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A hardware system for real-time decoding of in vivo calcium imaging data

Epifluorescence miniature microscopes (‘miniscopes’) are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loo...

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Autores principales: Chen, Zhe, Blair, Garrett J, Guo, Changliang, Zhou, Jim, Romero-Sosa, Juan-Luis, Izquierdo, Alicia, Golshani, Peyman, Cong, Jason, Aharoni, Daniel, Blair, Hugh T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9908073/
https://www.ncbi.nlm.nih.gov/pubmed/36692269
http://dx.doi.org/10.7554/eLife.78344
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author Chen, Zhe
Blair, Garrett J
Guo, Changliang
Zhou, Jim
Romero-Sosa, Juan-Luis
Izquierdo, Alicia
Golshani, Peyman
Cong, Jason
Aharoni, Daniel
Blair, Hugh T
author_facet Chen, Zhe
Blair, Garrett J
Guo, Changliang
Zhou, Jim
Romero-Sosa, Juan-Luis
Izquierdo, Alicia
Golshani, Peyman
Cong, Jason
Aharoni, Daniel
Blair, Hugh T
author_sort Chen, Zhe
collection PubMed
description Epifluorescence miniature microscopes (‘miniscopes’) are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.
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spelling pubmed-99080732023-02-09 A hardware system for real-time decoding of in vivo calcium imaging data Chen, Zhe Blair, Garrett J Guo, Changliang Zhou, Jim Romero-Sosa, Juan-Luis Izquierdo, Alicia Golshani, Peyman Cong, Jason Aharoni, Daniel Blair, Hugh T eLife Computational and Systems Biology Epifluorescence miniature microscopes (‘miniscopes’) are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals. eLife Sciences Publications, Ltd 2023-01-24 /pmc/articles/PMC9908073/ /pubmed/36692269 http://dx.doi.org/10.7554/eLife.78344 Text en © 2023, Chen et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Chen, Zhe
Blair, Garrett J
Guo, Changliang
Zhou, Jim
Romero-Sosa, Juan-Luis
Izquierdo, Alicia
Golshani, Peyman
Cong, Jason
Aharoni, Daniel
Blair, Hugh T
A hardware system for real-time decoding of in vivo calcium imaging data
title A hardware system for real-time decoding of in vivo calcium imaging data
title_full A hardware system for real-time decoding of in vivo calcium imaging data
title_fullStr A hardware system for real-time decoding of in vivo calcium imaging data
title_full_unstemmed A hardware system for real-time decoding of in vivo calcium imaging data
title_short A hardware system for real-time decoding of in vivo calcium imaging data
title_sort hardware system for real-time decoding of in vivo calcium imaging data
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9908073/
https://www.ncbi.nlm.nih.gov/pubmed/36692269
http://dx.doi.org/10.7554/eLife.78344
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