Review of data processing of functional optical microscopy for neuroscience

Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accu...

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Autores principales: Benisty, Hadas, Song, Alexander, Mishne, Gal, Charles, Adam S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2022
Materias:
Special Section on Computational Approaches for Neuroimaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351186/
https://www.ncbi.nlm.nih.gov/pubmed/35937186
http://dx.doi.org/10.1117/1.NPh.9.4.041402
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author Benisty, Hadas
Song, Alexander
Mishne, Gal
Charles, Adam S.
author_facet Benisty, Hadas
Song, Alexander
Mishne, Gal
Charles, Adam S.
author_sort Benisty, Hadas
collection PubMed
description Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.
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spelling pubmed-93511862022-08-05 Review of data processing of functional optical microscopy for neuroscience Benisty, Hadas Song, Alexander Mishne, Gal Charles, Adam S. Neurophotonics Special Section on Computational Approaches for Neuroimaging Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges. Society of Photo-Optical Instrumentation Engineers 2022-08-04 2022-10 /pmc/articles/PMC9351186/ /pubmed/35937186 http://dx.doi.org/10.1117/1.NPh.9.4.041402 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
spellingShingle Special Section on Computational Approaches for Neuroimaging
Benisty, Hadas
Song, Alexander
Mishne, Gal
Charles, Adam S.
Review of data processing of functional optical microscopy for neuroscience
title Review of data processing of functional optical microscopy for neuroscience
title_full Review of data processing of functional optical microscopy for neuroscience
title_fullStr Review of data processing of functional optical microscopy for neuroscience
title_full_unstemmed Review of data processing of functional optical microscopy for neuroscience
title_short Review of data processing of functional optical microscopy for neuroscience
title_sort review of data processing of functional optical microscopy for neuroscience
topic Special Section on Computational Approaches for Neuroimaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351186/
https://www.ncbi.nlm.nih.gov/pubmed/35937186
http://dx.doi.org/10.1117/1.NPh.9.4.041402
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