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

Abstract

<jats:p>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.</jats:p>

PsychRNN: An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks

“…For instance, it is poorly understood whether differences in training trajectories result in different cognitive strategies or neural representations in a task (e.g., Latimer and Freedman, 2019). Standardization and automation in animal training may aid experimental investigation of task shaping effects (Murphy et al, 2020;Berger et al, 2018). PsychRNN provides an accessible framework to explore neuroscientific questions related to task shaping in RNN models.…”

PsychRNN: An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks

“…For instance, it is poorly understood whether differences in training trajectories result in different cognitive strategies or neural representations in a task (e.g., Latimer and Freedman, 2019). Standardization and automation in animal training may aid experimental investigation of task shaping effects (Murphy et al, 2020;Berger et al, 2018). Although…”

TailTimer:an open-source device for automating the rodent tail immersion assay

“…A large part of the appeal of these computers is the vast array of external devices (i.e., sensors or motors) that can be connected and controlled through the GPIO ports. Devices for operant conditioning (Longley et al, 2017;Mazziotti et al, 2020), conditioned place preference (Vassilev et al, 2020), head-fixed mesoscale cortical imaging (Murphy et al, 2020), and even virtual reality (Tadres & Louis, 2020) have been reported. Further, a wide range of environmental factors (e.g., humidity, barometric pressure, and light) can be monitored using Raspberry Pi (Longley et al, 2017).…”