The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome. Public Library of Science 2012-05-18 /pmc/articles/PMC3356276/ /pubmed/22624008 http://dx.doi.org/10.1371/journal.pone.0037292 Text en Stobb 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
Stobb, Michael
Peterson, Joshua M.
Mazzag, Borbala
Gahtan, Ethan
Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish
title Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish
title_full Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish
title_fullStr Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish
title_full_unstemmed Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish
title_short Graph Theoretical Model of a Sensorimotor Connectome in Zebrafish
title_sort graph theoretical model of a sensorimotor connectome in zebrafish
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3356276/
https://www.ncbi.nlm.nih.gov/pubmed/22624008
http://dx.doi.org/10.1371/journal.pone.0037292
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