Abstract
A method for capturing gait signatures in neurological conditions that allows comparison of human gait with animal models would be of great value in translational research. However, the velocity dependence of gait parameters and differences between quadruped and biped gait have made this comparison challenging. Here we present an approach that accounts for changes in velocity during walking and allows for translation across species. In mice, we represented spatial and temporal gait parameters as a function of velocity and established regression models that reproducibly capture the signatures of these relationships during walking. In experimental parkinsonism models, regression curves representing these relationships shifted from baseline, implicating changes in gait signatures, but with marked differences between models. Gait parameters in healthy human subjects followed similar strict velocity dependent relationships which were altered in Parkinson’s patients in ways that resemble some but not all mouse models. This novel approach is suitable to quantify qualitative walking abnormalities related to CNS circuit dysfunction across species, identify appropriate animal models, and it provides important translational opportunities.
Highlights
Walking is a complex behavior that requires control of initiation and termination of locomotion, and ongoing adjustments of speed, stride length, cadence, direction, and posture in response to dynamic internal and external cues
Spatial and temporal gait parameters obtained on the 2 runways differed markedly (Fig. 1c), with stride length, swing duration, cadence and swing velocity being larger or longer and swing duration being shorter on the larger runway
These differences are due to the unique velocity dependent relationships of each of the gait parameters, which only become visible when plotting the stride-tostride data for each of the gait parameters as a function of gait velocity (Fig. 1d)
Summary
Walking is a complex behavior that requires control of initiation and termination of locomotion, and ongoing adjustments of speed, stride length, cadence, direction, and posture in response to dynamic internal and external cues. The functional-anatomical basis for the various gait abnormalities so readily recognized in clinical settings remains poorly understood as approaches to isolate relevant networks during life are relatively limited. This gap in knowledge stands in the way of the development of specific, circuit based treatment strategies targeted to the various specific gait abnormalities. Our results demonstrate a rigorous mathematical analysis model of walking that can allow comparison of animal models of gait disorders with human disease This opens the way for translational approaches to study the circuitry that underlies those abnormal gaits and find ways to correct them
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