An automated rat single pellet reaching system with high-speed video capture

  • Damien J. Ellens
  • , Matt Gaidica
  • , Andrew Toader
  • , Sophia Peng
  • , Shirley Shue
  • , Titus John
  • , Alexandra Bova
  • , Daniel K. Leventhal

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

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.

Original languageEnglish
Pages (from-to)119-127
Number of pages9
JournalJournal of Neuroscience Methods
Volume271
DOIs
StatePublished - Sep 15 2016

Keywords

  • Automated task
  • Forelimb
  • Motor learning
  • Rat
  • Single pellet grasping
  • Skilled reaching

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