Using the MouseWalker to Quantify Locomotor Dysfunction in a Mouse Model of 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 how the MW toolbox can help monitor the recovery of locomotor function after SCI and add relevant information about walking behavior.

The study sample was divided into two groups of female C57Bl/6J mice aged 9 weeks old: an SCI experimental group (n = 11), in which the animals underwent laminectomy followed by a moderate to severe contusion injury at the level of the T9/T10 vertebral column using an Infinite Horizon Impactor (see Table of Materials); and a sham-injured control group (n = 10), in which only the laminectomy was performed at the same column level (Figure 1, step 1). The locomotor behavior of the SCI and sham-injured animals was monitored for 30 days. The MW test was performed on the habituation day before the surgery (baseline) and 15 days, 22 days, and 30 days post-injury (dpi) (Figure 1, step 2). For the sake of comparison, the mice were subjected to the BMS test in parallel before the surgery and at 1 dpi, 3 dpi, 7 dpi, 14 dpi, 21 dpi, and 30 dpi (Supplementary Figure 3). After tracking all the videos obtained with the MW, two types of output files were then generated: graphical outputs, showing visual representations of several parameters after each run, and kinematic outputs, summarizing all the measurable motor parameters (Figure 1, step 3 and step 4).

Consequently, using a set of Python scripts (see Table of Materials and the GitHub repository link), the raw data plots were obtained (Figure 1, step 5). As most parameters are influenced by the speed of the animal, a regression model of the baseline group before the injury was performed together with the measured residual values for each condition (Figure 1, step 6). To check for kinematic profiles and significant differences between the control (sham) and experimental groups (SCI), all the kinematic parameters (total of 79) were subjected to a three-order principal component analysis (PCA), and a heatmap was generated with a collection of motor parameters that best described the dataset (total of 33) (Figure 1, step 7a,b). Finally, specific motor parameters that were affected after the SCI were compared to the baseline before the injury (Figure 1, Step 7c).

Figure 1: Schematic representation of the analysis workflow of the MW. (1) The animals are selected for laminectomy (sham control group) or laminectomy followed by a spinal cord injury (experimental group). (2) The animals are then subjected to a behavioral assay the day before the injury and on days 15, 22, and 30 post-injury. (3) The MW generates two types of output data: (a) graphical visualizations of several parameters, such as stance traces, gaiting, and stepping patterns, and (b) a kinematic summary of all the measurable motor parameters. (4) All the control and experimental data are congregated into a single file using the "MouseMultiEvaluate.m" script on MATLAB. (5) The "RawData_PlotGenerator" script for Python generates a visual representation of how all the measurable motor parameters vary according to speed. If the parameters do not correlate with speed, one could skip to (7); however, as most parameters after SCI strongly depend on speed, a model should be generated (6) using the "Residual_DataAnalysis" script for Python. After generating the residual values for each motor parameter, data analysis is carried out (7): (a) a principal component analysis (PCA) is performed using a selection of parameters with a "PCA_PlotGenerator" script; (b) a heatmap is created with a "Heatmap_PlotGenerator" script, to show the statistically significant differences between conditions for different parameters; and c) several individual parameters that are altered after SCI are evaluated with the "BoxPlot_PlotGenerator" script. All scripts are available in Table of Materials and GitHub repository link. The scripts are shown in red. Please click here to view a larger version of this figure.

From the graphical output data gathered from the MW, it was possible to confirm the well-known abrupt change in the visual display of the footprints after SCI. In the "Digital-ink" assay generated by the MW, lack of support of the hindpaws was detected (Figure 2A), together with a decrease in the footprint area for both the left and right hindpaws (Figure 2B), which was maintained from 15 dpi onward (data not shown). In addition, within each step cycle, the MW computes parameters related to the stance phase (i.e., the time between the paw touchdown and before lift-off) and the swing phase (i.e., the time the limb is off the ground). As such, the MW can generate visual "stance traces", which take into consideration the position of the body's center and axis in relation to each leg and their footprint center during the stance phases²³. The overall stance traces obtained for each animal displayed several unique features (Figure 2C). This data showed that after SCI, the hindpaws had shorter stance traces and more random paw positioning at both touchdown and lift-off from 15 dpi onward (Figure 2C).

Figure 2: Representative graphical outputs obtained by the MW software from the tracking videos. (A) "Digital-ink" prints for one SCI animal showing each paw with a different color: red (right fore), yellow (left fore), green (right hind), and blue (left hind) at several time points. (B) Footprints for the left fore (LF), left hind (LH), right fore (RF), and right hind (RH) of one SCI animal at 15 dpi. (C) "Stance traces" for one SCI animal at several time points. The AEP and PEP for one of the legs are illustrated in the first panel. The "footprint clustering" for both the AEP and PEP corresponds to the standard deviation of the average AEP or PEP coordinates in each video. Abbreviations: dpi = days post-injury; cm = centimeter; px = pixel. Please click here to view a larger version of this figure.

Next, the kinematic outputs were analyzed after being computed by the MW (Figure 3 and Figure 4). To obtain a more concise depiction of the dataset and test whether the kinematic motor parameters obtained from the MW were enough to depict locomotor deficits found in SCI animals across time, a PCA²⁷ was performed. Noticeably, 40% of the variance in the data could be explained in the first component (PC1: 40.1%), which segregated the group of animals that had an SCI from the rest, with a p-value lower than 0.001 based on a one-way ANOVA test (Figure 3A,B) at all time points (15 dpi, 22 dpi, and 30 dpi). There was also a poor contribution from the other components (PC2: 11% and PC3:8.6%). The assigned weight of each motor parameter contribution for each component is illustrated in Supplementary Figure 4. Moreover, the variance in the dataset was not enough to reflect differences across time (i.e., between 15 dpi, 22 dpi, and 30 dpi), which replicates the previously described plateau of locomotor recovery¹⁴. Altogether, these results indicate that the kinematic parameters obtained from the MW strongly describe the motor deficits observed after SCI across all time points.

Figure 3: Principal component analysis of all the kinematic motor parameters (79) obtained by the MW software after the residual data analysis. (A) A 3D visualization of the three-component PCA analysis. (B) A 2D visualization with circles representing 50% of collected data. In PC1, which explained over 40% of the variance, the SCI group at 15 dpi, 22 dpi, and 30 dpi was significantly different from the sham group and the baseline (before injury), with a p-value < 0.001, as determined by a one-way ANOVA. Each individual small dot or triangle represents the mean of three videos for each animal, while the larger dots or triangles represent the average point (n = 10-11 per condition, n = 21 for the baseline group). The contribution of each component is indicated in each axis. Abbreviations: dpi = days post-injury; SCI = spinal cord injury; PC = principal component. Please click here to view a larger version of this figure.

Then, a collection of motor parameters was selected based on how strongly it described the dataset (33 in total), and a heatmap was generated (Figure 4). Indeed, most locomotor parameters showed a drastic change after SCI at all time points (15 dpi, 22 dpi, and 30 dpi), while the sham-injured controls only showed significant changes at 30 dpi. These changes in the sham group could be explained by an overall decrease in swing speed, possibly due to test habituation, which will be discussed later.

It was noticeable that the SCI animals walked slower than the sham-injured controls (data not shown). However, independently of speed, at both 15 dpi and 30 dpi, the SCI animals displayed a higher swing duration, lower stance duration, and a lower duty factor index, which relates to the stance duration/stepping period²³. These results indicate that the alterations in leg positioning described above are characteristic of SCI, as seen in other animal models^30,31,32, and are not related to alterations in pace (Figure 4).

It should also be mentioned that the left and right synchrony was not affected, as a significant change in the "phase" indexes for the forelimbs and hindlimbs was not observed^10,23 (Figure 4), indicating intact coupling between the left and right limbs.

Moreover, the SCI mice displayed a lower "stance straightness" index (displacement/path length) in both the forelimbs and hindlimbs (Figure 4). This parameter measures how linear the traces are in relation to the ideal condition, which would be a straight line (ranging from 0 to 1, indicating a linear trace)²⁷. Therefore, these results indicate a strong inability to walk straight in this group.

For each stance phase, the MW draws a reconstruction of the body's oscillations, starting at paw touchdown – the anterior extreme position, or AEP-and ending prior to lift-off – the posterior extreme position, or PEP (see the example in Figure 2C). The "footprint clustering" of both the AEP and PEP measures the standard deviation of the average AEP or PEP coordinates in each video. The SCI animals showed an increase in hindpaw footprint clustering for the AEP at all time points, and a significant effect was only observed for the sham-injured group at 15 dpi (Figure 4). This illustrates that the SCI animals could not correctly position their hindlimbs at touchdown after the swing. Additionally, a decrease in forepaw "footprint clustering" for the PEP was seen, together with a decrease in hindpaw footprint clustering for the PEP, at 30 dpi (Figure 4). These results are in accordance with what is observed in the drawn "stance traces" and suggest that the position of the forepaws becomes more restricted after injury.

Finally, and in accordance with the alterations in the paw positioning, there were alterations in the gait strategies and "pressure" elicited by the paws, as measured by the average brightness over the area (Figure 4), which will be further discussed.

Figure 4: Heatmap plot showing a collection of the significantly altered locomotor parameters comparing SCI animals and sham-injured animals relative to the day prior to surgery, as obtained by the MW after residual data analysis. n = 10-11 per condition; the baseline group includes all the animals the day before surgery, n = 21. Data are expressed by the p-value after statistical analysis with a one-way ANOVA followed by Tukey's post hoc test (for normal distributions) or Dunn's post hoc test (for non-normal distributions). The P-values are represented by a color code, with red and blue shades indicating a decrease or increase relative to baseline, respectively. The color shade represents the statistical significance, with darker colors indicating a higher significance and lighter colors indicating a lower significance; ***P < 0.001; **P < 0.01; *P < 0.05. White indicates no variation. Abbreviations: dpi = days post-injury; SCI = spinal cord injury; s = second; ms = millisecond; avg = average; F = fore; H = hind; AEP = anterior extreme position; PEP = posterior extreme position; LF = left fore; LH = left hind; RF = right fore; RH = right hind. Please click here to view a larger version of this figure.

Subsequently, we sought to understand which individual parameters would be the best to describe the locomotor deficits of SCI animals at different stages of the injury (i.e., 15 dpi, 22 dpi, and 30 dpi). We started by examining the step cycle parameters that showed differences between the forelimbs and hindlimbs as the hindlimbs progressed from total paralysis to partial function (Figure 5). While the average swing speed increased significantly for the forelimbs relative to baseline (before injury), the hindlimb swing speed did not change significantly (although there was a tendency for it to be lower than baseline) (Figure 5A,B). In parallel, the average step length of the forelimbs decreased, with no significant changes for the hindlimbs (Figure 5C,D). Not surprisingly, the injured mice showed decreased forelimb swing duration and an inverse increase in the duration of their hindlimb swings at 15 dpi onward (Figure 5E,F). Taken together, these results indicate that the forelimbs adopted a faster rhythm, with two forelimb cycles for each hindlimb cycle. This 2:1 cycle ratio has been described previously after SCI hemisection in rats^1,33 and illustrates a key aspect of defective forelimb-hindlimb coordination, which is not recovered after 30 dpi in mice.

Figure 5: Step cycle parameters for the forepaws and hindpaws at several time points 1 day before the injury and at 15 dpi, 22 dpi, and 30 dpi in SCI animals (n = 11). (A,B) The average swing speed of the forepaws and hindpaws relative to the baseline. (C,D) The average step length of the forepaws and hindpaws relative to the baseline. (E,F) The average swing duration for the forepaws and hindpaws relative to the baseline. In the boxplots, the median is represented by the middle line, and the lower and upper edges of the boxes represent the 25% and 75% quartiles, respectively; the whiskers represent the range of the full data set. Outliers are represented by single dots. Statistical analysis was conducted with a one-way ANOVA followed by Tukey's post hoc test (for normal distributions) or Dunn's post hoc test (for non-normal distributions). *P < 0.05; **P < 0.01; ***P < 0.001. Abbreviations: dpi = days post-injury; SCI = spinal cord injury; cm = centimeter; s = second. Please click here to view a larger version of this figure.

The MW software is also able to compute the stepping patterns of mice by measuring the fraction of frames assigned to a specific leg combination, and this works as a proxy for the presence of specific gait strategies. At slower speeds, uninjured mice tend to adopt a "walking gait", in which most frames have a single-leg swing (regardless of the paw position). At intermediate speeds, most common on the runway, mice change to a trot gait, in which the most representative configuration is the diagonal-leg swing. Finally, at higher speeds, mice use a "gallop gait", with three legs swinging at the same time^23,34. Other less common configurations include the pacing gait, mostly represented by the lateral-leg swing (either both left or right legs), and the "bound/hopping gait", with either both hindlimbs or forelimbs swinging simultaneouslly¹⁰. However, one should keep in mind that, in the context of an SCI, some of these configurations, such as the three-leg swing, can reflect defective hindlimb paw positioning and, thus, do not precisely match with a specific gaiting strategy-in this case, the gallop. Therefore, the analysis was simplified by comparing the leg configurations alone.

After performing the residual analysis, it was noticed that there was a decrease in the prevalence of diagonal swings accompanied by a decrease in single swings at all time points (Figure 6A,B). More interestingly, there was an increase in the prevalence of lateral swings (Figure 6C). The pacing-like gait is not typical for a normal C57BL/6J mouse; however, it has already been reported to occur after SCI hemisection in rats¹. This in-phase pattern was not prevalent enough to change the forelimb or hindlimb phase index (as seen in Figure 3) but illustrates defective spinal feedback from the hindlimbs to the forelimbs. Additionally, there was a natural increase in the prevalence of forelimb/hindlimb swings (Figure 6D), possibly due to incorrect hindlimb plantar stepping, and an increase in three-leg swings (Figure 6E).

Figure 6: The average indexes for different stepping swing configurations. (A) Diagonal, (B) single, (C) lateral, (D) fore/hind, and (E) three-leg swing at several time points in SCI animals (n = 11) are shown. In the boxplots, the median is represented by the middle line, and the lower and upper edges of the boxes represent the 25% and 75% quartiles, respectively; the whiskers represent the range of the full data set. Outliers are represented by single dots. Statistical analysis was performed with a one-way ANOVA followed by Tukey's post hoc test (for normal distributions) or Dunn's post hoc test (for non-normal distributions). **P < 0.01; ***P < 0.001. Abbreviations: dpi = days post-injury; SCI = spinal cord injury; NA = not applicable. Please click here to view a larger version of this figure.

Finally, another readout that can be extracted from the MW is "pressure" as a measure of brightness/area. With higher speeds, the area of contact with the ground decreases, and the pressure increases, so a linear regression of the baseline data was performed, and the residual values for each condition were measured. It was noticed that the pressure on the forepaws increased significantly across all time points, but the strength of this effect tended to decrease over time, as the change for the left forepaw already lost statistical significance at 30 dpi (Figure 7A,C). This specific effect on the left side could be explained by a lateralized injury, which could have preferentially affected the right side of the spinal cord in this study. Nevertheless, the pressure exerted by the hindpaws was decreased in injured mice, as expected, across all time points, with no tendency toward an increase (Figure 7B,D).

Figure 7: Pressure elicited by the hind and fore paws at several time points in SCI animals (n = 11). Pressure elicited by the (A) left forepaw, (B) left hindpaw, (C) right forepaw, and (D) right hindpaw, shown as relative differences to baseline (the day before injury). In the boxplots, the median is represented as the middle line, and the lower and upper edges of the boxes represent the 25% and 75% quartiles, respectively; the whiskers represent the range of the full data set. Outliers are represented by single dots. Statistical analysis was performed with a one-way ANOVA followed by Tukey's post hoc test (for normal distributions) or Dunn's post hoc test (for non-normal distributions). **P < 0.01; ***P < 0.001. Abbreviations: dpi = days post-injury; SCI = spinal cord injury; cm = centimeter; px = pixel. Please click here to view a larger version of this figure.

Taken together, this study illustrates the power of the MW system for quantitatively describing the motor impairments caused by SCI that can sometimes be disregarded due to other test limitations. Furthermore, it underlines the undoubtedly limited functional recovery across time in the contusion mouse model of SCI.

Supplementary Figure 1: The MW hardware components. (A) This setup is divided as follows: I – fTIR walkway; II – fTIR support base and posts; III – walkway wall; IV – 45° mirror; and V – background backlight. (B) Close-up images of the Base-U- channel and walkway sidelines. (C) Design of the walkway wall. (D) Close-up image of the 45° mirror setup. Abbreviation: cm = centimeter. Please click here to download this File.

Supplementary Figure 2: A single frame of an fTIR video in which the pixel intensity and region areas are indicated. The pixel intensities for the body, background, and footprints used for the video analysis in this study are presented between brackets and indicated in red, all optimized for image clarity. The light intensity should be adjusted to obtain proper discrimination between the different regions. Relative areas of the body and footprints are indicated by dashed yellow lines. Both the areas and pixel intensity were acquired in ImageJ/FIJI. Please click here to download this File.

Supplementary Figure 3: (A) BMS total score and (B) subscore of the mice analyzed in this study (n = 10-11). All data were expressed as mean ± SEM. Statistical analysis was performed with a two-way repeated measures ANOVA followed by Bonferroni's post hoc test; ***P < 0.001. Abbreviation: BMS = Basso mouse scale. Please click here to download this File.

Supplementary Figure 4: The assigned weight of each motor parameter contribution for each component. The assigned weight of each motor parameter (79 in total) after the residual analysis for (A) PC1, (B) PC2, and (C) PC3 in the PCA. The cutoff line was drawn at 0.04 ms and −0.04. Abbreviations: ms = millisecond; avg = average; SD = standard deviation; F = fore; H = hind; AEP = anterior extreme position; PEP = posterior extreme position; LF = left fore; LH = left hind; RF = right fore; RH = right hind; Press = pressure. Please click here to download this File.