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Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture

Bioengineered 3D tunable neuronal constructs are a versatile platform for studying neuronal network functions, offering numerous advantages over existing technologies and providing for the discovery of new biological insights. Functional neural networks can be evaluated using calcium imaging and qua...

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Detalles Bibliográficos
Autores principales: Dingle, Yu-Ting L., Bonzanni, Mattia, Liaudanskaya, Volha, Nieland, Thomas J.F., Kaplan, David L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7841403/
https://www.ncbi.nlm.nih.gov/pubmed/33537680
http://dx.doi.org/10.1016/j.xpro.2020.100292
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author Dingle, Yu-Ting L.
Bonzanni, Mattia
Liaudanskaya, Volha
Nieland, Thomas J.F.
Kaplan, David L.
author_facet Dingle, Yu-Ting L.
Bonzanni, Mattia
Liaudanskaya, Volha
Nieland, Thomas J.F.
Kaplan, David L.
author_sort Dingle, Yu-Ting L.
collection PubMed
description Bioengineered 3D tunable neuronal constructs are a versatile platform for studying neuronal network functions, offering numerous advantages over existing technologies and providing for the discovery of new biological insights. Functional neural networks can be evaluated using calcium imaging and quantitatively described using network science. This protocol includes instructions for fabricating protein-based composite scaffolds, 3D in vitro culture of embryonic mouse cortical neurons, virally induced expression of GCaMP6f, wide-field calcium imaging, and computational analysis with open-source software and custom MATLAB code. For complete details on the use and execution of this protocol, please refer to Dingle et al. (2020).
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spelling pubmed-78414032021-02-02 Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture Dingle, Yu-Ting L. Bonzanni, Mattia Liaudanskaya, Volha Nieland, Thomas J.F. Kaplan, David L. STAR Protoc Protocol Bioengineered 3D tunable neuronal constructs are a versatile platform for studying neuronal network functions, offering numerous advantages over existing technologies and providing for the discovery of new biological insights. Functional neural networks can be evaluated using calcium imaging and quantitatively described using network science. This protocol includes instructions for fabricating protein-based composite scaffolds, 3D in vitro culture of embryonic mouse cortical neurons, virally induced expression of GCaMP6f, wide-field calcium imaging, and computational analysis with open-source software and custom MATLAB code. For complete details on the use and execution of this protocol, please refer to Dingle et al. (2020). Elsevier 2021-01-25 /pmc/articles/PMC7841403/ /pubmed/33537680 http://dx.doi.org/10.1016/j.xpro.2020.100292 Text en © 2021 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Protocol
Dingle, Yu-Ting L.
Bonzanni, Mattia
Liaudanskaya, Volha
Nieland, Thomas J.F.
Kaplan, David L.
Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture
title Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture
title_full Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture
title_fullStr Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture
title_full_unstemmed Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture
title_short Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture
title_sort integrated functional neuronal network analysis of 3d silk-collagen scaffold-based mouse cortical culture
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7841403/
https://www.ncbi.nlm.nih.gov/pubmed/33537680
http://dx.doi.org/10.1016/j.xpro.2020.100292
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