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.Walking is a complex behavior that requires not only control of initiation and termination of locomotion, but also ongoing adjustments of speed, stride length, cadence, direction, and posture in response to dynamic internal and external cues. Walking can be affected in many different ways secondary to musculoskeletal or cardiovascular problems, as well as dysfunction of the peripheral or the central nervous system (CNS). Gait disorders due to specific CNS circuit pathologies can be clinically recognized based upon phenomenology, such as shuffling gait or festination in Parkinson's disease or ataxic gait in cerebellar disorders 1, 2 . The wide variety of causal conditions and subtypes of gait disorders illustrate that abnormal function or pathology in multiple CNS networks differentially affect gait.Human gait can be objectively measured using direct or indirect kinematic, spatial or temporal measures via video-analysis, footfall studies, or wearable devices. Advances in imaging technology have allowed visualization of putative supratentorial circuitries involved in gait control [3][4][5][6][7][8][9] . However, 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.Animal models offer a means to circumvent current barriers of studying gait in humans. In mice, highly selective approaches are now available to identify components of CNS circuits from cortex to spinal cord that mediate or modulate locomotion, including walking 10-13 . Effects of interventions can then be measured u...

Clinical signs in Parkinson’s disease (PD), including parkinsonian gait, are often asymmetric, but mechanisms underlying gait asymmetries in PD remain poorly understood. A translational toolkit, a set of standardized measures to capture gait asymmetries in relevant mouse models and patients, would greatly facilitate research efforts. We validated approaches to quantify asymmetries in placement and timing of limbs in mouse models of parkinsonism and human PD subjects at speeds that are relevant for human walking. In mice, we applied regression analysis to compare left and right gait metrics within a condition. To compare alternation ratios of left and right limbs before and after induction of parkinsonism, we used circular statistics. Both approaches revealed asymmetries in hind- and forelimb step length in a unilateral PD model, but not in bilateral or control models. In human subjects, a similar regression approach showed a step length asymmetry in the PD but not control group. Sub-analysis of cohorts with predominant postural instability-gait impairment and with predominant tremor revealed asymmetries for step length in both cohorts and for swing time only in the former cohort. This translational approach captures asymmetries of gait in mice and patients. Application revealed striking differences between models, and that spatial and temporal asymmetries may occur independently. This approach will be useful to investigate circuit mechanisms underlying the heterogeneity between models.

Walking is a slow gait which is particularly adaptable to meet internal or external needs and is prone to maladaptive alterations that lead to gait disorders. Alterations can affect speed, but also style (the way one walks). While slowed speed may signify the presence of a problem, style represents the hallmark essential for clinical classification of gait disorders. However, it has been challenging to objectively capture key stylistic features while uncovering neural substrates driving these features. Here we revealed brainstem hotspots that drive strikingly different walking styles by employing an unbiased mapping assay that combines quantitative walking signatures with focal, cell type specific activation. We found that activation of inhibitory neurons that mapped to the ventromedial caudal pons induced slow motion-like style. Activation of excitatory neurons that mapped to the ventromedial upper medulla induced shuffle-like style. Contrasting shifts in walking signatures distinguished these styles. Activation of inhibitory and excitatory neurons outside these territories or of serotonergic neurons modulated walking speed, but without walking signature shifts. Consistent with their contrasting modulatory actions, hotspots for slow-motion and shuffle-like gaits preferentially innervated different substrates. These findings lay the basis for new avenues to study mechanisms underlying (mal)adaptive walking styles and gait disorders.