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Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling
Drosophila larvae crawl by peristaltic waves of muscle contractions, which propagate along the animal body and involve the simultaneous contraction of the left and right side of each segment. Coordinated propagation of contraction does not require sensory input, suggesting that movement is generated...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3616270/ https://www.ncbi.nlm.nih.gov/pubmed/23576980 http://dx.doi.org/10.3389/fncom.2013.00024 |
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author | Gjorgjieva, Julijana Berni, Jimena Evers, Jan Felix Eglen, Stephen J. |
author_facet | Gjorgjieva, Julijana Berni, Jimena Evers, Jan Felix Eglen, Stephen J. |
author_sort | Gjorgjieva, Julijana |
collection | PubMed |
description | Drosophila larvae crawl by peristaltic waves of muscle contractions, which propagate along the animal body and involve the simultaneous contraction of the left and right side of each segment. Coordinated propagation of contraction does not require sensory input, suggesting that movement is generated by a central pattern generator (CPG). We characterized crawling behavior of newly hatched Drosophila larvae by quantifying timing and duration of segmental boundary contractions. We developed a CPG network model that recapitulates these patterns based on segmentally repeated units of excitatory and inhibitory (EI) neuronal populations coupled with immediate neighboring segments. A single network with symmetric coupling between neighboring segments succeeded in generating both forward and backward propagation of activity. The CPG network was robust to changes in amplitude and variability of connectivity strength. Introducing sensory feedback via “stretch-sensitive” neurons improved wave propagation properties such as speed of propagation and segmental contraction duration as observed experimentally. Sensory feedback also restored propagating activity patterns when an inappropriately tuned CPG network failed to generate waves. Finally, in a two-sided CPG model we demonstrated that two types of connectivity could synchronize the activity of two independent networks: connections from excitatory neurons on one side to excitatory contralateral neurons (E to E), and connections from inhibitory neurons on one side to excitatory contralateral neurons (I to E). To our knowledge, such I to E connectivity has not yet been found in any experimental system; however, it provides the most robust mechanism to synchronize activity between contralateral CPGs in our model. Our model provides a general framework for studying the conditions under which a single locally coupled network generates bilaterally synchronized and longitudinally propagating waves in either direction. |
format | Online Article Text |
id | pubmed-3616270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-36162702013-04-10 Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling Gjorgjieva, Julijana Berni, Jimena Evers, Jan Felix Eglen, Stephen J. Front Comput Neurosci Neuroscience Drosophila larvae crawl by peristaltic waves of muscle contractions, which propagate along the animal body and involve the simultaneous contraction of the left and right side of each segment. Coordinated propagation of contraction does not require sensory input, suggesting that movement is generated by a central pattern generator (CPG). We characterized crawling behavior of newly hatched Drosophila larvae by quantifying timing and duration of segmental boundary contractions. We developed a CPG network model that recapitulates these patterns based on segmentally repeated units of excitatory and inhibitory (EI) neuronal populations coupled with immediate neighboring segments. A single network with symmetric coupling between neighboring segments succeeded in generating both forward and backward propagation of activity. The CPG network was robust to changes in amplitude and variability of connectivity strength. Introducing sensory feedback via “stretch-sensitive” neurons improved wave propagation properties such as speed of propagation and segmental contraction duration as observed experimentally. Sensory feedback also restored propagating activity patterns when an inappropriately tuned CPG network failed to generate waves. Finally, in a two-sided CPG model we demonstrated that two types of connectivity could synchronize the activity of two independent networks: connections from excitatory neurons on one side to excitatory contralateral neurons (E to E), and connections from inhibitory neurons on one side to excitatory contralateral neurons (I to E). To our knowledge, such I to E connectivity has not yet been found in any experimental system; however, it provides the most robust mechanism to synchronize activity between contralateral CPGs in our model. Our model provides a general framework for studying the conditions under which a single locally coupled network generates bilaterally synchronized and longitudinally propagating waves in either direction. Frontiers Media S.A. 2013-04-04 /pmc/articles/PMC3616270/ /pubmed/23576980 http://dx.doi.org/10.3389/fncom.2013.00024 Text en Copyright © 2013 Gjorgjieva, Berni, Evers and Eglen. 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 use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc. |
spellingShingle | Neuroscience Gjorgjieva, Julijana Berni, Jimena Evers, Jan Felix Eglen, Stephen J. Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling |
title | Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling |
title_full | Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling |
title_fullStr | Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling |
title_full_unstemmed | Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling |
title_short | Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling |
title_sort | neural circuits for peristaltic wave propagation in crawling drosophila larvae: analysis and modeling |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3616270/ https://www.ncbi.nlm.nih.gov/pubmed/23576980 http://dx.doi.org/10.3389/fncom.2013.00024 |
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