Open-Source Platform for Adjustable Training Regimes in Freely Moving and Head-Fixed Mice

Area of Science:

• Neuroscience
• Behavioral Science
• Computational Neuroscience

Background:

• Rodent models are crucial for understanding neural circuits underlying perception and decision-making.
• Existing behavioral platforms often lack flexibility and affordability, hindering detailed research.
• Advanced molecular tools require adaptable behavioral systems to link neural function with behavior.

Purpose of the Study:

• To present a novel, low-cost, and flexible behavioral platform for rodent research.
• To enable the study of complex behaviors in both head-fixed and freely moving conditions.
• To facilitate the integration of molecular tools with behavioral paradigms.

Main Methods:

• Developed a behavioral platform with a user-interactive GUI for on-line parameter adjustment.
• Designed the platform to support both head-fixed and freely moving task configurations.
• Integrated multiple external devices for synchronized recording of task-related variables.
• Trained mice in discrimination tasks (head-fixed and freely moving) to demonstrate platform flexibility.
• Utilized the platform to assess behavioral performance in mice with an autism spectrum disorder-associated mutation.

Main Results:

• The platform successfully executed both head-fixed and freely moving behavioral tasks.
• Standardized data output facilitated efficient data analysis for single users.
• Demonstrated the platform's utility in studying genetically modified mice.
• Showcased synchronized data acquisition from multiple integrated devices.

Conclusions:

• The presented platform offers an affordable and reproducible solution for studying behavioral decision-making in rodents.
• Its flexibility supports diverse behavioral paradigms and integration with various external devices.
• This tool advances the investigation of neural mechanisms of cognition in both healthy and diseased states.