December 19, 2018
In 2007, Adam Hoffman and colleagues shared their design for an Electric Operant Testing Apparatus (ELOPTA) in Behavior Research Methods.
Operant behavior is commonly studied in behavioral neuroscience, therefore there is a need for devices to train and collect data from animals in operant procedures. Commercially available systems often require training to program and use and can be expensive. Hoffman and colleagues developed a system that can automatically control operant procedures and record behavioral outputs. This system is intended to be easy to use because it is easily programmable, portable and durable.
Read more here!
Hoffman, A.M., Song, J. & Tuttle, E.M. Behavior Research Methods (2007) 39: 776. https://doi.org/10.3758/BF03192968
November 30, 2018
Nikolas Francis and Patrick Kanold of the University of Maryland share their design for Psibox, a platform for automated operant conditioning in the mouse home cage, in Frontiers in Neural Circuits.
The ability to collect behavioral data from large populations of subjects is advantageous for advancing behavioral neuroscience research. However, few cost-effective options are available for collecting large sums of data especially for operant behaviors. Francis and Kanold have developed and shared Psibox, an automated operant conditioning system. It incorporates three modules for central control , water delivery, and home cage interface, all of which can be customized with different parts. The system was validated for training mice in a positive reinforcement auditory task and can be customized for other tasks as well. The full, low-cost system allows for quick training of groups of mice in an operant task with little day-to-day experimenter involvement.
Learn how to set up your own Psibox system here!
Francis, NA., Kanold, PO., (2017). Automated operant conditioning in the mouse home cage. Front. Neural Circuits.
October 17, 2018
In the journal HardwareX, Jinook Oh and colleagues share their design for OpenFeeder, an automatic feeder for animal experiments.
Automatic delivery of precisely measured food amounts is important when studying reward and feeding behavior. Commercially available devices are often designed with specific species and food types in mind, limiting the ways that they can be used. This open-source automatic feeding design can easily be customized for food types from seeds to pellets to fit the needs of any species. OpenFeeder integrates plexiglass tubes, Arduino Uno, a motor driver, and piezo sensor to reliably deliver accurate amounts of food, and can also be built using 3D printed parts.
Read more from HardwareX.
Or check out the device on Open Science Framework and Github.
We are looking for your feedback to understand how we can better serve the community! We’re also interested to know if/how you’ve implemented some of the open-source tools from our site in your own research.
We would greatly appreciate it if you could fill out a short survey (~5 minutes to complete) about your experiences with OpenBehavior.
October 3, 2018
Thomas Akam and researchers from the Champalimaud Foundation and Oxford University have developed pyControl, a system that combines open-source hardware and software for control of behavioral experiments.
The ability to seamlessly control various aspects of a complex task is important for behavioral neuroscience research. pyControl, an open-source framework, combines Python scripts and a Micropython microcontroller for the control of behavioral experiments. This framework can be run through a command line interface (CLI), or in a user-friendly graphical user interface (GUI) that allows users to manage a variety of devices such as nose pokes, LED drivers, stepper motor controllers and more. The data collected using this system can then be imported easily into Python for data analysis. In addition to complete documentation on the pyControl website, users are welcome to ask questions and interact with the developers and other users via a pyControl Google group.
Read more on the pyControl website.
Purchase the pyControl breakout board at OpenEphys.
Or check out the pyControl Google group!
August 8, 2018
In HardwareX, an open access journal for designing, building and customizing opensource scientific hardware, Martin A. Raymond and colleagues share their design for a user-constructed, low-cost lickometer.
Researchers interested in ingestive behaviors of rodents commonly use licking behavior as a readout for the amount of fluid a subject consumes, as recorded by a lickometer. Commercially available lickometers are powerful tools to measure this behavior, but can be expensive and often require further customization. The authors offer their own design for an opensource lickometer that utilizes readily available or customizable components such as a PC sound card and 3D printed drinking bottle holder. The data from this device is collected by Audacity, and opensource audio program, which is then converted to a .csv format which can be analyzed using an R script made available by the authors to assess various features of licking microstructure. A full bill of materials, instructions for assembly and links to design files are available in the paper.
Check out the full publication here!
Raymond, M. A., Mast, T. G., & Breza, J. M. (2018). An open-source lickometer and microstructure analysis program. HardwareX, 4. doi:10.1016/j.ohx.2018.e00035
July 23, 2018
OpenBehavior has been covering open-source neuroscience projects for a few years, and we are always thrilled to see projects that are well documented and can be easily reproduced by others. To further this goal, we have formed a collaboration with Hackaday.io, who have provided a home for OpenBehavior on their site. This can be found at: https://hackaday.io/OpenBehavior, where we currently have 36 projects listed ranging from electrophysiology to robotics to behavior. We are excited about this collaboration because it provides a straightforward way for people to document their projects with instructions, videos, images, data, etc. Check it out, see what’s there, and if you want your project linked to the OpenBehavior page simply tag it as “OPENBEHAVIOR” or drop us a line at the Hackaday page.
Note: This collaboration between OpenBehavior and Hackaday.io is completely non-commercial, meaning that we don’t pay Hackaday.io for anything, nor do we receive any payments from them. It’s simply a way to further our goal of promoting open-source neuroscience tools and their goal of growing their science and engineering community.
June 15, 2018
In a recent preprint on BioRxiv, Alessio Buccino and colleagues from the University of Oslo provide a step-by-step guide for setting up an open source, low cost, and adaptable system for combined behavioral tracking, electrophysiology, and closed-loop stimulation. Their setup integrates Bonsai and Open Ephys with multiple modules they have developed for robust real-time tracking and behavior-based closed-loop stimulation. In the preprint, they describe using the system to record place cell activity in the hippocampus and medial entorhinal cortex, and present a case where they used the system for closed-loop optogenetic stimulation of grid cells in the entorhinal cortex as examples of what the system is capable of. Expanding the Open Ephys system to include animal tracking and behavior-based closed-loop stimulation extends the availability of high-quality, low-cost experimental setup within standardized data formats.
Read more on BioRxiv, or on GitHub!
Buccino A, Lepperød M, Dragly S, Häfliger P, Fyhn M, Hafting T (2018). Open Source Modules for Tracking Animal Behavior and Closed-loop Stimulation Based on Open Ephys and Bonsai. BioRxiv. http://dx.doi.org/10.1101/340141
June 12, 2018
In a recent publication in the Frontiers in Systems Neuroscience, Solari and colleagues of the Hungarian Academy of Sciences and Semmelweis University have shared the following about a behavioral setup for temporally controlled rodent behavior. This arrangement allows for training of head-fixed animals with calibrated sound stimuli, precisely timed fluid and air puff presentations as reinforcers. It combines microcontroller-based behavior control with a sound delivery system for acoustic stimuli, fast solenoid valves for reinforcement delivery and a custom-built sound attenuated chamber, and is shown to be suitable for combined behavior, electrophysiology and optogenetics experiments. This system utilizes an optimal open source setup of both hardware and software through using Bonsai, Bpod and OpenEphys.
Read more here!
Solari N, Sviatkó K, Laszlovszky T, Hegedüs P and Hangya B (2018). Open Source Tools for Temporally Controlled Rodent Behavior Suitable for Electrophysiology and Optogenetic Manipulations. Front. Syst. Neurosci. 12:18. doi: 10.3389/fnsys.2018.00018
May 21, 2018
Meaghan Creed has developed a novel device for assessing preferences by mice among fluids in their homecages, i.e. two-bottle choice test. She shared the design on http://hackaday.io and contributed the summary of it below.
Often in behavioral neuroscience, we need to measure how often and how much a mouse will consume multiple liquids in their home cage. Examples include sucrose preference tasks in models of depression, or oral drug self-administration (ie. Morphine, opiates) in the context of addiction. Classically, two bottles are filled with liquids and volumes are manually recorded at a single time point. Here, we present a low-cost, two-sipper apparatus that mounts on the inside of a standard mouse cage. Interactions are detected using photointerrupters at the base of each sipper which are logged to an SD card using a standard Arduino. Sippers are constructed from 15 mL conical tubes which allows additional volumetric measurements, the rest of the holding apparatus is 3D printed, and the apparatus is constructed with parts from Arduino and Sparkfun. This automated approach allows for high temporal resolution collected over 24 hours, allowing measurements of patterns of intake in addition to volume measurements. Since we don’t need to manually weigh bottles we can do high-throughput studies, letting us run much larger cohorts.
This is designed such that each set of 2 sippers uses its own Arduino and SD card. With a bit of modification to the code one Arduino Uno can be programmed to log from 6 cages onto the same SD card. Arduino compatible boards with more GPIOs (like Arduino Mega) can log from up to 56 sippers on one Arduino.