Inexpensive, scalable camera system for tracking rats in large spaces

Area of Science:

• Neuroscience
• Computational Neuroscience
• Behavioral Neuroscience

Background:

• Studies on neural correlates of spatial navigation are often limited to small arenas (≤1 m²) due to hardware constraints of recording cables.
• Wireless neural recording systems offer greater range but lack precise animal tracking capabilities in large environments.
• Existing position tracking systems can limit the scale of experiments investigating neural representations of space.

Purpose of the Study:

• To develop and validate an open-source, scalable, and low-cost multicamera tracking system for large environments.
• To enable the characterization of neural correlates of spatial navigation in biologically relevant, large-scale environments.
• To improve the temporal accuracy of animal tracking for precise neural data analysis.

Main Methods:

• Development and benchmarking of a novel multicamera tracking system ('Picamera system') using low-cost hardware.
• Integration of the Picamera system with wireless neural recording technology.
• Comparative analysis of the Picamera system's temporal accuracy against a popular commercial tracking system.

Main Results:

• The Picamera system demonstrated substantially higher temporal accuracy compared to a commercial system.
• Improved accuracy in estimating spatial firing characteristics and head direction tuning of neurons was observed.
• The system successfully facilitated studies in environments up to 16.5 m².

Conclusions:

• The developed Picamera system overcomes previous hardware limitations, enabling neural studies in large, biologically relevant spaces.
• Enhanced temporal accuracy is critical for aligning multi-camera data and accurately characterizing spatially modulated neural activity.
• This advancement facilitates a deeper understanding of neural mechanisms underlying spatial navigation at a larger scale.