Jul 27, 2023

Vijay Namboodiri has contributed this summary of his lab’s open-source system for behavioral control based on the Arduino Mega microcontroller and a MATLAB-based graphical interface and analysis code.

Associative learning and memory tasks are a staple of many behavioral neuroscience laboratories. These tasks are typically implemented by commercially available hardware/software, which is expensive. More recently, alternative open source behavioral controllers have been proposed. Here, we add to this ecosystem by presenting a behavior controller optimized and customized for associative learning and memory tasks called B-CALM. Advantages of our system are that it is low cost, modular, easy to assemble, operable via a user-friendly GUI, and requires no programming to implement many standard associative learning and memory tasks (described in detail in this document). We provide build instructions for hardware for a mouse headfixed system. However, so long as your hardware uses TTL pulses, any specific input to the Arduino can be swapped out with your own hardware with no changes in the software. Thus, the provided software should be able to control many different types of hardware for different task configurations (e.g., freely moving lever press/nosepoke entry). Our paper shows the precision and utility of this system across a range of behavioral tasks in headfixed mice.

This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. RRID:SCR_023884

Access the design from GitHub!

Check out the repository on GitHub.

Read more about it!

Check out the publication to read more about B-CALM (article is available open-access from a link on the GitHub as well)!