The video provides instructions for assembling and customizing a MouseWalker Apparatus for experiments. It details setting up a high-speed camera with appropriate lighting conditions to capture FTIR signals, including adjusting light intensity and positioning the camera lens for optimal focus on the apparatus's plexiglass surface.

setting up of the mousewalker (mw) apparatus

Cuantificación de la disfunción locomotora en ratones con lesión medular utilizando MouseWalker

The effective coordination of four limbs is not unique to quadruped animals. Forelimb-hindlimb coordination in humans remains important to accomplish several tasks, such as swimming and alterations of speed while walking1. Various limb kinematic2 and motor program1,3,4, as well as proprioceptive feedback circuits5, are conserved between humans and other mammals&#160;and should be considered when analyzing therapeutic options for motor disorders, such as spinal cord injury (SCI)6,7,8.
In order to walk, several spinal connections from the forelimbs and hindlimbs need to be properly wired and rhythmically activated, which requires inputs from the brain and feedback from the somatosensory system2,9,10. These connections culminate in the central pattern generators (CPGs), which are situated at a cervical and lumbar level for the forelimbs and hindlimbs, respectively1,9,10. Often, after SCI, the disruption of neuronal connectivity and the formation of an inhibitory glial scar12 limit the recovery of locomotor function, with outcomes varying from total paralysis to restricted function of a group of limbs depending on the injury severity. Tools to precisely quantify locomotor function after SCI are critical for monitoring recovery and evaluating the effects of treatments or other clinical interventions6.
The standard metric assay for mouse contusion models of SCI is the Basso mouse scale (BMS)13,14, a non-parametric score that considers trunk stability, tail position, plantar stepping, and forelimb-hindlimb coordination in an open field arena. Even though the BMS is extremely reliable for most cases, it requires at least two experienced raters to observe all the angles of animal movement in order to account for natural variability and reduce bias.
Other assays have also been developed to assess motor performance after SCI quantitatively. These include the rotarod test, which measures time spent on a rotating cylinder15; the horizontal ladder, which measures the number of missed railings and positive ladder grabs16,17; and the beam walking test, which measures the time an animal takes and the number of failures it makes when crossing a narrow beam18. Despite reflecting a combination of motor deficits, none of these tests produce direct locomotor information about forelimb-hindlimb coordination.
To specifically and more thoroughly analyze walking behavior, other assays have been developed to reconstruct step cycles and gaiting strategies. One example is the footprint test, where the inked paws of an animal draw a pattern over a sheet of white paper19. Although simple in its execution, extracting kinematic parameters such as stride length is cumbersome and inaccurate. Moreover, the lack of dynamic parameters, such as the duration of the step cycle or leg-timed coordination, limits its applications; indeed, these dynamic parameters can only be acquired by analyzing frame-by-frame videos of rodents walking through a transparent surface. For SCI studies, researchers have analyzed walking behavior from a lateral view using a treadmill, including reconstructing the step cycle and measuring the angular variations of each leg joint4,20,21. Even though this approach can be extremely informative6, it remains focused on a specific set of limbs and lacks additional gait features, such as coordination.
To fill these gaps, Hamers and colleagues developed a quantitative test based on an optical touch sensor using frustrated total internal reflection (fTIR)22. In this method, light propagates through glass via internal reflection, becomes scattered upon paw pressing, and, finally, is captured by a high-speed camera. More recently, an open-source version of this method, called MouseWalker, was made available, and this approach combines an fTIR walkway with a tracking and quantification software package23. Using this method, the user can extract a large set of quantitative parameters, including step, spatial, and gait patterns, footprint positioning, and forelimb-hindlimb coordination, as well as visual outputs, such as footprint patterns (mimicking the inked paw assay6) or stance phases relative to the body axis. Importantly, due to its open-source nature, new parameters can be extracted by updating the MATLAB script package.
Here, the previously published assembly of the MouseWalker23 system is updated. A description of how to set it up is provided, with all the steps required to achieve the best video quality, tracking conditions, and parameter acquisition. Additional post-quantification tools are also shared to enhance the analysis of the MouseWalker (MW) output dataset. Finally, the usefulness of this tool is demonstrated by obtaining quantifiable values for general locomotor performance, specifically step cycles and forelimb-hindlimb coordination, in a spinal cord injury (SCI) context.

Autor destacado: Uso del MouseWalker para cuantificar la disfunción locomotora en un modelo de ratón de lesión de la médula espinal  

Uso del MouseWalker para cuantificar la disfunción locomotora en un modelo de ratón de lesión de la médula espinal

Watch this Scientific Journal Video about Setting Up of the MouseWalker MW Apparatus at JoVE.com

Setting Up of the MouseWalker (MW) Apparatus  

Configuración del aparato MouseWalker (MW)

Comience ensamblando el aparato MouseWalker, como se describe en otra parte, o personalícelo según las necesidades específicas del diseño experimental. Configure la cámara de alta velocidad con una lente rápida y una gran apertura para capturar más luz, lo que ayuda a registrar las señales de reflexión interna total frustrada o FTIR. Con las luces de la habitación apagadas, verifique la intensidad de la luz de fondo y la pasarela.Ajuste la intensidad si es necesario agregando plástico semiopaco o usando un potenciómetro. Coloque la lente correctamente a la misma altura en el centro del espejo reflectante de 45 grados y perpendicular a la pasarela. Ajuste el contraste de imagen de la pasarela reduciendo o aumentando la iluminación.Luego enfoca la lente en la superficie del plexiglás.

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Research

JoVE Journal

Neuroscience

Setting Up of the MouseWalker (MW) Apparatus

238 vistas. Comience ensamblando el aparato MouseWalker, como se describe en otra parte, o personalícelo según las necesidades específicas del diseño experimental. Configure la cámara de alta velocidad con una lente rápida y una gran apertura para capturar más luz, lo que ayuda a registrar las señales de reflexión interna total frustrada o FTIR. Con las luces de la habitación apagadas, verifique la intensidad de la luz de fondo y la pasarela.Ajuste la intensidad si es necesario agregando...

Video: Setting Up of the MouseWalker (MW) Apparatus  

Using the MouseWalker to Quantify Locomotor Dysfunction in a Mouse Model of Spinal Cord Injury

The execution of complex and highly coordinated motor programs, such as walking and running, is dependent on the rhythmic activation of spinal and supra-spinal circuits. After a thoracic spinal cord injury, communication with upstream circuits is impaired. This, in turn, leads to a loss of coordination, with limited recovery potential. Hence, to better evaluate the degree of recovery after the administration of drugs or therapies, there is a necessity for new, more detailed, and accurate tools to quantify gait, limb coordination, and other fine aspects of locomotor behavior in animal models of spinal cord injury. Several assays have been developed over the years to quantitatively assess free-walking behavior in rodents; however, they usually lack direct measurements related to stepping gait strategies, footprint patterns, and coordination. To address these shortcomings, an updated version of the MouseWalker, which combines a frustrated total internal reflection (fTIR) walkway with tracking and quantification software, is provided. This open-source system has been adapted to extract several graphical outputs and kinematic parameters, and a set of post-quantification tools can be to analyze the output data provided. This manuscript also demonstrates how this method, allied with already established behavioral tests, quantitatively describes locomotor deficits following spinal cord injury.

An experimental pipeline to quantitatively describe the locomotor pattern of freely walking mice using the MouseWalker (MW) toolbox is provided, ranging from initial video recordings and tracking to post-quantification analysis. A spinal cord contusion injury model in mice is employed to demonstrate the usefulness of the MW system.