期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 271, 期 -, 页码 119-127出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2016.07.009
关键词
Skilled reaching; Single pellet grasping; Forelimb; Motor learning; Automated task; Rat
资金
- National Institute of Neurological Disease and Stroke [K08-NS072183]
- Brain Research Foundation
- Parkinson's Disease Foundation [PDF-FBS-1454]
- National Institute of Health [T32 NS007222]
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. (C) 2016 Elsevier B.V. All rights reserved.
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