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Automated system for training and assessing string-pulling behaviors in rodents.

Gianna A Jordan¹, Abhilasha Vishwanath², Gabriel Holguin²

¹Biomedical Engineering, University of Arizona, Tucson Arizona.

Biorxiv : the Preprint Server for Biology

|July 18, 2023

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The PANDA system automates string-pulling tasks for studying motor control and neural activity in rats. This automated approach significantly enhances training efficiency and behavioral assessment for motor disorders research.

Area of Science:

Neuroscience
Behavioral Science
Engineering

Background:

String-pulling tasks are crucial for studying bimanual motor control and problem-solving across species.
Current methods rely on manual training and video scoring, which are labor-intensive and lack automation.
There is a need for automated systems to improve the efficiency and accuracy of string-pulling behavior analysis.

Approach:

Developed the PANDA (Pulling And Neural Data Analysis) system, an integrated hardware and software solution.
The system uses a continuous string loop, rotary encoder, feeder, microcontroller, and high-speed camera for automated training and assessment.
PANDA synchronizes behavioral data with neural recordings from motor cortex and hippocampus.

Key Points:

Automated shaping significantly improved rat performance in string-pulling tasks, with over 100 meters pulled per session.

Keywords:

Parkinson’s disease automation hippocampus motor control motor cortex string pulling

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Last Updated: Jul 23, 2025

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A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

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The PANDA system enables detailed analysis of the relationship between paw movements and neural activity (single-unit and local-field potentials).

Demonstrated system efficacy in both unimplanted and electrode-implanted rats.

Conclusions:

The PANDA system offers a cost-effective and efficient tool for researchers studying motor control and sensorimotor integration.
Facilitates research into motivation and motor disorders like Parkinson's disease, Huntington's disease, and stroke.
Supports advanced investigation of neural mechanisms underlying coordinated movement and learning.