Head-restrained device comparison!

Good surgery techniques and head-fixation methods allow us to perform in vivo multiphoton or electrophysiological recording. Most of these methods try to go beyond the awakeness of the mice and the fact that the whole brain can be investigated in an intact form. Stronger conclusions can be taken if mice can perform a leaned task during the measurements. 

Most researchers in this field have seen and used a variety of different head-fixed tools for in-vivo mice experiments so we thought it would be beneficial for everyone to have an overview of the commercially available devices. We also need to note that DIY solutions exist all around the world, of which some are well documented and accessible to the public.

Green color code indicates our opinion, we would choose it in the given category.

These are the commercially available out-of-box solutions, but if we read publications about in-vivo head-restrained behavioral experiments we can see the majority of these devices are home-build solutions. They are cheaper but only if the laboratory has the expertise in building these devices or can easily understand and has access to DIY  protocols. Still, it usually takes time to train the animals and become familiar with the behavioral input and output data; therefore many people would rather invest some funding to have turn-key solutions and support for their device.

Here is one of the most well-documented home-built solutions from outstanding Lee lab   for understanding the tasks and the difficulties a lab needs to manage if it would develop its own solution:

Natural Whisker-Guided Behavior by Head-Fixed Mice in Tactile Virtual Reality

Nicholas J. Sofroniew, Jeremy D. Cohen, Albert K. Lee and Karel Svoboda :

„SPHERICAL TREADMILL.

The spherical treadmill was a 15.56 inch diameter hollow Smoothfoam ball (Plasteel; 16 inch diameter, Ball no. 183). Balls were purchased as hollow halves with an initial wall thickness of 19.5 ± 0.2 mm and weight of 121.3 ± 0.5 g. The inside of the halves was carved with a hot wire system (Hot Wire Foam Factory) to give a wall thickness of 3.79 ± 0.66 mm. Two matched halves were glued together with expanded polystyrene foam glue (Hot Wire Foam Factory; Foam Glue, no. 028B-8). The total weight of the ball was 82.5 g. The ball was supported by 10 Ping-Pong balls (JOOLA Gold 3-Star 40 mm) in air cannons. Each air cannon consisted of a 1.577 inch diameter acrylic tube plugged at one end with an acetyl resin base plate containing a tube fitting (McMaster Carr, no. 50745K15) for air flow. The air cannons were clamped at regular intervals around the ball in a custom 19 inch diameter acrylic ribbed bowl. One cannon was located under the bottom of the ball, three cannons were located in a ring at a latitude of 60° S, and six were located in a ring at a latitude of 20° S. The airflow to the bottom cannon, the ring of cannons at 60°S, and two groups of three cannons at 20° S was controlled independently with regulators (McMaster Carr, nos. 3846K29 and 5627K511).

BALL TRACKING.

Rotation of the ball was tracked using two cameras containing chips that measure optic flow (Avago Technologies, ADNS-6090) with a serial interface to a microcontroller (Atmel, ATMega644p; Seelig et al., 2010). The cameras were mounted on the ribbed bowl around the equator of the ball, 45 mm from the ball surface. One camera was directly in front of the mouse, and one was on the right. The surface of the ball in front of each camera was illuminated using a 940 nm IR LED (Roithner, ELJ-940-629). Each camera imaged a 2.2 × 2.2 mm² field of view onto a 30 × 30 pixel sensor with a lens (focal length 25 mm; Computar) and a 10 mm extension tube. The microcontroller interfaced with a PC running MATLAB via serial communication and provided shutter time (inverse of light level) and contrast metrics. These parameters were used to focus the lenses and adjust the illumination during initial setup. For tracking ball motion, every 2 ms the microcontroller received two signed integers measuring the optic flow Δ_x and Δ_y from each camera. These signals were converted to analog voltages ranging from 0 to 5 V, centered on 2.5 V, with 150 mV resolution. The microcontroller also provided a clock signal. The RTLinux was triggered by the clock signal to read and rediscretize the analog values of the optic flow. The vector of camera motion displacement signals was transformed to a vector of ball motion v_ball by multiplication with a calibration matrix A_calib, v_ball = A_calib × [Δ_x1, Δ_y1, Δ_x2, Δ_y2]′.

BALL ROTATION CALIBRATION.

To determine A_calib, the rotation of the ball was recorded independently of the ball tracking system using a high-speed (500 Hz) camera (Mikrotron MC1362). The field-of-view was 11 × 11 mm² (27 pixels per mm). The camera was focused on the surface of the top of the ball, where the head of the mouse would be. Each video image was corrected for uneven illumination. For each frame, the forward and sideways rotation of the ball was computed from the x and y displacements that gave the peak cross-correlation with the next frame. A_calib was determined by least squares fitting a linear transformation from the camera-motion displacement signals to the recorded forward and sideways rotation of the ball. The predicted ball motion and actual ball motion had a correlation coefficient of 0.97. Thus, the real-time tracking system provided a high bandwidth and accurate measurement of ball motion.”

This device’s design and all its parameter are freely accessible on this link:  https://hhmi.flintbox.com/#technologies/f5aec3e3-2995-47f6-8950-35b20a12039b

Thanks to Lee Lab and Janelia Experimental Technology.

Some other good publications:

Close alternative solution for JetBall by Phenosys published:

Natural Whisker-Guided Behavior by Head-Fixed Mice in Tactile Virtual Reality. Nicholas J. Sofroniew, Jeremy D. Cohen, Albert K. Lee, and Karel Svoboda doi: 10.1523/JNEUROSCI.0712-14.2014

Close alternative solution for MobileHomeCage by Neurotar published :

Air-Track: A Real-World Floating Environment for Active Sensing in Head-Fixed Mice Mostafa A Nashaat 1, Hatem Oraby 2, Robert N S Sachdev 2, York Winter 2, Matthew E Larkum 3 DOI: 10.1152/jn.00088.2016

Close alternative solution for Gramophone by Femtonics published :  

Inferring Cortical Function in the Mouse Visual System Through Large-Scale Systems Neuroscience. Michael Hawrylycz 1, Costas Anastassiou 2, Anton Arkhipov 2, Jim Berg 2, Michael Buice 2, Nicholas Cain 2, Nathan W Gouwens 2, Sergey Gratiy 2, Ramakrishnan Iyer 2, Jung Hoon Lee 2, Stefan Mihalas 2, Catalin Mitelut 2, Shawn Olsen 2, R Clay Reid 2, Corinne Teeter 2, Saskia de Vries 2, Jack Waters 2, Hongkui Zeng 2, Christof Koch 1, MindScope DOI: 10.1073/pnas.1512901113

A close alternative solution for Linear treadmill by Phenosys or Luigs and Neumann

Control of Timing, Rate and Bursts of Hippocampal Place Cells by Dendritic and Somatic Inhibition Sébastien Royer 1, Boris V Zemelman, Attila Losonczy, Jinhyun Kim, Frances Chance, Jeffrey C Magee, György Buzsáki DOI: 10.1038/nn.3077

Resources:      

1. https://www.neurotar.com/

2. https://www.phenosys.com/

3. https://femtonics.eu/

4. https://www.luigs-neumann.com/

5. Natural Whisker-Guided Behavior by Head-Fixed Mice in Tactile Virtual Reality
    Nicholas J. Sofroniew, Jeremy D. Cohen, Albert K. Lee and Karel Svoboda 
   Journal of Neuroscience 16 July 2014, 34 (29) 9537-9550; DOI: https://doi.org/10.1523/JNEUROSCI.0712-14.2014

6. https://www.janelia.org/open-science/large-spherical-treadmill-rodents