Mouse locomotion is a complex biological process that provides scientists with profound insights into overall health. Analyzing the specific patterns of a mouse’s walk, or its gait, offers a quantifiable measure of neurological and musculoskeletal function. Because mice share many genetic and physiological similarities with humans, studying their movement is a powerful method for understanding and modeling various human diseases. Gait analysis transforms simple movement into measurable data, effectively turning the mouse’s walk into a functional biomarker for health and disease.
The Basic Biomechanics of Mouse Walking
Mouse locomotion is quadrupedal. The animal maintains a semi-plantigrade posture, walking with a portion of its foot and toes contacting the ground, which balances speed and stability. At lower speeds, the mouse typically employs an out-of-phase walk, where limbs are placed sequentially to maintain continuous ground contact. As the animal accelerates to intermediate speeds, it often transitions to a trot, a symmetrical gait where diagonally opposite limbs move together, such as the left front and right hind paw.
At higher speeds, mice transition to running gaits like the gallop or full-bound, which involve periods where all four paws are off the ground simultaneously. The gait cycle is split into two primary phases for each limb: the stance phase, when the paw is in contact with the ground and bearing weight, and the swing phase, when the paw is lifted and advanced forward. The duration of the stance phase becomes significantly shorter as the pace increases.
The tail acts as a dynamic stabilizer, especially when the animal is navigating unstable or narrow surfaces. When a mouse moves, its tail performs oscillations that are phase-locked to the step cycle, helping to counteract rotational forces and maintain equilibrium. The tail generates angular momentum to mitigate undesired body roll.
Techniques for Analyzing Mouse Gait
Researchers rely on advanced, automated systems to quantify the subtle features of mouse gait, moving beyond older methods like dipping paws in ink to collect static footprints. One common method utilizes pressure-sensitive walkways or glass-floor systems, which capture the precise moment and intensity of each paw’s contact with the surface. These systems use internal reflection technology and high-speed cameras positioned underneath the walkway to create digital paw prints with high spatial and temporal resolution. Another sophisticated approach uses ventral plane videography, often with a transparent treadmill, to capture the dynamic motion of the limbs from below while the mouse walks at a controlled speed.
These technologies allow for the measurement of numerous specific parameters impossible to quantify through visual observation alone. Parameters measured include:
- Stride length, the distance between successive placements of the same paw.
- Base of support, the width between the left and right paw placements.
- Stance time and swing time.
- Duty cycle, the percentage of the gait cycle that a paw is on the ground.
- Paw pressure distribution, providing a proxy for the force exerted by each limb, which is a sensitive indicator of pain or weakness.
These precise, objective measurements are necessary because they allow for the detection of minute, often subclinical, changes in movement that signal underlying physiological issues.
Gait Analysis as a Research Tool
The quantitative data derived from gait analysis systems serves as a powerful biomarker to track the progression of various diseases in mouse models. Neurological disorders, which often affect motor control, produce distinct and measurable changes in walking patterns. For example, mouse models of Parkinson’s disease show significant gait disturbances, including shortened stride length and increased stride-to-stride variability. Similarly, models for Huntington’s disease exhibit failure in hindlimb coordination, with increased variability in forelimb stride.
Changes in gait parameters are also used to monitor the effectiveness of new drug therapies or genetic interventions. Researchers can measure if the treatment restores parameters like stride length or interlimb coordination toward normal levels. For conditions such as Charcot-Marie-Tooth disease, a peripheral neuropathy, gait analysis can reveal a wider step width and abnormal joint angles, such as altered ankle dorsiflexion. This ability to dynamically reflect disease state and progression makes gait analysis a non-invasive tool for preclinical studies.