Automated system for training and assessing reaching and grasping behaviors in rodents

Abstract

Background: Reaching, grasping, and pulling behaviors are studied across species to investigate motor control and problem solving. String pulling is a distinct reaching and grasping behavior that is rapidly learned, requires bimanual coordination, is ethologically grounded, and has been applied across species and disease conditions.

New method: Here we describe the PANDA system (Pulling And Neural Data Analysis), a hardware and software system that integrates a continuous string loop connected to a rotary encoder, feeder, microcontroller, high-speed camera, and analysis software for the assessment and training of reaching, grasping, and pulling behaviors and synchronization with neural data.

Results: We demonstrate this system in rats implanted with electrodes in motor cortex and hippocampus and show how it can be used to assess relationships between reaching, pulling, and grasping movements and single-unit and local-field activity. Furthermore, we found that automating the shaping procedure significantly improved performance over manual training, with rats pulling > 100 m during a 15-minute session.

Comparison with existing methods: String-pulling is typically shaped by tying food reward to the string and visually scoring behavior. The system described here automates training, streamlines video assessment with deep learning, and automatically segments reaching movements into distinct reach/pull phases. No system, to our knowledge, exists for the automated shaping and assessment of this behavior.

Conclusions: This system will be of general use to researchers investigating motor control, motivation, sensorimotor integration, and motor disorders such as Parkinson's disease and stroke.

Keywords: Automation; Grasping; Hippocampus; Motor control; Motor cortex; Parkinson's disease; Reaching; String pulling.