Gait Analysis of Age-dependent Motor Impairments in Mice with Neurodegeneration

This method can help answering key questions in the Aging and Neurodegeneration Research such as the onset and progression of gait and motor abnormalities with age and in particular, in mouse models of neurodegenerative diseases. The result of such status can be translated to a much better understanding of motor impairments in patients with neurodegenerative diseases for example, Parkinson's Disease or ataxias. The main advantage of using video based gait analysis is that it allows studying both subtle and severe motor impairments in mouse models of neurodegeneration.

Begin by determining the health status of each animal by examining it closely and weighting it on a balance. Gently apply red finger paint to the animal's paws with a brush. Place the animal in a spare, clean cage while the paint dries.

Next, set the speed of the treadmill on the top right panel of the apparatus. Then, place the animal in the test chamber and cover it with a dark cloth to allow each animal to adjust for one to two minutes. Turn on the light in the test chamber by turning the treadmill light rotary switch to the on position.

Open the cover a little bit so that you can observe the animal during the task. Start the treadmill for about half a second to warn the animal that the task is about to begin. Turn the treadmill rotary switch to forward to start the treadmill.

Then, click the Record button in the imager software. Once the animal runs in a stable manner, record for at least five seconds before stopping the treadmill. Stop the recording by clicking Stop on the imager software and turn the treadmill rotary switch back to the off position.

Next, click the Edit button in the imager software to open a menu in which the start and end point of the video section can be set. Navigate through the video using the slider on the bottom of the screen. To select the current time point as the start or end point, click From Frame Number and To, respectively.

Make sure the section contains at least seven steps per paw or fourteen steps in total of the animal running stably at a constant speed. Finally, enter the animal identification, birthdate, weight, and sex. Save the data on a desired location on the computer or server.

The principle of video based gait analysis is to measure the paw area in contact with the surface over time for each individual paw. Many gait dynamics and posture parameters can be extracted from the recorded videos, for example, the swing time, stance time and width, stride length, and frequency. Other gait features such as ataxia coefficient or step angle variability can then be calculated from the primary measurements.

Begin the video analysis by starting the analysis software and clicking Select Study Folder to select the folder with the recorded videos. Select one video and click Go.Use the re-draw function to select the area where the mouse is running. Note, this section should only contain the mouse and white background.

Next, enter values in the length and width boxes to change the mask that excludes the red area around the snout of the animal for analysis. Adjust the sliders filter noise and filter fur and dark patches to optimize the black and white paw print. Set the filter noise slider to 800 to 950 for black animals and to 700 to 800 for brown or white animals, depending on the exact fur color of the animal, and select Okay.

Then select a video that passed the first adjustment and select the Go function to start the analysis of the video. Next, select an analyzed video and click Go.Note that the paw print area in contact with the belt over time for each separate paw, can now be seen. To compare the original video and the calculated paw print for the selected area, select the Play Video function.

To correct small mistakes, use either the Correct, Connect, or Delete option. Use the Correct option to delete a wrong signal. Click once to zoom into the relevant area and mark the left border of the object to remove with a second click and the right border with the third click.

Use the Connect option to combine two signals. Click once to zoom into the relevant area and double click in the middle of the two objects to combine. Use the Delete option to remove time points from the analysis completely.

Click once to zoom into the relevant area and mark the left border of the area to remove with the second click and the right border with the third click. Then select Next Limb to proceed through the four limbs. Note, after Next Limb is clicked after the last paw, the software completes the analysis and shows the results for the animal on four screens.

Finally, after all videos from one experiment are analyzed, select all videos and click Reorganize Results to export the results. About 50 gait parameters are calculated and listed in the exported file. Sort the result by group, age, and running speed, and analyze all these conditions independently.

In the gait analysis in wild type mice with advancing age, results indicated that the stance with normalized animal width does not change with advancing age. However, hind limb double support and limb loading do increase with age in wild type animals. Furthermore, while all tested animals can run at 30 meters per second at one month, the endophilin mutants develop running deficits as they age.

Additionally, gait rhythm is impaired in endophilin mutants. For example, the propel time decreases in the endophilin mutants as the mice age. When attempting the procedure, it's important to remember that the most critical step is the recording of the original video.

All further analysis depends on good quality videos. Gait analysis is a useful method to categorize gait and motor behavior in mouse models of neurodegeneration. However, some aspects of motor behavior, for example, muscle strength, are not adequately assessed by this method.

But therefore a command complimenting video based gait analysis with a battery of other motor behavior tests, like grip strength, and beam walking. After watching this video, you should have a good understanding of how to perform gait analysis in mouse models that develop motor impairment with aging.