Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.

Increased efforts in the assembly and analysis of connectome data are providing new insights into the principles underlying the connectivity of neural circuits. However, despite these considerable advances in connectomics, neuroanatomical data must be integrated with neurophysiological and behaviora...

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Autores principales: Eduardo J Izquierdo, Randall D Beer
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Publicado: Public Library of Science (PLoS) 2013
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Acceso en línea:https://doaj.org/article/1239f56b336d4dd692c9a7d1c6f4b509
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spelling oai:doaj.org-article:1239f56b336d4dd692c9a7d1c6f4b5092021-11-18T05:52:28ZConnecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.1553-734X1553-735810.1371/journal.pcbi.1002890https://doaj.org/article/1239f56b336d4dd692c9a7d1c6f4b5092013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23408877/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Increased efforts in the assembly and analysis of connectome data are providing new insights into the principles underlying the connectivity of neural circuits. However, despite these considerable advances in connectomics, neuroanatomical data must be integrated with neurophysiological and behavioral data in order to obtain a complete picture of neural function. Due to its nearly complete wiring diagram and large behavioral repertoire, the nematode worm Caenorhaditis elegans is an ideal organism in which to explore in detail this link between neural connectivity and behavior. In this paper, we develop a neuroanatomically-grounded model of salt klinotaxis, a form of chemotaxis in which changes in orientation are directed towards the source through gradual continual adjustments. We identify a minimal klinotaxis circuit by systematically searching the C. elegans connectome for pathways linking chemosensory neurons to neck motor neurons, and prune the resulting network based on both experimental considerations and several simplifying assumptions. We then use an evolutionary algorithm to find possible values for the unknown electrophsyiological parameters in the network such that the behavioral performance of the entire model is optimized to match that of the animal. Multiple runs of the evolutionary algorithm produce an ensemble of such models. We analyze in some detail the mechanisms by which one of the best evolved circuits operates and characterize the similarities and differences between this mechanism and other solutions in the ensemble. Finally, we propose a series of experiments to determine which of these alternatives the worm may be using.Eduardo J IzquierdoRandall D BeerPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 2, p e1002890 (2013)
institution DOAJ
collection DOAJ
language EN
topic Biology (General)
QH301-705.5
spellingShingle Biology (General)
QH301-705.5
Eduardo J Izquierdo
Randall D Beer
Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
description Increased efforts in the assembly and analysis of connectome data are providing new insights into the principles underlying the connectivity of neural circuits. However, despite these considerable advances in connectomics, neuroanatomical data must be integrated with neurophysiological and behavioral data in order to obtain a complete picture of neural function. Due to its nearly complete wiring diagram and large behavioral repertoire, the nematode worm Caenorhaditis elegans is an ideal organism in which to explore in detail this link between neural connectivity and behavior. In this paper, we develop a neuroanatomically-grounded model of salt klinotaxis, a form of chemotaxis in which changes in orientation are directed towards the source through gradual continual adjustments. We identify a minimal klinotaxis circuit by systematically searching the C. elegans connectome for pathways linking chemosensory neurons to neck motor neurons, and prune the resulting network based on both experimental considerations and several simplifying assumptions. We then use an evolutionary algorithm to find possible values for the unknown electrophsyiological parameters in the network such that the behavioral performance of the entire model is optimized to match that of the animal. Multiple runs of the evolutionary algorithm produce an ensemble of such models. We analyze in some detail the mechanisms by which one of the best evolved circuits operates and characterize the similarities and differences between this mechanism and other solutions in the ensemble. Finally, we propose a series of experiments to determine which of these alternatives the worm may be using.
format article
author Eduardo J Izquierdo
Randall D Beer
author_facet Eduardo J Izquierdo
Randall D Beer
author_sort Eduardo J Izquierdo
title Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
title_short Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
title_full Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
title_fullStr Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
title_full_unstemmed Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
title_sort connecting a connectome to behavior: an ensemble of neuroanatomical models of c. elegans klinotaxis.
publisher Public Library of Science (PLoS)
publishDate 2013
url https://doaj.org/article/1239f56b336d4dd692c9a7d1c6f4b509
work_keys_str_mv AT eduardojizquierdo connectingaconnectometobehavioranensembleofneuroanatomicalmodelsofcelegansklinotaxis
AT randalldbeer connectingaconnectometobehavioranensembleofneuroanatomicalmodelsofcelegansklinotaxis
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