Most studies of neural correlates of spatial navigation are restricted to small arenas (≤1 m2) because of the limits imposed by the recording cables. New wireless recording systems have a larger recording range. However, these neuronal recording systems lack the ability to track animals in large area, constraining the size of the arena. We developed and benchmarked an open-source, scalable multicamera tracking system based on low-cost hardware. This "Picamera system" was used in combination with a wireless recording system for characterizing neural correlates of space in environments of sizes up to 16.5 m2. The Picamera system showed substantially better temporal accuracy than a popular commercial system. An explicit comparison of one camera from the Picamera system with a camera from the commercial system showed improved accuracy in estimating spatial firing characteristics and head direction tuning of neurons. This improved temporal accuracy is crucial for accurately aligning videos from multiple cameras in large spaces and characterizing spatially modulated cells in a large environment. NEW & NOTEWORTHY Studies of neural correlates of space are limited to biologically unrealistically small spaces by neural recording and position tracking hardware. We developed a camera system capable of tracking animals in large spaces at a high temporal accuracy. Together with the new wireless recording systems, this system facilitates the study of neural correlates of space at biologically relevant scale. This increased temporal accuracy of tracking also improves the estimates of spatiotemporal correlates of neural activity.
Keywords: hippocampus; large space; medial entorhinal cortex; spatial navigation.