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Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging
An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous cu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046699/ https://www.ncbi.nlm.nih.gov/pubmed/33826050 http://dx.doi.org/10.1007/s10827-020-00774-1 |
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author | Chicchi, Lorenzo Cecchini, Gloria Adam, Ihusan de Vito, Giuseppe Livi, Roberto Pavone, Francesco Saverio Silvestri, Ludovico Turrini, Lapo Vanzi, Francesco Fanelli, Duccio |
author_facet | Chicchi, Lorenzo Cecchini, Gloria Adam, Ihusan de Vito, Giuseppe Livi, Roberto Pavone, Francesco Saverio Silvestri, Ludovico Turrini, Lapo Vanzi, Francesco Fanelli, Duccio |
author_sort | Chicchi, Lorenzo |
collection | PubMed |
description | An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas. |
format | Online Article Text |
id | pubmed-8046699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-80466992021-04-27 Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging Chicchi, Lorenzo Cecchini, Gloria Adam, Ihusan de Vito, Giuseppe Livi, Roberto Pavone, Francesco Saverio Silvestri, Ludovico Turrini, Lapo Vanzi, Francesco Fanelli, Duccio J Comput Neurosci Article An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas. Springer US 2021-04-07 2021 /pmc/articles/PMC8046699/ /pubmed/33826050 http://dx.doi.org/10.1007/s10827-020-00774-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Chicchi, Lorenzo Cecchini, Gloria Adam, Ihusan de Vito, Giuseppe Livi, Roberto Pavone, Francesco Saverio Silvestri, Ludovico Turrini, Lapo Vanzi, Francesco Fanelli, Duccio Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
title | Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
title_full | Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
title_fullStr | Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
title_full_unstemmed | Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
title_short | Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
title_sort | reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046699/ https://www.ncbi.nlm.nih.gov/pubmed/33826050 http://dx.doi.org/10.1007/s10827-020-00774-1 |
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