Category: All

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

 

 

StimDuino

December 20, 2017

StimDuino, an inexpensive Arduino-controlled stimulus isolator that allows for highly accurate, reproducible automated setting of stimulation currents. The automatic stimulation patterns are software-controlled and the parameters are set from Matlab-coded simple, intuitive and user-friendly graphical user interface. StimDuino-generated automation of the input-output relationship assessment eliminates need for the current intensity manually adjusting, improves stimulation reproducibility, accuracy and allows on-site and remote control of the stimulation parameters for both in vivo and in vitro applications.


Sheinin, A., Lavi, A., & Michaelevski, I. (2015). StimDuino: An Arduino-based electrophysiological stimulus isolator. Journal of Neuroscience Methods, 243, 8-17. doi:10.1016/j.jneumeth.2015.01.016

ZebraTrack

December 18, 2017

ZebraTrack is a cost-effective imaging setup for distraction-free behavioral acquisition with automated tracking using open-source ImageJ software and workflow for extraction of behavioral endpoints of zebrafish. This ImageJ algorithm is capable of providing control to users at key steps while maintaining automation in tracking without the need for the installation of external plugins.


Nema, S., Hasan, W., Bhargava, A., & Bhargava, Y. (2016). A novel method for automated tracking and quantification of adult zebrafish behaviour during anxiety. Journal of Neuroscience Methods, 271, 65-75. doi:10.1016/j.jneumeth.2016.07.004

 

Pyper

November 28, 2017

Pyper is developed by The Margrie Laboratory.


Pyper provides real-time or pre-recorded motion tracking of a specimen in an open-field. Pyper can send TTL pulses based on detection of the specimen within user-defined regions of interest.  The software can be used through the command line or through a built-in graphical user interface. The live feed can be provided by a USB or Raspberry Pi camera.

Example of Pyper tracking a mouse in an open field


Find more information here.

Manual for Pyper.

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

3DTracker – 3D video tracking system for animal behavior

November 8th, 2017

Jumpei Matsumoto has submitted the following to OpenBehavior regarding 3D tracker, a 3D video tracking system for animal behavior.


3DTracker-FAB is an open source software for 3D-video based markerless computerized behavioral analysis for laboratory animals (currently mice and rats). The software uses multiple depth cameras to reconstruct full 3D images of animals and fit skeletal models to the 3D image to estimate 3D pose of the animals.


More information on 3D tracker may be found on the system’s website, www.3dtracker.org

Additionally, a dynamic poster on the system was presented on November 12, 2017 at the Society for Neuroscience annual meeting. Click here for more information.

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.