June 18, 2020
Jonathan Krynitsky and colleagues from the Kravitz lab at Washington University have constructed and shared RAT, a closed loop system for machine vision rodent tracking and task control.
The Rodent Arena Tracker, or RAT, is a low cost wireless position tracker for automatically tracking mice in high contrast arenas. The device can use subject position information to control other devices in real time, allowing for closed loop control of various tasks based on positional behavior data. The device is based on the OpenMV Cam M7 (openmv.io), an opensource machine vision camera equipped with onboard processing for real-time analysis which reduces data storage requirements and removes the need for an external computer. The authors optimized the control code for tracking mice and created a custom circuit board to run the device off a battery and include a real-time clock for synchronization, a BNC input/output port, and a push button for starting the device. The build instructions for RAT, as well as validation data to highlight effectiveness and potential uses for the device are available in their recent publication. Further, all the design files, such as the PCB design, 3D printer files, python code, etc, are available on hackaday.io.
Read the full article here!
Or check out the project on hackaday.io!
Krynitsky, J., Legaria, A. A., Pai, J. J., Garmendia-Cedillos, M., Salem, G., Pohida, T., & Kravitz, A. V. (2020). Rodent Arena Tracker (RAT): A Machine Vision Rodent Tracking Camera and Closed Loop Control System. Eneuro, 7(3). doi:10.1523/eneuro.0485-19.2020
February 6, 2020
The Adaptive Motor Control Lab at Harvard recently posted their project, Camera Control, a python based camera software GUI, to Github.
Camera Control is an open-source software package written by postdoctoral fellow Gary Kane that allows video to be recorded in sync with behavior. The python GUI and scripts allows investigators to record from multiple imaging source camera feeds with associated timestamps for each frame. When used in combination with a NIDAQ card, timestamps from a behavioral task can also be recorded on the falling edge of a TTL signal. This allows video analysis to be paired with physiological recording which can be beneficial in assessing behavioral results. This package requires Windows 10, Anaconda, and Git, and is compatible with Imaging Source USB3 cameras. The software package is accessible for download from the lab’s github and instructions for installation and video recording are provided.
Find more on Github.
Kane, G. & Mathis, M. (2019). Camera Control: record video and system timestamps from Imaging Source USB3 cameras. GitHub. https://zenodo.org/badge/latestdoi/200101590
July 3, 2019
Michael Romano and colleagues from the Han Lab at Boston University recently published their project using a Teensy microcontroller to control an sCMOS camera in behavioral experiments to obtain high temporal precision:
Teensy microcontrollers are becoming increasingly more popular and widespread in the neuroscience community. One benefit of using a Teensy is its ease of programming for those with little programming experience, as it uses Arduino/C++ language. An additional benefit of using a Teensy microcontroller is that it can take in and send out time-precise signals. Romano et al. developed a flexible Teensy 3.2-based interface for data acquisition and delivery of analog and digital signals during a rodent locomotion tracking experiment and in a trace eye blink conditioning experiment. The group shows how the interface can be paired with optical calcium imaging as well. The setup integrates a sCMOS camera with behavioral experiments, and the interface is rather user-friendly.
The Teensy interface ensures that the data is temporally precise, and the Teensy interface can also deliver digital signals with microsecond precision to capture images from a paired sCMOS camera. Calcium imaging can be performed during the eye blink conditioning experiment. This was done through pulses send to the camera to capture calcium activity in the hippocampus at 20 Hz from the Teensy. Additionally, the group shows that the Teensy interface can also generate analog sound waveforms to drive speakers for the eye blink experiment. The study shows how an inexpensive piece of lab equipment, like a simple Teensy microcontroller, can be utilized to drive multiple aspects of a neuroscience experiment, and provides inspiration for future experiments to utilize microcontrollers to control behavioral experiments.
For more details on the project, check out the project’s GitHub here.
Romano, M., Bucklin, M., Gritton, H., Mehrotra, D., Kessel, R., & Han, X. (2019). A Teensy microcontroller-based interface for optical imaging camera control during behavioral experiments. Journal of Neuroscience Methods, 320, 107-115.
February 6, 2019
Arne Meyer and colleagues recently shared their design and implementation of a head-mounted camera system for capturing detailed behavior in freely moving mice.
Video monitoring of animals can give great insight to behaviors. Most video monitoring systems to collect precise behavioral data require fixed position cameras and stationary animals, which can limit observation of natural behaviors. To address this, Meyer et al. developed a system which combines a lightweight head-mounted camera and head-movement sensors to detect behaviors in mice. The system, built using commercially available and 3D printed parts, can be used to monitor a variety of subtle behaviors including eye position, whisking, and ear movements in unrestrained animals. Furthermore, this device can be mounted in combination with neural implants for recording brain activity.
Read more here! You can also check out their github here. Documentation and files are also available on OpenEphys here.
Meyer, A. F., Poort, J., O’Keefe, J., Sahani, M., & Linden, J. F. (2018). A Head-Mounted Camera System Integrates Detailed Behavioral Monitoring with Multichannel Electrophysiology in Freely Moving Mice. Neuron, 100(1). doi:10.1016/j.neuron.2018.09.020