Name: Using the MouseWalker to Quantify Locomotor Dysfunction in a Mouse Model of Spinal Cord Injury (Video) | JoVE Journal
Uploaded: 2023-03-24T14:50:00.000+00:00
Duration: 7 min 28 s
Description: Learn quantitative locomotor analysis using the MouseWalker toolbox in a mouse spinal cord injury model. This method enables precise measurement of coordination and motor recovery through kinematic parameters and graphical outputs.

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The authors thank Laura Tucker and Natasa Loncarevic for their comments on the manuscript and the support given by the Rodent Facility of the Instituto de Medicina Molecular Jo&#227;o Lobo Antunes. The authors want to acknowledge financial support from Pr&#233;mios Santa Casa Neuroci&#234;ncias - Prize Melo e Castro for Spinal Cord Injury Research (MC-36/2020) to L.S. and C.S.M. This work was supported by Funda&#231;&#227;o para a Ci&#234;ncia e a Tecnologia (FCT) (PTDC/BIA-COM/0151/2020), iNOVA4Health (UIDB/04462/2020 and UIDP/04462/2020), and LS4FUTURE (LA/P/0087/2020) to C.S.M. L.S. was supported by a CEEC Individual Principal Investigator contract (2021.02253.CEECIND). A.F.I. was supported by a doctoral fellowship from FCT (2020.08168.BD). A.M.M. was supported by a doctoral fellowship from FCT (PD/BD/128445/2017). I.M. was supported by a post-doctoral fellowship from FCT (SFRH/BPD/118051/2016). D.N.S. was supported by a doctoral fellowship from FCT (SFRH/BD/138636/2018).

Quantifying Locomotor Dysfunction in Spinal Cord Injury Mice Using MouseWalker

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</ol>

The authors declare that they have no competing financial interests.

Here, the potential of the MouseWalker method is demonstrated by analyzing locomotor behavior after SCI. It provides new insights into specific alterations in stepping, footprint, and gait patterns that would otherwise be missed by other standard tests. In addition to providing an updated version of the MW package, data analysis tools are also described using the supplied Python scripts (see step 5).
As the MW generates a large dataset and a collection of kinematic parameters that reflect a hi...

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.

<table><tbody><tr><td>&lt;strong&gt;45&amp;ordm; Mirror&amp;nbsp;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>2 aluminum extrusion (2 x 2 cm), 16 cm height, 1 on each side</td><td>Misumi</td><td></td><td></td></tr><tr><td>2 aluminum extrusion (2 x 2 cm), 23 cm, @ 45&amp;deg; , 1 on each side</td><td>Misumi</td><td></td><td></td></tr><tr><td>1 aluminum extrusion (2 x 2 cm), 83 cm long</td><td>Misumi</td><td></td><td></td></tr><tr><td>87 x 23 cm mirror</td><td>General glass supplier&amp;nbsp;</td><td></td><td></td></tr><tr><td>black cardboard filler&amp;nbsp;</td><td>General stationery supplier</td><td></td><td>We used 2, one with 69 x 6 cm and another with 69 x 3cm to limit the reflection on the mirror</td></tr><tr><td>&lt;strong&gt;Background backlight&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>109 x 23 cm plexiglass (0.9525 cm thick)</td><td>General hardware supplier</td><td></td><td></td></tr><tr><td>2 lateral aluminum extrusion (4 x 4 cm), 20 cm long, 1 on each side</td><td>Misumi</td><td></td><td></td></tr><tr><td>multicolor LED strip</td><td>General hardware supplier</td><td></td><td></td></tr><tr><td>white opaque paper to cover the plexyglass</td><td>General stationery supplier</td><td></td><td></td></tr><tr><td>&lt;strong&gt;fTIR Support base and posts&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>2 aluminum extrusion (4 x 4 cm), 100 cm height</td><td>Misumi</td><td></td><td></td></tr><tr><td>60 x 30 cm metric breadboard</td><td>Edmund Optics&amp;nbsp;</td><td>#54-641</td><td></td></tr><tr><td>M6 12 mm screws</td><td>Edmund Optics&amp;nbsp;</td><td></td><td></td></tr><tr><td>M6 hex nuts and wahers</td><td>Edmund Optics&amp;nbsp;</td><td></td><td></td></tr><tr><td>&lt;strong&gt;fTIR Walkway&amp;nbsp;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>109 x 8.5 cm plexyglass (1.2 cm thick)</td><td>General hardware supplier</td><td></td><td>109 x 8.5 cm plexyglass (1.2 cm thick)</td></tr><tr><td>109 cm long Base-U-channel aluminum with 1.6 cm height x 1.9 cm depth thick folds (to hold the plexyglass)</td><td>General hardware supplier</td><td></td><td></td></tr><tr><td>2 lateral aluminum extrusion (4 x 4 cm) 20 cm length, 1 on each side</td><td>Misumi</td><td></td><td></td></tr><tr><td>black cardboard filler&amp;nbsp;</td><td>General stationery supplier</td><td></td><td>we used 2 fillers on each side to cover the limits of the plexyglass, avoiding bright edges</td></tr><tr><td>M6 12 mm screws</td><td>Edmund Optics&amp;nbsp;</td><td></td><td></td></tr><tr><td>&lt;strong&gt;High speed camera (on a tripod)&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Blackfly S USB3</td><td>FLIR</td><td>#BFS-U3-32S4M-C</td><td>This is a reccomendation. The requirement is to record at least 100 frames per second</td></tr><tr><td>&lt;strong&gt;Infinite Horizon Impactor&amp;nbsp;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Infinite Horizon Impactor&amp;nbsp;</td><td>Precision Systems and Instrumentation, LLC.</td><td>#0400</td><td></td></tr><tr><td>&lt;strong&gt;Lens&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Nikon AF Zoom-Nikkor 24-85mm</td><td>Nikon</td><td>#1929</td><td>This lens is reccomended, however other lens can be used. Make sure it contains a large aperture (i.e., smaller F-stop values), to capture fTIR signals</td></tr><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>MATLAB R2022b</td><td>MathWorks</td><td></td><td></td></tr><tr><td>Python 3.9.13&amp;nbsp;</td><td>Python Software Foundation</td><td></td><td></td></tr><tr><td>Anaconda Navigator 2.1.4</td><td>Anaconda, Inc.</td><td></td><td></td></tr><tr><td>Spyder 5.1.5&amp;nbsp;</td><td>Spyder Project Contributors</td><td></td><td></td></tr><tr><td>&lt;strong&gt;Walkway wall&amp;nbsp;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>2 large rectagular acrilics with 100 x 15 cm</td><td>Any bricolage convenience store</td><td></td><td></td></tr><tr><td>2 Trapezian acrilic laterals with 6-10 length x 15 cm height</td><td>Any bricolage convenience store</td><td></td><td></td></tr><tr><td>&lt;strong&gt;GitHub Materials&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>&lt;strong&gt;Folder name&lt;/strong&gt;</td><td>&lt;strong&gt;URL&lt;/strong&gt;</td><td></td><td></td></tr><tr><td>Boxplots</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/Boxplots</td><td></td><td>Script to create Boxplots</td></tr><tr><td>Docs</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/Docs</td><td></td><td>Additional documents</td></tr><tr><td>Heatmap</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/Heatmaps</td><td></td><td>Script to create heatmap</td></tr><tr><td>Matlat script</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/Matlab%20Script</td><td></td><td>MouseWalker matlab script</td></tr><tr><td>PCA</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/PCA%20plots</td><td></td><td>Script to perform Principal Component Analysis</td></tr><tr><td>Raw data Plots</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/Rawdata%20Plots</td><td></td><td>Script to create Raw data plots</td></tr><tr><td>Residual Analysis</td><td>https://github.com/NeurogeneLocomotion/MouseWalker/tree/main/Residual_Analysis</td><td></td><td>Code to compute residuals from Raw data</td></tr></tbody></table>

using the mousewalker to quantify locomotor dysfunction in a mouse model of spinal cord injury

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.

The standard BMS system describes the gross motor deficits after SCI14. Due to its subjective nature, other quantitative assays are generally performed alongside the BMS to produce a more detailed and fine assessment of locomotion. However, these tests fail to show specific information about step cycles, stepping patterns, and forelimb-hindlimb coordination, which is extremely important in understanding how the spinal circuitry maintains function and adapts to an incomplete SCI. This section shows...

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.

The execution of complex and highly coordinated motor programs, such as walking and running, is dependent on the rhythmic activation of spinal and ...

using-mousewalker-to-quantify-locomotor-dysfunction-mouse-model

Research

JoVE Journal

Neuroscience

A longitudinal examination of bone loss in the femurs and tibiae of adult mice was performed following spinal cord injury using sequential low-dose X-ray scans.  Tibia bone loss was detected throughout the study, while bone loss in the femur was not detected until 40 days post injury.

Longitudinal Evaluation of Mouse Hind Limb Bone Loss After Spinal Cord Injury using Novel, in vivo, Methodology

Source: Kumar, S., et. al. Mouse Model of Pressure Ulcers After Spinal Cord Injury. J. Vis. Exp. (2019)This video demonstrates a detailed induction of spinal cord injury in mice. The anesthetized mouse is dissected to expose T9-T10 vertebrae, and their spinous processes are removed. The exposed spinal cord is then transected to inflict the injury. The surgical area is then closed, and the mouse is allowed to recover.

Generating a Mouse Model with a Spinal Cord Injury

Kinematic gait analysis in the sagittal plane yields highly precise information about how movement is executed. We describe the application of these techniques to identify gait deficits for mice subjected to autoimmune-mediated demyelination. These methods may also be used to characterize gait deficits for other mouse models featuring impaired locomotion.

Sagittal Plane Kinematic Gait Analysis in C57BL/6 Mice Subjected to MOG35-55 Induced Experimental Autoimmune Encephalomyelitis

This protocol describes a flexible, low-cost system for measuring mouse ambulation in an open field activity assay. We show that a 6-minute ambulation assay based on this system detects a decrease in voluntary movement in mdx mice, and accurately distinguishes improvement in a muscle-specific rescue of these animals.

A Simple and Low-cost Assay for Measuring Ambulation in Mouse Models of Muscular Dystrophy

Here, we describe a simple method to induce clinically relevant skin pressure ulcers (PUs) in a mouse model of spinal cord injury (SCI). This model can be used in pre-clinical studies to screen for different therapeutics for healing PUs in SCI patients.

Mouse Model of Pressure Ulcers After Spinal Cord Injury

The rat thoracic spinal hemisection is a valuable and reproducible model of unilateral spinal cord injury to investigate the neural mechanisms of locomotor recovery and treatment efficacy. This article includes a detailed step-by-step guide to perform the hemisection procedure and to assess locomotor performance in an open-field arena.

Thoracic Spinal Cord Hemisection Surgery and Open-Field Locomotor Assessment in the Rat

We simulated clinical surgery to establish a protocol of direct anastomosis of bilateral brachial plexus nerves via the prespinal route in mice, contributing to the study of the neural mechanisms underlying rehabilitation upon crossing nerve transfer after central and peripheral nervous system injuries.

A Mouse Model of Direct Anastomosis via the Prespinal Route for Crossing Nerve Transfer Surgery

Presented here is a novel automated spinal cord injury contusion device for mice, which can accurately produce spinal cord injury contusion models with varying degrees.

Automated Impactor for Contusive Spinal Cord Injury Model in Mice

This article presents a protocol for executing the highly translational and independently proven mouse Stroke Unit (mSU) concept in large-stroke mice. It also provides a standardized protocol for executing the focal experimental stroke scale in mice, which evaluates stroke focal deficits detected even long-term.

The Mouse Stroke Unit Protocol with Standardized Neurological Scoring for Translational Mouse Stroke Studies

A minimally invasive protocol to stabilize the mouse spinal column and perform repetitive in vivo spinal cord imaging using two-photon microscopy is described. This method combines a spinal stabilization device and an anesthetic regimen to minimize respiratory-induced movements and produce raw imaging data that require no alignment or other post-processing.

In vivo Imaging of the Mouse Spinal Cord Using Two-photon Microscopy

Learn quantitative locomotor analysis using the MouseWalker toolbox in a mouse spinal cord injury model. This method enables precise measurement of coordination and motor recovery through kinematic parameters and graphical outputs.

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

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