Open Skinner Box

Mar 11, 2021

Katherine A. Scott shared the details about her Open Skinner Box on her blog Kscottz.


The Open Skinner Box is an open source operant conditioning chamber used to train animal behavior. The device features a full behavioral apparatus and an online platform for data logging and analysis. In this Open Skinner Box, a buzzer is used to cue the availability of a reward, animals respond via a switch, and a stepper motor is used to deliver a food reward. This Open Skinner Box has additional features that allow for a more automated process controlled by a webserver and easier data collection and analysis. 

This device uses RasberryPi’s camera to collect data when the rodents respond using the switch. RasberryPi’s GPIO pins are used to control the buzzer, the switch and the stepper so that the process is automated and can be run by the external web server, which consolidates the entire system to run experiments. The server is broken down into 4 main components: a Hardware interface to connect the camera, buzzer, switch and stepper; a Camera interface to save the images from the camera and monitor rodent activity; an Experiment runner to begin and end experiments; and a Data Interface to analyze the data. Python, Mongo DB, PiCamera, Numpy, matplotlib, and OpenCV are all used on the webserver to collect and analyze the data. The code can be found at the Github repository linked below.

This device allows behavioral scientists to run experiments, collect and analyze data using open source code and low-cost products that can be monitored from a remote location. This project makes operant behavioral research much more accessible.

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.  Project portal RRID:SCR_021437; Software RRID:SCR_021514

Open Skinner Box Blog Post

Read more about this project on the KScottz blog! 

Read the Documentation

Get access to the code from GitHub. 

Thanks Sarisha!

This project summary is a part of the collection from neuroscience undergraduate students in the Computational Methods course at American University. 

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