High-throughput automated home-cage mesoscopic functional imaging of mouse cortex

Mouse head-fixed behaviour coupled with functional imaging has become a powerful technique in rodent systems neuroscience. However, training mice can be time consuming and is potentially stressful for animals. Here we report a fully automated, open source, self-initiated head-fixation system for mes...

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Published in:Nature communications Vol. 7; no. 1; p. 11611
Main Authors: Murphy, Timothy H., Boyd, Jamie D., Bolaños, Federico, Vanni, Matthieu P., Silasi, Gergely, Haupt, Dirk, LeDue, Jeff M.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 13-06-2016
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Summary:Mouse head-fixed behaviour coupled with functional imaging has become a powerful technique in rodent systems neuroscience. However, training mice can be time consuming and is potentially stressful for animals. Here we report a fully automated, open source, self-initiated head-fixation system for mesoscopic functional imaging in mice. The system supports five mice at a time and requires minimal investigator intervention. Using genetically encoded calcium indicator transgenic mice, we longitudinally monitor cortical functional connectivity up to 24 h per day in >7,000 self-initiated and unsupervised imaging sessions up to 90 days. The procedure provides robust assessment of functional cortical maps on the basis of both spontaneous activity and brief sensory stimuli such as light flashes. The approach is scalable to a number of remotely controlled cages that can be assessed within the controlled conditions of dedicated animal facilities. We anticipate that home-cage brain imaging will permit flexible and chronic assessment of mesoscale cortical function. Functional imaging in awake head-fixed mice is a widely used technique to study neural responses. Here the authors report on an open source, fully automated unsupervised system for training mice to self initiate head fixation to enable stable mesoscopic functional imaging of cortical functional connectivity.
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These authors contributed equally to this work.
ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms11611