Category: Behavioral Apparatus

Automated mouse homecage two-bottle choice test

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.

https://hackaday.io/project/158279-automated-mouse-homecage-two-bottle-choice-test

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.

Open-source touch-screen for rodent behavioral testing

March 9, 2018

O’Leary and colleagues describe an open-source touch-screen for rodent behavioral testing. The manuscript is well documented and includes all of the parts needed to build the system on your own. Very useful methods for testing cognitive function and relating findings across species (rodents, primates, humans). Congrats to the authors on setting a high standard for open-source neuroscience!

O’Leary, J.D., O’Leary, O.F., Cryan, J.F. et al. Behav Res (2018). https://doi.org/10.3758/s13428-018-1030-y

SnackClock

March 1, 2018

From the Kravitz lab at the NIH comes a simple device for dispensing pre-measured quantities of food at regular intervals throughout the day.  Affectionately known as “SnackClock”, this device uses a 24-hour clock movement to rotate a dispenser wheel one revolution per day.  The wheel contains 12 compartments, which allows the device to dispense 12 pre-measured “snacks” at regular 2 hour intervals.  The Kravitz lab has used this device to dispense high-fat diet throughout the day, rather than giving mice one big piece once per day.  The device is very simple to build and use, requiring just two 3D printed parts and a ~$10 clock movement.  There is no microcontroller or coding required for this device, and it runs on one AA battery for >1 year.  The 3D files are supplied and can be edited to fit SnackClock in different brands of caging, or to adjust the number of snack compartments.  With additional effort the clock movement could be replaced by a stepper motor to allow for dispensing at irregular or less frequent intervals.

https://kravitzlab.github.io/SnackClock

 

Article in Nature on monitoring behavior in rodents

An interesting summary of recent methods for monitoring behavior in rodents was published this week in Nature.The article mentions Lex Kravitz and his lab’s efforts on the Feeding Experimentation Device (FED) and also OpenBehavior. Check it out:  https://www.nature.com/articles/d41586-018-02403-5

DIY Rodent Running Disk

February 6, 2018 

Brian Isett, who is now at Carnegie Mellon, has kindly shared the following tutorial regarding the creation and implementation of a Rodent Running Disk he designed while at University of California, Berkeley.


“Awake, naturalistic behavior is the gold standard for many neuroscience experiments.  Increasingly, researchers using the mouse model system strive to achieve this standard while also having more control than a freely moving animal. Using head-fixation, a mouse can be positioned very precisely relative to ongoing stimuli, but often at the cost of naturalism. One way to overcome this problem is to use the natural running of the mouse to control stimulus presentation in a closed-loop “virtual navigation” environment. This combination allows for awake, naturalistic behavior, with the added control of head-fixation. A key element of this paradigm is to have a very fast way of decoding mouse locomotion.
In this tutorial, we describe using an acrylic disk mounted to an optical encoder to achieve fast locomotion decoding. Using an Arduino to decode the TTL pulses coming from the optical encoder, real-time, closed-loop stimuli can be easily presented to a head-fixed mouse. This ultimately allowed us to present tactile gratings to a mouse performing a whisker-mediated texture discrimination task as a “virtual foraging task” — tactile stimuli moved past the whiskers synchronously with mouse locomotion. But the design is equally useful for measuring mouse running position and speed in a very precise way.”

The tutorial may be found here.


Isett, B.R., Feasel, S.H., Lane, M.A., and Feldman, D.E. (2018). Slip-Based Coding of Local Shape and Texture in Mouse S1. Neuron 97, 418–433.e5.

MAPLE: a Modular Automated Platform for Large-Scale Experiments

January 8th, 2018 
The de Bivort lab and FlySorter, LLC are happy to share on OpenBehavior their open-source Drosophila handling platform, called MAPLE: Modular Automated Platform for Large-Scale Experiments.

Drosophila Melanogaster has proven a valuable genetic model organism due to the species’ rapid reproduction, low-maintenance, and extensive genetic documentation. However, the tedious chore of handling and manually phenotyping remains a limitation with regards to data collection. MAPLE: a Modular Automated Platform for Large-Scale Experiments provides a solution to this limitation.

MAPLE is a Drosophila-handing robot that boasts a modular design, allowing the platform to both automate diverse phenotyping assays and aid with lab chores (e.g., collecting virgin female flies). MAPLE permits a small-part manipulator, a USB digital camera, and a fly manipulator to work simultaneously over a platform of flies. Failsafe mechanisms allow users to leave MAPLE unattended without risking damage to MAPLE or the modules.

The physical platform integrates phenotyping and animal husbandry to allow end-to-end experimental protocols. MAPLE features a large, physically-open workspace for user convenience. The sides, top, and bottom are made of clear acrylic to allow optical phenotyping at all time points other than when the end-effector carriages are above the modules. Finally, the low cost and scalability allow large-scale experiments ($3500 vs hundreds of thousands for a “fly-flipping” robot).

MAPLE’s utility and versatility were demonstrated through the execution of two tasks: collection of virgin female flies, and a large-scale longitudinal measurement of fly social networks and behavior.

Links to materials:

CAD files

Control Software

Raw data and analysis scripts 

De Bivort Lab Site 


 

ArControl: Arduino Control Platform

January 3rd, 2018

The following behavioral platform was developed and published by Xinfeng Chen and Haohong Li, from Huazhong University of Science and Technology, Wuhan, China


ArControl: Arduino Control Platform is a comprehensive behavioral platform developed to deliver stimuli and monitor responses. This easy-to-use, high-performance system uses an Arduino UNO board and a simple drive circuit along with a stand-along GUI application. Experimental data is automatically recorded with the built-in data acquisition function and the entire behavioral schedule is stored within the Arduino chip. Collectively, this makes ArControl a “genuine, real-time system with high temporal resolution”. Chen and Li have tested ArControl using a Go/No-Go task and a probabilistic switching behavior task. The results of their work show that ArControl is a reliable system for behavioral research.

Source codes and PCB drafts may be found here: ArControl Github

 

 

Airtrack

November 28, 2017

Airtrack was developed in LARKUM Lab by Mostafa Nashaat, Hatem Oraby, Robert Sachdev, York Winter and Matthew Larkum. Alexander Schill, engineer at Charité workshop (CWW) had a significant contribution to the design of the platform and the airtrack table.


Airtrack is a head-fixed behavioral environment that uses a lightweight physical maze floating on an air table that moves around the animal’s body under the direct control of the animal itself, solving many problems associated with using virtual reality for head-fixed animals.

Illustrative Image of the Airtrack


More Information can be found at http://www.neuro-airtrack.com/

Nashaat, MA, Oraby, H, Sachdev, RNS, Winter, Y, Larkum, ME. (2016).
Air-Track: a real-world floating environment for active sensing in head-fixed mice.
Journal of Neurophysiology 116 (4) 1542-1553; DOI:10.1152/jn.00088.2016

Autonomous Training of a Forelimb Motor Task

November 3, 2017

Greg Silas, from the University of Ottawa, has kindly contributed the following to OpenBehavior.


“Silasi et al developed a low-cost system for fully autonomous training of group housed mice on a forelimb motor task. We demonstrate the feasibility of tracking both end-point as well as kinematic performance of individual mice, each performing thousands of trials over 2.5 months. The task is run and controlled by a Raspberry Pi microcomputer, which allows for cages to be monitored remotely through an active internet connection.”

Click here to submit a piece of open-source software or hardware to OpenBehavior.

Moving Wall Box (MWB)

October 26th, 2017

Andreas Genewsky, from the Max-Planck Institute of Psychiatry, has generously shared the following regarding his Moving Wall Box task and associated apparatus.


“Typicallly, behavioral paradigms which aim to asses active vs. passive fear responses, involve the repeated application of noxius stimuli like electric foot shocks (step-down avoidance, step-through avoidance, shuttle-box). Alternative methods to motivate the animals and ultimately induce a conflict situation which needs to be overcome often involve food and/or water deprivation.

In order to repeatedly assess fear coping strategies in an emotional challenging situation without footshocks, food or water deprivation (comlying to the Reduce & Refine & Replace 3R principles), we devised a novel testing strategy, henceforward called the Moving Wall Box (MWB) task. In short, during the MWB task a mouse is repeatedly forced to jump over a small ice-filled box (10 trials, 1 min inter-trial intervals ITI), by slowly moving walls (2.3 mm/s, over 60 s), whereby the presence of the animal is automatically sensed via balances and analyzed by a microcontroller board which in turn controls the movements of the walls. The behavioral readouts are (1) the latency to reach the other compartment (high levels of behavioral inhibition lead to high latencies) and (2) the number of inter-trial shuttles per trial (low levels of behavioral inhibition lead to high levels of shuttles during the ITI).

The MWB offers the possibility to conduct simultaneous in vivo electrophysiological recordings, which could be later aligned to the behavioral responses (escapes). Therefore the MWB task fosters the study of activity patterns in, e.g., optogenetically identified neurons with respect to escape responses in a highly controlled setting. To our knowledge there is no other available compatible behavioral paradigm.”