PiRATeMC: A highly flexible, scalable, and low-cost system for obtaining high quality video recordings for behavioral neuroscience

Samuel W. Centanni, Alexander C.W. Smith

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

With the rapidly accelerating adoption of machine-learning based rodent behavioral tracking tools, there is an unmet need for a method of acquiring high quality video data that is scalable, flexible, and relatively low-cost. Many experimenters use webcams, GoPros, or other commercially available cameras that can be expensive, offer minimal flexibility of recording parameters, and not optimized for recording rodent behavior, leading to suboptimal and inconsistent video quality. Furthermore, commercially available products are not conducive for synchronizing multiple cameras, or interfacing with third-party equipment to allow time-locking of video to other equipment such as microcontrollers for closed-loop experiments. We present a low-cost, customizable ecosystem of behavioral recording equipment, PiRATeMC (Pi-based Remote Acquisition Technology for Motion Capture) based on Raspberry Pi Camera Boards with the ability to acquire high quality recordings in bright/low light, or dark conditions under infrared light. PiRATeMC offers users control over nearly every recording parameter, and can be fine-tuned to produce optimal videos in any behavioral apparatus. This setup can be scaled up for synchronous control of any number of cameras via a self-contained network without burdening institutional network infrastructure. The Raspberry Pi is an excellent platform with a large online community designed for novice and inexperienced programmers interested in using an open-source recording system. Importantly, PiRATeMC supports TTL and serial communication, allowing for synchronization and interfacing of video recording with behavioral or other third-party equipment. In sum, PiRATeMC minimizes the cost-prohibitive nature of conducting and analyzing high quality behavioral neuroscience studies, thereby increasing accessibility to behavioral neuroscience.

Original languageEnglish
Article number100108
JournalAddiction Neuroscience
Volume8
DOIs
StatePublished - Dec 2023
Externally publishedYes

Keywords

  • Behavioral neuroscience
  • Pose estimation
  • Rodent behavior
  • Video tracking

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