Light sheet fluorescence microscopy for 3D imaging of Ca2+ dynamics in neuronal cultures

Pablo Loza-Alvarez; Gustavo Castro-Olvera; Jorge A. Madrid-Wolff; Omar E. Olarte; Emilio J. Gualda; Jordi Soriano; Estefanía Estévez-Priego; Adriaan A. Ludl

doi:10.1117/12.2593900

1 August 2021 Light sheet fluorescence microscopy for 3D imaging of Ca²⁺ dynamics in neuronal cultures

Pablo Loza-Alvarez, Gustavo Castro-Olvera, Jorge A. Madrid-Wolff, Omar E. Olarte, Emilio J. Gualda, Jordi Soriano, Estefanía Estévez-Priego, Adriaan A. Ludl

Author Affiliations +

Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 118040L (2021) https://doi.org/10.1117/12.2593900
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Abstract

LSFM is a technique that allows obtaining fast 2D images of biological samples. Its characteristic 90° geometry results in a highly efficient excitation and light collection of the generated signal, minimizing light dose onto the sample and reducing phototoxicity effects. Furthermore, by displacing the sample through the light sheet, high-resolution 3D images can also be obtained. Therefore, LSFM has been put forward as an interesting candidate for fast volumetric brain imaging. Here, I will present our results for 3D imaging of the spontaneous and dynamic calcium activity in primary neuron cultures in hydrogels. The obtained data is then processed to calculate the connectivity maps in the 3D neuron cultures in hydrogels and assess the topological properties of these maps such as the modules or highly connected subnetworks. This abstract is part of the symposium: "Diagnosis and Prediction of Neurodegenerative Diseases using Artificial Intelligence"

Conference Presentation

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Pablo Loza-Alvarez, Gustavo Castro-Olvera, Jorge A. Madrid-Wolff, Omar E. Olarte, Emilio J. Gualda, Jordi Soriano, Estefanía Estévez-Priego, and Adriaan A. Ludl "Light sheet fluorescence microscopy for 3D imaging of Ca²⁺ dynamics in neuronal cultures", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 118040L (1 August 2021); https://doi.org/10.1117/12.2593900

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