Researchers use different ways to analyze gait in animals. Basically we can distinguish two methods: one can either observe or measure gait in an unrestricted manner, or one chooses a forced manner, such as a treadmill or treadwheel.
The cerebellum, our “little brain”, is all about motor control; more specifically, it’s about coordination, precision, and timing. So when the functioning of the cerebellum is compromised, incoordination of movement (ataxia) occurs. Ataxia is found in many neurological diseases such as Parkinson’s and early onset Alzheimer’s.
Cerebellar cell types functioning
Purkinje cells, interneurons, and granule cells of the cerebellar cortex play an important role in reflexive types of motor learning, as we can tell from studies using the eye blink test and vestibulo-ocular testing. But since their role in more complex behaviors is not well understood, Maria Fernanda Vinueza Veloz and her colleagues decided to study the role of each one of these cell types in motor learning, locomotor adaptation, motivation and avoidance behavior using several knock-out mouse strains and testing them on the ErasmusLadder.
In my last two blogs, I wrote about static gait parameters. Specifically, what a single footprint can tell you and what kind of information you can get from the distance relationships between prints. Now it’s time to talk about all four paws, and the time based relationships between them. If you ask me, we’ve been saving the best blog for last!
Temporal relations are the parameters that have to do with time, such as timing and duration. This is where automation of gait research shows it true colors.
Parameters that describe the relation and distances between footfalls.
Last week I wrote about the value of a print. A footprint, that is. With CatWalk XT, you can extract a lot of information from just one footprint. In this post, I am taking it a step further by talking about the relationship between prints.
In the study of many different disorders that affect the nervous system, muscles, or bones, it is important to know how the animal walks. Does it have a regular gait, following a normal pattern of footsteps? Or can we detect a lack of coordination, or ataxia? Those are important behavioral observations in many studies. So how can you detect them: by looking at the relation between prints.
Gait parameters as behavioral endpoints – parameters from a footprint
So here it is – the first blog in a series of three, about rodent gait analysis and what a single footprint can tell us.
Modern systems – better than ink
So what can one footprint tell you? Well, it could tell you a lot. Simply putting the paw in ink and studying the print left behind is one way to go about it, but there are far more sophisticated ways of footprint analysis. While an ink-print can give you an idea of the print area of a foot, you cannot tell how the animal is distributing his weight across its feet. It also cannot tell you the maximum surface area of a foot touching the ground during the duration of the entire footfall. Modern systems can.
Modern systems that use light to detect a footfall can indicate the intensity of a print, which in turn can correlate with how the animal is bearing its weight. In models of conditions that affect a single limb, the animal often shows less use of the affected paw. This is reflected in a relatively lower intensity of that footprint, which is found in models of arthritis [8,9] and sciatic nerve injury [1,2,4,10].
The usefulness of gait is well established in research on spinal cord injury, ataxia, and arthritis. But in fact, research on all disorders that influence gait in any way, can benefit from gait and footfall analysis. Gait is an important part of the behavioral repertoire of animals, and detailed gait analysis is a logical endpoint to take into account.