Dec 16, 2021

In behavioral neuroscience, operant boxes remain one of the most important tools for drug discovery and for understanding behaviors involving learning, memory, and attention. In more recent years they have also become an important component in understanding the brain circuitry underpinning behaviors when used in combination with in vivo measurements and stimulations such as electrophysiology and optogenetics. While commercial operant boxes can often be equipped to accommodate the addition of neurophysiological recording and manipulation, this can be prohibitively expensive and complex. Additionally, as operant boxes are rarely designed with neurophysiology in mind from the beginning, the resulting solution will often have reward receptacles, nose pokes, or other features that are not ideal for use with tethered animals. Therefore, Sampath Kapanaiah and colleagues have developed a python-based operant-box system in a 5-choice design (pyOS-5), an open source system optimized for use with tethered animals.

The 5-choice design is highly versatile, allowing for assays for attention, perseveration, motor impulsivity, decision impulsivity, rule-shift learning, working memory, and motivation. The control electronics for pyOS-5 build on pyControl, controlling a custom PCB integrating 5 infra-red break-beam sensors and 5 stimulus LEDs, a single nose-poke for the reward receptacle, a stepper motor for the control of a custom peristaltic pump for reward delivery, an audio board for tone generation through an attached speaker, a house light and fan, an LED driver for optogenetic stimulation, and bidirectional communication with external devices via TTL pulses.

PyOS-5 includes designs for the inner operant box as well as an outer insulating box. PyOS-5 also provides a powerful custom graphical user-interface along with a wide range of ready-to-use scripts for 5-choice based tasks and functionality to extract performance measures for online monitoring and offline analysis. PyOS-5 is a highly versatile system built from the ground up with neurophysiology in mind.


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_022336

Read the Paper!

Read more about pyOS-5 in the Scientific Reports paper!

GitHub Repository

Get access to necessary files and code for pyOS-5 from their GitHub repository!

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