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Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome
Understanding how the structural connectivity and spatial geometry of a network constrains the dynamics it is able to support is an active and open area of research. We simulated the plausible dynamics resulting from the known C. elegans connectome using a recent model and theoretical analysis that...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985353/ https://www.ncbi.nlm.nih.gov/pubmed/33767613 http://dx.doi.org/10.3389/fnsys.2021.564124 |
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author | George, Vivek Kurien Puppo, Francesca Silva, Gabriel A. |
author_facet | George, Vivek Kurien Puppo, Francesca Silva, Gabriel A. |
author_sort | George, Vivek Kurien |
collection | PubMed |
description | Understanding how the structural connectivity and spatial geometry of a network constrains the dynamics it is able to support is an active and open area of research. We simulated the plausible dynamics resulting from the known C. elegans connectome using a recent model and theoretical analysis that computes the dynamics of neurobiological networks by focusing on how local interactions among connected neurons give rise to the global dynamics in an emergent way. We studied the dynamics which resulted from stimulating a chemosensory neuron (ASEL) in a known feeding circuit, both in isolation and embedded in the full connectome. We show that contralateral motorneuron activations in ventral (VB) and dorsal (DB) classes of motorneurons emerged from the simulations, which are qualitatively similar to rhythmic motorneuron firing pattern associated with locomotion of the worm. One interpretation of these results is that there is an inherent—and we propose—purposeful structural wiring to the C. elegans connectome that has evolved to serve specific behavioral functions. To study network signaling pathways responsible for the dynamics we developed an analytic framework that constructs Temporal Sequences (TSeq), time-ordered walks of signals on graphs. We found that only 5% of TSeq are preserved between the isolated feeding network relative to its embedded counterpart. The remaining 95% of signaling pathways computed in the isolated network are not present in the embedded network. This suggests a cautionary note for computational studies of isolated neurobiological circuits and networks. |
format | Online Article Text |
id | pubmed-7985353 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79853532021-03-24 Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome George, Vivek Kurien Puppo, Francesca Silva, Gabriel A. Front Syst Neurosci Neuroscience Understanding how the structural connectivity and spatial geometry of a network constrains the dynamics it is able to support is an active and open area of research. We simulated the plausible dynamics resulting from the known C. elegans connectome using a recent model and theoretical analysis that computes the dynamics of neurobiological networks by focusing on how local interactions among connected neurons give rise to the global dynamics in an emergent way. We studied the dynamics which resulted from stimulating a chemosensory neuron (ASEL) in a known feeding circuit, both in isolation and embedded in the full connectome. We show that contralateral motorneuron activations in ventral (VB) and dorsal (DB) classes of motorneurons emerged from the simulations, which are qualitatively similar to rhythmic motorneuron firing pattern associated with locomotion of the worm. One interpretation of these results is that there is an inherent—and we propose—purposeful structural wiring to the C. elegans connectome that has evolved to serve specific behavioral functions. To study network signaling pathways responsible for the dynamics we developed an analytic framework that constructs Temporal Sequences (TSeq), time-ordered walks of signals on graphs. We found that only 5% of TSeq are preserved between the isolated feeding network relative to its embedded counterpart. The remaining 95% of signaling pathways computed in the isolated network are not present in the embedded network. This suggests a cautionary note for computational studies of isolated neurobiological circuits and networks. Frontiers Media S.A. 2021-03-09 /pmc/articles/PMC7985353/ /pubmed/33767613 http://dx.doi.org/10.3389/fnsys.2021.564124 Text en Copyright © 2021 George, Puppo and Silva. 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) and the copyright owner(s) 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 George, Vivek Kurien Puppo, Francesca Silva, Gabriel A. Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome |
title | Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome |
title_full | Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome |
title_fullStr | Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome |
title_full_unstemmed | Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome |
title_short | Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome |
title_sort | computing temporal sequences associated with dynamic patterns on the c. elegans connectome |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985353/ https://www.ncbi.nlm.nih.gov/pubmed/33767613 http://dx.doi.org/10.3389/fnsys.2021.564124 |
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