In a recently published article (Erskine et al., 2019), The Schaefer lab at the Francis Crick Institute introduced their new open-source project called AutonoMouse.
AutonoMouse is a fully automated, high-throughput system for self-initiated conditioning and behavior tracking in mice. Many aspects of behavior can be analyzed through having rodents perform in operant conditioning tasks. However, in operant experiments, many variables can potentially alter or confound results (experimenter presence, picking up and handling animals, altered physiological states through water restriction, and the issue that rodents often need to be individually housed to keep track of their individual performances). This was the main motivation for the authors to investigate a way to completely automate operant conditioning. The authors developed AutonoMouse as a fully automated system that can track large numbers (over 25) of socially-housed mice through implanted RFID chips on mice. With the RFID trackers and other analyses, the behavior of mice can be tracked as they train and are subsequently tested on (or self-initiate testing in) an odor discrimination task over months with thousands of trials performed every day. The novelty in this study is the fully automated nature or the entire system (training, experiments, water delivery, weighing the animals are all automated) and the ability to keep mice socially-housed 24/7, all while still training them and tracking their performance in an olfactory operant conditioning task. The modular set-up makes it possible for AutonoMouse to be used to study many other sensory modalities, such as visual stimuli or in decision-making tasks. The authors provide a components list, layouts, construction drawings, and step-by-step instructions for the construction and use of AutonoMouse in their publication and on their project’s github.
For more details, check out this youtube clip interview with Andreas Schaefer, PI on the project.
The github for the project’s control software is located here: https://github.com/RoboDoig/autonomouse-control and for the project’s design and hardware instructions is here: https://github.com/RoboDoig/autonomouse-design. The schedule generation program is located here: https://github.com/RoboDoig/schedule-generator
March 13, 2019
Suhasa Kodandaramaiah from the University of Minnesota, Twin Cities, has shared the following about Craniobot, a computer numerical controlled robot for cranial microsurgeries.
The palette of tools available for neuroscientists to measure and manipulate the brain during behavioral experiments has greatly expanded in the previous decade. In many cases, using these tools requires removing sections of the skull to access the brain. The procedure to remove the sub-millimeter thick mouse skull precisely without damaging the underlying brain can be technically challenging and often takes significant skill and practice. This presents a potential obstacle for neuroscience labs wishing to adopt these technologies in their research. To overcome this challenge, a team at the University of Minnesota led by Mathew Rynes and Leila Ghanbari (equal contribution) created the ‘Craniobot,’ a cranial microsurgery platform that combines automated skull surface profiling with a computer numerical controlled (CNC) milling machine to perform a variety of cranial microsurgical procedures on mice. The Craniobot can be built from off-the-shelf components for a little over $1000 and the team has demonstrated its capability to perform small to large craniotomies, skull thinning procedures and for drilling pilot holes for installing bone anchor screws.
Read more about the Craniobot here. Software package for controlling the craniobot can be found on Github.
Ghanbari, L., Rynes, M. L., Hu, J., Schulman, D. S., Johnson, G. W., Laroque, M., . . . Kodandaramaiah, S. B. (2019). Craniobot: A computer numerical controlled robot for cranial microsurgeries. Scientific Reports, 9(1). doi:10.1038/s41598-018-37073-w
December 12, 2018
Vladislav Voziyanov and colleagues have developed and shared the TRIO Platform, a low-profile in vivo imaging support and restraint system for mice.
In vivo optical imaging methods are common tools for understanding neural function in mice. This technique is often performed in head-fixed, anesthetized animals, which requires monitoring of anesthesia level and body temperature while stabilizing the head. Fitting each of the components necessary for these experiments on a standard microscope stage can be rather difficult. Voziyanov and colleagues have shared their design for the TRIO (Three-In-One) Platform. This system is compact and provides sturdy head fixation, a gas anesthesia mask, and warm water bed. While the design is compact enough to work with a variety of microscope stages, the use of 3D printed components makes this design customizable.
Read more about the TRIO Platform in Frontiers in Neuroscience!
The design files and list of commercially available build components are provided here.
Voziyanov, V., Kemp, B. S., Dressel, C. A., Ponder, K., & Murray, T. A. (2016). TRIO Platform: A Novel Low Profile In vivo Imaging Support and Restraint System for Mice. Frontiers in Neuroscience, 10. doi:10.3389/fnins.2016.00169
October 31, 2018
At the upcoming Society for Neuroscience meeting in San Diego, there will be a number of posters and talks that highlight novel devices and software that have implications for behavioral neuroscience. If you’re heading to the meeting, be sure to check them out! Relevant posters and talks are highlighted in the document, available at the following link: https://docs.google.com/document/d/12XqODhW14K2drCCEARVESoqqE0KrSjksZKN40xURVmk/edit?usp=sharing
We are looking for your feedback to understand how we can better serve the community! We’re also interested to know if/how you’ve implemented some of the open-source tools from our site in your own research.
We would greatly appreciate it if you could fill out a short survey (~5 minutes to complete) about your experiences with OpenBehavior.
July 23, 2018
OpenBehavior has been covering open-source neuroscience projects for a few years, and we are always thrilled to see projects that are well documented and can be easily reproduced by others. To further this goal, we have formed a collaboration with Hackaday.io, who have provided a home for OpenBehavior on their site. This can be found at: https://hackaday.io/OpenBehavior, where we currently have 36 projects listed ranging from electrophysiology to robotics to behavior. We are excited about this collaboration because it provides a straightforward way for people to document their projects with instructions, videos, images, data, etc. Check it out, see what’s there, and if you want your project linked to the OpenBehavior page simply tag it as “OPENBEHAVIOR” or drop us a line at the Hackaday page.
Note: This collaboration between OpenBehavior and Hackaday.io is completely non-commercial, meaning that we don’t pay Hackaday.io for anything, nor do we receive any payments from them. It’s simply a way to further our goal of promoting open-source neuroscience tools and their goal of growing their science and engineering community.
An interesting summary of recent methods for monitoring behavior in rodents was published this week in Nature.The article mentions Lex Kravitz and his lab’s efforts on the Feeding Experimentation Device (FED) and also OpenBehavior. Check it out: https://www.nature.com/articles/d41586-018-02403-5
January 8th, 2018
The de Bivort lab and FlySorter, LLC are happy to share on OpenBehavior their open-source Drosophila handling platform, called MAPLE: Modular Automated Platform for Large-Scale Experiments.
Drosophila Melanogaster has proven a valuable genetic model organism due to the species’ rapid reproduction, low-maintenance, and extensive genetic documentation. However, the tedious chore of handling and manually phenotyping remains a limitation with regards to data collection. MAPLE: a Modular Automated Platform for Large-Scale Experiments provides a solution to this limitation.
MAPLE is a Drosophila-handing robot that boasts a modular design, allowing the platform to both automate diverse phenotyping assays and aid with lab chores (e.g., collecting virgin female flies). MAPLE permits a small-part manipulator, a USB digital camera, and a fly manipulator to work simultaneously over a platform of flies. Failsafe mechanisms allow users to leave MAPLE unattended without risking damage to MAPLE or the modules.
The physical platform integrates phenotyping and animal husbandry to allow end-to-end experimental protocols. MAPLE features a large, physically-open workspace for user convenience. The sides, top, and bottom are made of clear acrylic to allow optical phenotyping at all time points other than when the end-effector carriages are above the modules. Finally, the low cost and scalability allow large-scale experiments ($3500 vs hundreds of thousands for a “fly-flipping” robot).
MAPLE’s utility and versatility were demonstrated through the execution of two tasks: collection of virgin female flies, and a large-scale longitudinal measurement of fly social networks and behavior.
Links to materials:
Raw data and analysis scripts
De Bivort Lab Site