Damien J Ellens1, Matt Gaidica2, Andrew Toader1, Sophia Peng1, Shirley Shue1, Titus John3, Alexandra Bova2, Daniel K Leventhal4. 1. Department of Neurology, University of Michigan, Ann Arbor, MI 48109, United States. 2. Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States. 3. Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States. 4. Neurology Service, VA Ann Arbor Health System, Ann Arbor, MI 48109, United States; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, United States; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States. Electronic address: dleventh@med.umich.edu.
Abstract
BACKGROUND: Single pellet reaching is an established task for studying fine motor control in which rats reach for, grasp, and eat food pellets in a stereotyped sequence. Most incarnations of this task require constant attention, limiting the number of animals that can be tested and the number of trials per session. Automated versions allow more interventions in more animals, but must be robust and reproducible. NEW METHOD: Our system automatically delivers single reward pellets for rats to grasp with their forepaw. Reaches are detected using real-time computer vision, which triggers video acquisition from multiple angles using mirrors. This allows us to record high-speed (>300 frames per second) video, and trigger interventions (e.g., optogenetics) with high temporal precision. Individual video frames are triggered by digital pulses that can be synchronized with behavior, experimental interventions, or recording devices (e.g., electrophysiology). The system is housed within a soundproof chamber with integrated lighting and ventilation, allowing multiple skilled reaching systems in one room. RESULTS: We show that rats acquire the automated task similarly to manual versions, that the task is robust, and can be synchronized with optogenetic interventions. COMPARISON WITH EXISTING METHODS: Existing skilled reaching protocols require high levels of investigator involvement, or, if ad libitum, do not allow for integration of high-speed, synchronized data collection. CONCLUSION: This task will facilitate the study of motor learning and control by efficiently recording large numbers of skilled movements. It can be adapted for use with modern neurophysiology, which demands high temporal precision.
BACKGROUND: Single pellet reaching is an established task for studying fine motor control in which rats reach for, grasp, and eat food pellets in a stereotyped sequence. Most incarnations of this task require constant attention, limiting the number of animals that can be tested and the number of trials per session. Automated versions allow more interventions in more animals, but must be robust and reproducible. NEW METHOD: Our system automatically delivers single reward pellets for rats to grasp with their forepaw. Reaches are detected using real-time computer vision, which triggers video acquisition from multiple angles using mirrors. This allows us to record high-speed (>300 frames per second) video, and trigger interventions (e.g., optogenetics) with high temporal precision. Individual video frames are triggered by digital pulses that can be synchronized with behavior, experimental interventions, or recording devices (e.g., electrophysiology). The system is housed within a soundproof chamber with integrated lighting and ventilation, allowing multiple skilled reaching systems in one room. RESULTS: We show that rats acquire the automated task similarly to manual versions, that the task is robust, and can be synchronized with optogenetic interventions. COMPARISON WITH EXISTING METHODS: Existing skilled reaching protocols require high levels of investigator involvement, or, if ad libitum, do not allow for integration of high-speed, synchronized data collection. CONCLUSION: This task will facilitate the study of motor learning and control by efficiently recording large numbers of skilled movements. It can be adapted for use with modern neurophysiology, which demands high temporal precision.
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