July 16, 2018
In a special issue of Journal of Neural Engineering, Dominique Martinez and colleagues their share design for NeRD, an open source neural recording device for wireless transmission of local field potential (LFP) data in in freely-behaving animals.
Electrophysiological recording of local field potentials in freely-behaving animals is a prominent tool used by researchers for assessing the neural basis of behavior. When performing these recordings, cables are commonly used to transmit data to the recording equipment, which tethers the animals and can interfere with natural behavior. Wireless transmission of LFP data has the advantage of removing the cable between the animal and the recording equipment, but is hampered by the large number of data to be transmitted at a relatively high rate.
To reduce transmission bandwidth, Martinez et al. propose an encoder/decoder algorithm based on adaptive non-uniform quantization. As proof-of- concept, they developed a NeRD prototype that digitally transmits eight channels encoded at 10 kHz with 2 bits per sample. This lightweight device occupies a small volume and is powered with a small battery allowing for 2h 40min of autonomy. The power dissipation is 59.4 mW for a communication range of 8 m and transmission losses below 0.1%. The small weight and low power consumption offer the possibility of mounting the entire device on the head of a rodent without resorting to a separate head-stage and battery backpack. The use of adaptive quantization in the wireless transmitting neural implant allows for lower transmission bandwidths, preservation of high signal fidelity, and preservation of fundamental frequencies in LFPs from a compact and lightweight device.
Martinez, D., Clément, M., Messaoudi, B., Gervasoni, D., Litaudon, P., & Buonviso, N. (2018). Adaptive quantization of local field potentials for wireless implants in freely moving animals: An open-source neural recording device. Journal of Neural Engineering, 15(2), 025001. doi:10.1088/1741-2552/aaa041
July 2, 2018
In Current Protocols in Neuroscience, Alexander Jacob and colleagues share their open source compact head-mounted endoscope (CHEndoscope) for imaging in the awake behaving mouse.
This miniature microscope device is designed to provide an accessible set of calcium imaging tools to investigate the relationship between behavior and population neuronal activity for in vivo rodents. The CHEndoscope is open source, flexible, and consists of only 4 plastic components that can be 3D printed. It uses an implanted gradient index (GRIN) lens in conjunction with the genetically encoded calcium indicator GCaMP6 to image calcium transients from hundreds of neurons simultaneously in awake behaving mice. The aim of the open source model is to provide an accessible and flexible set of calcium imaging tools for the neuroscience research community. The linked article describes in depth the assembly, surgical implantation, data collection, and processing of calcium signals using the CHEndoscope.
Link to paper: https://currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/cpns.51
Jacob, A. D., Ramsaran, A. I., Mocle, A. J., Tran, L. M., Yan, C., Frankland, P. W., & Josselyn, S. A. (2018). A compact head‐mounted endoscope for in vivo calcium imaging in freely behaving mice. Current Protocols in Neuroscience, 84, e51. doi: 10.1002/cpns.51
June 25, 2018
Andreas Genewsky and colleagues from the Max Planck Institute of Psychiatry have shared the design, construction and validation of a simplified, low-cost, radar-based motion detector for home cage activity monitoring in mice. This simple, open-source device allows for motion detection without visual contact to the animal and can be used with various cage types. It features a custom printed circuit board and motion detector shield for Arduino, which saves raw activity and timestamped data in CSV files onto an SD card; the authors also provide a Python script for data analysis and generation of actograms. This device offers a cost-effective, DIY alternative to optical imaging of home-cage activity.
Read more from the Journal of Biomedical Engineering publication!
Genewsky, A., Heinz, D. E., Kaplick, P. M., Kilonzo, K., & Wotjak, C. T. (2017). A simplified microwave-based motion detector for home cage activity monitoring in mice. Journal of Biological Engineering,11(1). doi:10.1186/s13036-017-0079-y
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
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.
April 2, 2018
Check out the Ethoscopes platform!
Ethoscopes enable high-throughput analysis of behavior in Drosophila and other animals for <$100. The system is capable of real-time video tracking, is based on raspberry pi, and even has its own R package for data analysis. All software and build specifications are available at http://lab.gilest.ro/ethoscope.
March 8, 2018
Robyn A. Grant, from Manchester Metropolitan University, has shared the following on Twitter regarding the development of the LocoWhisk arena:
“Come help me develop my new arena. Happy to hear from anyone looking to test it or help me develop it further.”
The LocoWhisk system is a new, portable behavioural set-up that incorporates both gait analysis (using a pedobarograph) and whisker movements (using high-speed video camera and infrared light source). The system has so far been successfully piloted on many rodent models, and would benefit from further validation and commercialisation opportunities.
Learn more here: https://crackit.org.uk/locowhisk-quantifying-rodent-exploration-and-locomotion-behaviours
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
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.
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