TY - JOUR
T1 - Rodent arena tracker (Rat)
T2 - A machine vision rodent tracking camera and closed loop control system
AU - Krynitsky, Jonathan
AU - Legaria, Alex A.
AU - Pai, Julia J.
AU - Garmendia-Cedillos, Marcial
AU - Salem, Ghadi
AU - Pohida, Tom
AU - Kravitz, Alexxai V.
N1 - Publisher Copyright:
© 2020 Krynitsky et al.
PY - 2020
Y1 - 2020
N2 - Video tracking is an essential tool in rodent research. Here, we demonstrate a machine vision rodent tracking camera based on a low-cost, open-source, machine vision camera, the OpenMV Cam M7. We call our device the rodent arena tracker (RAT), and it is a pocket-sized machine vision-based position tracker. The RAT does not require a tethered computer to operate and costs about $120 per device to build. These features make the RAT scalable to large installations and accessible to research institutions and educational set-tings where budgets may be limited. The RAT processes incoming video in real-time at 15 Hz and saves x and y positional information to an onboard microSD card. The RAT also provides a programmable multi-function input/output pin that can be used for controlling other equipment, transmitting tracking information in real time, or receiving data from other devices. Finally, the RAT includes a real-time clock (RTC) for accurate time stamping of data files. Real-time image processing averts the need to save video, greatly re-ducing storage, data handling, and communication requirements. To demonstrate the capabilities of the RAT, we performed three validation studies: (1) a 4-d experiment measuring circadian activity patterns; (2) logging of mouse positional information alongside status information from a pellet dispensing device; and (3) control of an optogenetic stimulation system for a real-time place preference (RTPP) brain stimulation reinforcement study. Our design files, build instructions, and code for the RAT implementation are open source and freely available online to facilitate dissemination and further development of the RAT.
AB - Video tracking is an essential tool in rodent research. Here, we demonstrate a machine vision rodent tracking camera based on a low-cost, open-source, machine vision camera, the OpenMV Cam M7. We call our device the rodent arena tracker (RAT), and it is a pocket-sized machine vision-based position tracker. The RAT does not require a tethered computer to operate and costs about $120 per device to build. These features make the RAT scalable to large installations and accessible to research institutions and educational set-tings where budgets may be limited. The RAT processes incoming video in real-time at 15 Hz and saves x and y positional information to an onboard microSD card. The RAT also provides a programmable multi-function input/output pin that can be used for controlling other equipment, transmitting tracking information in real time, or receiving data from other devices. Finally, the RAT includes a real-time clock (RTC) for accurate time stamping of data files. Real-time image processing averts the need to save video, greatly re-ducing storage, data handling, and communication requirements. To demonstrate the capabilities of the RAT, we performed three validation studies: (1) a 4-d experiment measuring circadian activity patterns; (2) logging of mouse positional information alongside status information from a pellet dispensing device; and (3) control of an optogenetic stimulation system for a real-time place preference (RTPP) brain stimulation reinforcement study. Our design files, build instructions, and code for the RAT implementation are open source and freely available online to facilitate dissemination and further development of the RAT.
KW - Machine vision
KW - Mouse
KW - Rodent
KW - Tracking
KW - Video
UR - http://www.scopus.com/inward/record.url?scp=85084694292&partnerID=8YFLogxK
U2 - 10.1523/ENEURO.0485-19.2020
DO - 10.1523/ENEURO.0485-19.2020
M3 - Article
C2 - 32284342
AN - SCOPUS:85084694292
SN - 2373-2822
VL - 7
JO - eNeuro
JF - eNeuro
IS - 3
M1 - ENEURO.0485-19.2020
ER -