March 5, 2020
One of the co-founders of OpenBehavior, Lex Kravitz recently participated in an interview about the development of the Feeding Experiment Device, lovingly known as FED! Read more to learn about how the project started, how the device has improved and what’s next for the project, including a partnership with the OpenEphys team. Perhaps this will inspire and guide you through your own project development!
1. Tell us about FED: What is it intended to do? What was its initial purpose for use in your lab?
FED is a home-cage compatible device for training mice! FED stands for the Feeding Experimentation Device, the name is also a pun: it was invented while my lab was at the NIH, so the FED was made by the Feds 🙂
The initial purpose of FED was to measure feeding, and quantify daily calories eaten by mice living in home cages. Our lab studies feeding and obesity and the automated methods that exist for measuring food intake (typically small weighing scales that attach to the cage) were too expensive for our lab to purchase enough of them for our studies, which often involved >50 mice at a time. We figured other people might have the same need so we decided to invent something to do this. We settled on a pellet dispensing approach because we can buy pellets in precision sizes (20mg each), which means that instead of weighing the food we can calculate the calories from the number of pellets eaten. From an engineering standpoint counting pellets seemed easier than scales too. I was very fortunate to have a postbac Katrina Nguyen in my lab with a background in BioMedical Engineering, and she spearheaded the development of our first device, which we called FED. After she left the lab another postbac, Mohamed Ali, worked with me to create the FED2, which was a slightly refined version of FED, and FED2 eventually evolved into the FED3 model that we’re working with today.
2. Can you briefly describe the components of the device, what it is made of, how long it takes to make one?
FED is a “smart” pellet dispenser. At its core it’s a 3D printed pellet dispenser, which also has a microcontroller board inside, the Adafruit M0 Adalogger, which is an extremely capable microcontroller. In addition to dispensing pellets, FED3 has two “nosepokes” for mice to interact with it, 8 multicolored LEDs, an audio generator, a screen for user feedback, and a programmable output for synchronizing FED3 behavior with other techniques like optogenetics or fiber photometry. FED3 is small enough to fit inside of rodent home cages and does not require a connected computer to operate. FED3 is designed to simplify rodent training, it ships with 12 built-in programs, including fixed-ratio and progressive-ratio operant training routines, as well as optogenetic self-stimulation programs. Most importantly, FED3 is open-source and it can be hacked and re-programmed by users to achieve new functionality. It takes me about 1-2 hours to put one together from scratch, it would probably take a new user 3-4 hours. The electronics parts cost about $135, and the Open Ephys Production Site is selling assembled electronics for a small markup. With the electronics and printed parts in hand it takes about 15 minutes to assemble.
3. Since initial development of the device, what general improvements have been made?
Since Katrina Nguyen made the first FED, we worked a lot to improve reliability of the device. We envisioned this being an “always on” device that can sit in a cage and measure food intake around the clock. It holds about 10 days worth of pellets and the battery lasts about a week, so in theory this is possible. The major challenge, however, is that it is a mechanical pellet dispenser that is prone to issues such as jamming or dispensing errors. In practice we clean and test the FEDs each day when we run multi-day studies.
One issue with the first FED was that we had no way to get user feedback, so if it jammed the only way we’d even know was if we opened the cage and tried to get a pellet. For this reason we put a screen on FED2, so we could see how many pellets were dispensed and also get an error message when it was jammed. For FED3 we added more functions, such as the two “nosepokes” for the mouse to interact with FED to run full home-cage operant tasks. Finally, we added a synchronized BNC output connector, which let’s us sync the nosepoke and pellet data with ephys or fiber photometry. Several groups we know are doing this to synchronize fiber photometry recordings with pellet retrieval, or generate pulses for optogenetic self-stimulation.
4. Switching gears from the actual device to production and replication, what have you seen as necessary steps to getting other labs / researchers successfully using your device (documentation, forums, contact email, etc)?
In terms of my own work to get FED3 into other people’s hands, I think the most important thing was to get other people to start using it. So I’ve tried to keep our online documentation for FED3 complete and up to date. I also give a lot of them out in exchange for feedback – basically it’s important for other people to try building and using a device to discover its flaws that you might not realize because you’ve worked on it too long. I don’t wait until the devices were perfect before I started giving give away so I could find out what worked and what didn’t for new users.
5. Since updating and producing FED3, you’ve decided to connect with OpenEphys production team to sell the device on their website. Why did you decide to now sell the device and have OpenEphys distribute it? What are the advantages (to you as the developer, to OpenEphys, and to the potential users) of deciding to put the device on OpenEphys for production?
It is very challenging to distribute a hardware device as a researcher – there aren’t good revenue streams for funding development of devices like this and there aren’t good logistics for distributing them through a University setting. It also takes a lot of time to communicate with people, mail out devices, and provide support. Really, all of this are better suited to a company, and for several reasons I don’t want to start one.
Therefore, I jumped at the chance to work with the Open Ephys Production Site to take on these distribution challenges! You can see their FED3 sales page here. Working with them has been really fun and productive – I mailed them a FED3 and they first did a thorough evaluation of the electronics and found several things they could improve in my design to make it more robust and better for manufacture. So we worked together to implement and test those improvements. The main advantage for me is that working with them amplifies the effort our team did on this device. I would love to see cheap and easy operant training available in every lab. I also support their broader mission of distributing open source tools in neuroscience. I’ll take this moment to make a brief (no) conflict of interest statement, I’m not receiving any funding back from their sales of FED3, the proceeds are all going to support their efforts to distribute FED3 and other open source hardware.
6. Describe the connection between you as a developer and OpenEphys production. Can / should others try to “pitch” their device to OpenEphys (or to other companies out there for production)?
Working with OEPS was very collaborative. We started by evaluating whether the FED3 was something they wanted to sell, and they quickly determined it was. Filipe Carvalho then went through the design files and made some recommendations for things he wanted to change to improve manufacturability. For example, our version relied heavily on Adafruit breakout boards, whereas he engineered the relevant chips onto the FED3 printed circuit board assembly. This makes FED3 easier to manufacture and more reliable. We worked together on all changes, and it was a really productive collaboration. I would definitely suggest others “pitch” their ideas to OEPS! Even if it doesn’t work out for OEPS to distribute the idea I’m sure they’ll get good feedback and learn something about manufacturing and distributing open source hardware.
7. What general advice or instructions do you have for other researchers looking to develop their devices in a similar way. Please let us know of anything you’d like to share with the open-source neuroscience world.
I would advise people to share their designs early and often. Don’t wait until the design is perfect (it never will be)! The easier you make it for others to use your device the more of a chance they’ll see the value in it that made you create it in the first place. Try to document online as you go, ie: by using github.com or hackaday.io to keep a record of changes you make and validation experiments you perform. It can be difficult to go back and create documentation after the fact, but if you do it as you go you have a built-in record for what you did, and why you made the design decisions you made. If you keep up documentation on the way it can also turn into something that you can publish as a methods paper when it’s ready for that. So in summary – share early and share often, and document your work!