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Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae
Prepulse inhibition (PPI) is a behavioural phenomenon in which a preceding weaker stimulus suppresses the startle response to a subsequent stimulus. The effect of PPI has been found to be reduced in psychiatric patients and is a promising neurophysiological indicator of psychiatric disorders. Becaus...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458643/ https://www.ncbi.nlm.nih.gov/pubmed/36075992 http://dx.doi.org/10.1038/s41598-022-19210-8 |
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author | Furuya, Kotaro Katsumata, Yuki Ishibashi, Masayuki Matsumoto, Yutaro Morimoto, Takako Aonishi, Toru |
author_facet | Furuya, Kotaro Katsumata, Yuki Ishibashi, Masayuki Matsumoto, Yutaro Morimoto, Takako Aonishi, Toru |
author_sort | Furuya, Kotaro |
collection | PubMed |
description | Prepulse inhibition (PPI) is a behavioural phenomenon in which a preceding weaker stimulus suppresses the startle response to a subsequent stimulus. The effect of PPI has been found to be reduced in psychiatric patients and is a promising neurophysiological indicator of psychiatric disorders. Because the neural circuit of the startle response has been identified at the cellular level, investigating the mechanism underlying PPI in Drosophila melanogaster larvae through experiment-based mathematical modelling can provide valuable insights. We recently identified PPI in Drosophila larvae and found that PPI was reduced in larvae mutated with the Centaurin gamma 1A (CenG1A) gene, which may be associated with autism. In this study, we used numerical simulations to investigate the neural mechanisms underlying PPI in Drosophila larvae. We adjusted the parameters of a previously developed Drosophila larvae computational model and demonstrated that the model could reproduce several behaviours, including PPI. An analysis of the temporal changes in neuronal activity when PPI occurs using our neural circuit model suggested that the activity of specific neurons triggered by prepulses has a considerable effect on PPI. Furthermore, we validated our speculations on PPI reduction in CenG1A mutants with simulations. |
format | Online Article Text |
id | pubmed-9458643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94586432022-09-10 Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae Furuya, Kotaro Katsumata, Yuki Ishibashi, Masayuki Matsumoto, Yutaro Morimoto, Takako Aonishi, Toru Sci Rep Article Prepulse inhibition (PPI) is a behavioural phenomenon in which a preceding weaker stimulus suppresses the startle response to a subsequent stimulus. The effect of PPI has been found to be reduced in psychiatric patients and is a promising neurophysiological indicator of psychiatric disorders. Because the neural circuit of the startle response has been identified at the cellular level, investigating the mechanism underlying PPI in Drosophila melanogaster larvae through experiment-based mathematical modelling can provide valuable insights. We recently identified PPI in Drosophila larvae and found that PPI was reduced in larvae mutated with the Centaurin gamma 1A (CenG1A) gene, which may be associated with autism. In this study, we used numerical simulations to investigate the neural mechanisms underlying PPI in Drosophila larvae. We adjusted the parameters of a previously developed Drosophila larvae computational model and demonstrated that the model could reproduce several behaviours, including PPI. An analysis of the temporal changes in neuronal activity when PPI occurs using our neural circuit model suggested that the activity of specific neurons triggered by prepulses has a considerable effect on PPI. Furthermore, we validated our speculations on PPI reduction in CenG1A mutants with simulations. Nature Publishing Group UK 2022-09-08 /pmc/articles/PMC9458643/ /pubmed/36075992 http://dx.doi.org/10.1038/s41598-022-19210-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Furuya, Kotaro Katsumata, Yuki Ishibashi, Masayuki Matsumoto, Yutaro Morimoto, Takako Aonishi, Toru Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae |
title | Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae |
title_full | Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae |
title_fullStr | Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae |
title_full_unstemmed | Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae |
title_short | Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae |
title_sort | computational model predicts the neural mechanisms of prepulse inhibition in drosophila larvae |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458643/ https://www.ncbi.nlm.nih.gov/pubmed/36075992 http://dx.doi.org/10.1038/s41598-022-19210-8 |
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