|Title||Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages.|
|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Murphy, Timothy H., Nicholas J. Michelson, Jamie D. Boyd, Tony Fong, Luis A. Bolanos, David Bierbrauer, Teri Siu, Matilde Balbi, Federico Bolaños, Matthieu Vanni, and Jeff M. LeDue|
|Date Published||2020 05 15|
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.
|PubMed Central ID||PMC7332290|
|Grant List||FDN-143209 / / CIHR / Canada|