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Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages

We report improved automated open-source methodology for head-fixed mesoscale cortical imaging and/or behavioral training of home cage mice using Raspberry Pi-based hardware. Staged partial and probabilistic restraint allows mice to adjust to self-initiated headfixation over 3 weeks’ time with ~50%...

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Autores principales: Murphy, Timothy H, Michelson, Nicholas J, Boyd, Jamie D, Fong, Tony, Bolanos, Luis A, Bierbrauer, David, Siu, Teri, Balbi, Matilde, Bolanos, Federico, Vanni, Matthieu, LeDue, Jeff M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332290/
https://www.ncbi.nlm.nih.gov/pubmed/32412409
http://dx.doi.org/10.7554/eLife.55964
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author Murphy, Timothy H
Michelson, Nicholas J
Boyd, Jamie D
Fong, Tony
Bolanos, Luis A
Bierbrauer, David
Siu, Teri
Balbi, Matilde
Bolanos, Federico
Vanni, Matthieu
LeDue, Jeff M
author_facet Murphy, Timothy H
Michelson, Nicholas J
Boyd, Jamie D
Fong, Tony
Bolanos, Luis A
Bierbrauer, David
Siu, Teri
Balbi, Matilde
Bolanos, Federico
Vanni, Matthieu
LeDue, Jeff M
author_sort Murphy, Timothy H
collection PubMed
description We report improved automated open-source methodology for head-fixed mesoscale cortical imaging and/or behavioral training of home cage mice using Raspberry Pi-based hardware. Staged partial and probabilistic restraint allows mice to adjust to self-initiated headfixation over 3 weeks’ time with ~50% participation rate. We support a cue-based behavioral licking task monitored by a capacitive touch-sensor water spout. While automatically head-fixed, we acquire spontaneous, movement-triggered, or licking task-evoked GCaMP6 cortical signals. An analysis pipeline marked both behavioral events, as well as analyzed brain fluorescence signals as they relate to spontaneous and/or task-evoked behavioral activity. Mice were trained to suppress licking and wait for cues that marked the delivery of water. Correct rewarded go-trials were associated with widespread activation of midline and lateral barrel cortex areas following a vibration cue and delayed frontal and lateral motor cortex activation. Cortical GCaMP signals predicted trial success and correlated strongly with trial-outcome dependent body movements.
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spelling pubmed-73322902020-07-13 Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages Murphy, Timothy H Michelson, Nicholas J Boyd, Jamie D Fong, Tony Bolanos, Luis A Bierbrauer, David Siu, Teri Balbi, Matilde Bolanos, Federico Vanni, Matthieu LeDue, Jeff M eLife Neuroscience We report improved automated open-source methodology for head-fixed mesoscale cortical imaging and/or behavioral training of home cage mice using Raspberry Pi-based hardware. Staged partial and probabilistic restraint allows mice to adjust to self-initiated headfixation over 3 weeks’ time with ~50% participation rate. We support a cue-based behavioral licking task monitored by a capacitive touch-sensor water spout. While automatically head-fixed, we acquire spontaneous, movement-triggered, or licking task-evoked GCaMP6 cortical signals. An analysis pipeline marked both behavioral events, as well as analyzed brain fluorescence signals as they relate to spontaneous and/or task-evoked behavioral activity. Mice were trained to suppress licking and wait for cues that marked the delivery of water. Correct rewarded go-trials were associated with widespread activation of midline and lateral barrel cortex areas following a vibration cue and delayed frontal and lateral motor cortex activation. Cortical GCaMP signals predicted trial success and correlated strongly with trial-outcome dependent body movements. eLife Sciences Publications, Ltd 2020-05-15 /pmc/articles/PMC7332290/ /pubmed/32412409 http://dx.doi.org/10.7554/eLife.55964 Text en © 2020, Murphy et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Neuroscience
Murphy, Timothy H
Michelson, Nicholas J
Boyd, Jamie D
Fong, Tony
Bolanos, Luis A
Bierbrauer, David
Siu, Teri
Balbi, Matilde
Bolanos, Federico
Vanni, Matthieu
LeDue, Jeff M
Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
title Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
title_full Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
title_fullStr Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
title_full_unstemmed Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
title_short Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
title_sort automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332290/
https://www.ncbi.nlm.nih.gov/pubmed/32412409
http://dx.doi.org/10.7554/eLife.55964
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