Autoreward2

May 26, 2017

Jesús Ballesteros, Ph.D. (Learning and Memory Research Group, Department of Neurophysiology at Ruhr-University Bochum, Germany) has generously his project, called Autoreward2, with OpenBehavior. Autoreward2 is an Elegoo Uno-based system designed to detect and reward rodents in a modified T-maze task.


In designing their modified T-maze, Ballesteros found the need for an automatic reward delivery system. Using open-source resources, he aimed to create a system with the following capabilities:

  • Detect an animal at a certain point in a maze;
  • Deliver a certain amount of fluid through the desired licking port;
  • Provide visual cues that indicate which point in the maze has been reached;
  • Allow different modes to be easily selected using an interface;
  • Allow different working protocols (i.e., habituation, training, experimental, cleaning)

To achieve these aims, he created used an Elegoo UNO

R3 board to read inexpensive infrared emitters. Breaking any infrared beam causes the board to open one or two solenoid valves connected to a fluid tank. The valve remains open for around 75 milliseconds, allowing a single drop of fluid to form at the tip of the licking port. Additionally,  the bread board contains LEDS to signal to the researcher when the IR beam has been crossed.

Currently, a membrane keypad allows different protocols or modes to be selected. The system is powered through a 9V wall adapter, providing 3.3V to the LEDs and IR circuits and 9V to the solenoids.

Importantly, the entire system can be built for under 80€. In the future, Ballesteros hopes to add a screen and an SD card port, and to switch the keypad out for a wireless interface.

 

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_021460

Paper

The full description may be found here.

Arduino

The sketch and arduino code may be found here.

Github

The Github page for the project may be found here.

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