Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits methods
Aim. Evidence-backed execution summary for Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits methods from Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits.
Show snapshot details
On this page
This experiment, in seven questions
Jump straight to the part of the recipe you need. Data and provenance labels stay close to the action they support.
Shopping and prep list
What do I need before I start?
mouse
Subject model for the experiment.
- Use
- confirm full cohort details in the source paper
Seeking postural stability: Distribution of supporting limbs
reagent used in the protocol.
- Use
- Figure shows the percentage of the step cycle duration spent per individual gait on a given number of limb(s). During lateral walk, hop, and out-of-phase walk at low step frequency, mice were mainly supported on three limbs. During faster gaits (trot, hop, and out-of-phase walk at high speed, gallops, and bounds), m...
Kinematic analysis
For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during steady-state treadmill locomotion, thus avoiding the acceleration and deceleration phases observed with a catwalk setup. The timing of foot...
- Use
- For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during steady-state treadmill locomotion, thus avoiding the acceleration and deceleration phases observed with a catwalk setup. The timing of foot...
Gaits with an in-phase hindlimb coupling
These gaits corresponded to half-bound, full-bound, and hop (Grillner,; Hildebrand, ). The full-bound was distinguished from the half-bound by a robust in-phase coupling of the left-right forelimbs (Supplementary Videos, ). The duty cycle of the stance phase was inferior to 50%, which was indicative of running gai...
- Use
- These gaits corresponded to half-bound, full-bound, and hop (Grillner,; Hildebrand, ). The full-bound was distinguished from the half-bound by a robust in-phase coupling of the left-right forelimbs (Supplementary Videos, ). The duty cycle of the stance phase was inferior to 50%, which was indicative of running gai...
Gaits with an out-of-phase hindlimb coupling
Based on the duty cycle, we were able to identify and characterize two more running gaits, the transverse and the rotary gallop, for which the hindlimb coupling was out-of-phase (Supplementary Video ). While the out-of-phase coupling of hindlimbs was more variable in the transverse gallop than in rotary gallop, the...
- Use
- Based on the duty cycle, we were able to identify and characterize two more running gaits, the transverse and the rotary gallop, for which the hindlimb coupling was out-of-phase (Supplementary Video ). While the out-of-phase coupling of hindlimbs was more variable in the transverse gallop than in rotary gallop, the...
A dynamic system with attractor, semi-attractor, and transient gaits
Locomotion is a dynamic process, which depends on intrinsic and extrinsic properties. The intrinsic properties reflect the current status and the history of the system and its sub-systems, which are embedded in the anatomy and physiology of spinal cervical and lumbar locomotor circuits, and its supraspinal descendin...
- Use
- Locomotion is a dynamic process, which depends on intrinsic and extrinsic properties. The intrinsic properties reflect the current status and the history of the system and its sub-systems, which are embedded in the anatomy and physiology of spinal cervical and lumbar locomotor circuits, and its supraspinal descendin...
A dynamic system with attractor, semi-attractor, and transient gaits
Using neonatal locomotor studies, mouse genetics have previously shown that manipulating genes can reorganize the spinal locomotor circuit. This neural rewiring consequently can reduce or increase the diversity of locomotor patterns, thus leading to a unique and strong left-right synchronization or an increased vari...
- Use
- Using neonatal locomotor studies, mouse genetics have previously shown that manipulating genes can reorganize the spinal locomotor circuit. This neural rewiring consequently can reduce or increase the diversity of locomotor patterns, thus leading to a unique and strong left-right synchronization or an increased vari...
A dynamic system with attractor, semi-attractor, and transient gaits
Moreover, the neural circuit undergoes massive changes during development, thus giving rise to functional changes at the cellular, systemic, and behavioral levels. This translates into the acquisition of new locomotor gaits, as illustrated by crawling or rolling in the infant, which eventually switches to a walking...
- Use
- Moreover, the neural circuit undergoes massive changes during development, thus giving rise to functional changes at the cellular, systemic, and behavioral levels. This translates into the acquisition of new locomotor gaits, as illustrated by crawling or rolling in the infant, which eventually switches to a walking...
A dynamic system with attractor, semi-attractor, and transient gaits
In addition, the dynamic of locomotor gaits also depends on extrinsic properties, such as the environment and the context in which the mouse evolved. Laboratory mice were fed ad libitum and kept in small cages are not exposed to a rich and life-threatening environment; there is hence no need to seek food and water o...
- Use
- In addition, the dynamic of locomotor gaits also depends on extrinsic properties, such as the environment and the context in which the mouse evolved. Laboratory mice were fed ad libitum and kept in small cages are not exposed to a rich and life-threatening environment; there is hence no need to seek food and water o...
A dynamic system with attractor, semi-attractor, and transient gaits
As previously reported during over-ground and catwalk locomotion (Serradj and Jamon,; Talpalar et al.,; Borgius et al.,; Bellardita and Kiehn, ), we identified the trot as a preferential or attractor gait during treadmill locomotion. Its large spectrum of stride frequency over a wide range of treadmill speeds all...
- Use
- As previously reported during over-ground and catwalk locomotion (Serradj and Jamon,; Talpalar et al.,; Borgius et al.,; Bellardita and Kiehn, ), we identified the trot as a preferential or attractor gait during treadmill locomotion. Its large spectrum of stride frequency over a wide range of treadmill speeds all...
Before you run
What should be confirmed before execution?
First confirmation
Equipment is listed but no product mappings are linked.
Confirm before execution
This page is backed by a publishable Replication Data Ledger package with zero critical source-verification issues.
Confirm before execution
Open the source paper before finalizing run-specific details.
Procurement checkpoint
Use source-stated vendors where present. Treat mapped products as sourcing options unless the page marks an exact source match.
Open quote workflowStep-by-step procedure
What do I do, in order?
Materials and methods
Six adult C57BL/6J mice (>3 weeks old) of either sex were used in this study. All procedures were performed according to the guidelines of the Canadian Council on Animal Care and were approved by the local committee of Université Laval (CPAUL and CPAC).
Kinematic analysis
For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during steady-state treadmill locomotion, thus avoiding the acceleration and deceleration phases observed with a catwalk setup. The timing of foot lifts and contacts for all four limbs, as well as the two-dimensional spatial coordinates of joints, were manually extracted at a resolution of 5 ms (200 samples/s). Temporal and spatial data were exported and processed with custom-written routines in Matlab (MathWorks). We first evaluated basic locomotor parameters. The step cycle was defined by two successive foot contacts from the reference limb (here, the left hindlimb) to determine the instantaneous step frequency. The step cycle was divided in two phases: the stance phase initiated when the foot of a limb made contac...
Materials and methods
Mice were trained to walk on a commercially available single-lane mouse treadmill (LE 8700 Series, Panlab). The inner dimensions of the lane were 32 × 5 cm. Speed could be adjusted from 5 to 150 cm/s. The electrified grid at the rear of the lane was set at the minimal intensity (0.1 mA) to motivate locomotion of mice on the belt. First, mice were allowed to acclimate quietly on the lane for 20-30 min. They were then introduced to walk at 10-15 cm/s for 5 min. At that stage, the mice kept walking on the treadmill belt to avoid the electrified grid. Among the group of nine mice used during the training phase, six learned to avoid the electrified grid. The three remaining mice were excluded from the study. Mice were walked at increasing speed. Once they reached 100 cm/s, they were tested 3 times at each speed to obtain at least 10 contiguous strides (bouts of 10-60...
Kinematic analysis
Based on previous studies comparing several quadruped species (Hildebrand,,; Heglund and Taylor,; Abourachid et al., ) or focusing on dogs (Maes and Abourachid, ) or mice (Herbin et al., ), we identified and classified eight gaits: lateral walk, trot, rotary gallop, transverse gallop, half-bound, full-bound, hop, and out-of-phase walk (see procedure in Figure ). This last gait has not been previously described. To assign a step cycle in a particular gait, we used as criteria the phase values of homologous limbs and ipsilateral limbs and the duty cycle of the hindlimb stance (Table ). Once all step cycles were identified, we computed the mean phase and vector length (r) of hind-, fore-, ipsi-, and diagonal couplings of each gait. Coupling was identified as in-phase (phase = 0 ± 0.125), anti-phase (0.5 ± 0.125) or out-of-phase (low coupling: 0.125-0.375, high coupling...
Graph analysis
Graph analysis is a technique often applied to the study of complex network (Strogatz,; Mason and Verwoerd,; Bullmore and Sporns,; Ma'Ayan, ). Networks are represented as nodes (or vertices) connected by links (or edges). Gaits were defined as nodes, and transitions between gaits as edges. Graphs were constructed at each speed. The weight of a transition from one node to another (e.g., from node A to node B) was calculated as the ratio of this path occurrence on all transitions from the node of origin (node A). In the context of our study, we investigated for all speeds: (1) the probability that a gait remains the same from cycle to cycle (stability), (2) the probability that other gaits converge toward a specific gait (attractiveness), and (3) the probability that when a mouse breaks away from a given gait, it tends to move toward another gait (predictability of transition). For a...
Attractor vs. transitional gaits
We next hypothesized that, given their high occurrence, preferential gaits could be considered as attractor gaits and should occur over a wide range of speeds, whereas the others would emerge as transitional gaits, occurring less often and over a narrower range of speeds. All mice could run up to 105 cm/s, and the number of mice running decreased beyond that speed (Figure ). As illustrated by the color-coded matrix in Figure, two attractor gaits emerged: trot at walking speed (30 cm/s) and full-bound at running speed (>120 cm/s). The out-of-phase walk was the dominant gait at speeds below 15 cm/s, but never at the extent observed for trot and full-bound. A somewhat similar phenomenon occurred at high speeds with half-bound. Although never dominant over the full-bound, half-bound occurred in similar proportion to full-bound at 90 and 105 cm/s. Mice running at 120-150 cm/s had a...
Attractor vs. transitional gaits
The other gaits barely exceeded an occurrence of 30% at any speed. Surprisingly, lateral walk was found only at speeds below 30 cm/s and in lower proportion than out-of-phase walk or trot. Hop was the least frequent gait, and was mainly found at the lowest speeds (5-10 cm/s) and at the transition between walk and run (60-75 cm/s), which could explain its high occurrence in several mutant mice (Kullander,; Beg et al.,; Fawcett et al.,; Shi et al.,; Serradj and Jamon,; Asante et al., ). Also less frequent, transverse and rotary gallops occurred between 60 and 105 cm/s. Interestingly, we found that all gaits, except lateral walk, were equally adopted by mice at 75 cm/s, thus suggesting a state of instability in the neuronal networks generating and organizing locomotor gaits at that speed. In summary, our analysis demonstrates the existence of attractor and transitional g...
Outcomes of locomotor programs
We first analyzed the step frequency of the left hindlimb according to the treadmill speed (Figure ) and found that the step frequency increased linearly from 5 cm/s before reaching a plateau (no more significant increase) at 60-75 cm/s ( p < 0.001, Kruskal-Wallis test and post-ho c Tukey's HSD test). Interestingly, as illustrated in Figure, there were no predominant gaits at 60-75 cm/s, which might reflect a transient state that could preclude the neural locomotor networks from setting a particular locomotor gait. However, half-bound and full-bound emerged as dominant gaits at high treadmill speeds above 75 cm/s (Figure ), therefore suggesting that other parameters might contribute to overcoming the temporal limitation of the step frequency beyond that speed.
Measurement outputs
What raw and processed outputs should exist?
For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during...
- Raw artifact
- Per-run gait capture with paw placement, timing, and stride features for each animal
- Processed artifact
- Cleaned gait metrics table and recovery trend summary across timepoints
- Reported as
- Group comparisons of gait indices, stride metrics, or recovery curves
Based on previous studies comparing several quadruped species (Hildebrand,,; Heglund and Taylor,; Abourachid et al., ) or focusing on dogs (Maes and Abourachid, ) or mice (He...
- Raw artifact
- Per-run gait capture with paw placement, timing, and stride features for each animal
- Processed artifact
- Cleaned gait metrics table and recovery trend summary across timepoints
- Reported as
- Group comparisons of gait indices, stride metrics, or recovery curves
Gait identification. The procedure depicts the architecture of the automated routine identifying the gait. Step 1 is based on the hindlimbs coupling (left side as reference). G...
- Raw artifact
- Per-run gait capture with paw placement, timing, and stride features for each animal
- Processed artifact
- Cleaned gait metrics table and recovery trend summary across timepoints
- Reported as
- Group comparisons of gait indices, stride metrics, or recovery curves
Basic locomotor parameters for each gait.
- Raw artifact
- Per-run gait capture with paw placement, timing, and stride features for each animal
- Processed artifact
- Cleaned gait metrics table and recovery trend summary across timepoints
- Reported as
- Group comparisons of gait indices, stride metrics, or recovery curves
Analysis plan
How should the outputs become interpretable results?
Acquisition
Capture run-level gait data for each animal and preserve the timepoint or treatment labeling.
inferred from protocolPreprocessing / cleaning
Circular statistics were used to evaluate the phase values of forelimbs, hindlimbs, homolateral left limbs, and diagonal limbs (opposite left hindlimb and right forelimb) (Drew and Doucet,; Kiehn and Kjaerulff,; Zar, ).
from paperScoring or quantification
Quantify the primary readouts for this experiment: For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during...; Based on previous studies comparing several quadruped species (Hildebrand,,; Heglund and Taylor,; Abourachid et al., ) or focusing on dogs (Maes and Abourachid, ) or mice (He...; Gait identification. The procedure depicts the architecture of the automated routine identifying the gait. Step 1 is based on the hindlimbs coupling (left side as reference). G...; Basic locomotor parameters for each gait..
from paperStatistical comparison
Circular statistics were used to evaluate the phase values of forelimbs, hindlimbs, homolateral left limbs, and diagonal limbs (opposite left hindlimb and right forelimb) (Drew...; We first analyzed the step frequency of the left hindlimb according to the treadmill speed (Figure ) and found that the step frequency increased linearly from 5 cm/s before reac...; Step frequencies in relation to speed and gait. (A) Boxplot of step frequencies at different treadmill speeds. The upper and lower limits of the box correspond to the percentile...; As expected, there was an effect of gait on the step frequency (statistical comparison of distributions from Figure, p < 0.001, Kruskal-Wallis test, paired comparison by Tukey...
from paperReporting output
Report representative outputs alongside summary comparisons for For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during..., Based on previous studies comparing several quadruped species (Hildebrand,,; Heglund and Taylor,; Abourachid et al., ) or focusing on dogs (Maes and Abourachid, ) or mice (He..., Gait identification. The procedure depicts the architecture of the automated routine identifying the gait. Step 1 is based on the hindlimbs coupling (left side as reference). G..., Basic locomotor parameters for each gait..
inferred from protocolStructured statistical methods
Circular statistics were used to evaluate the phase values of forelimbs, hindlimbs, homolateral left limbs, and diagonal limbs (opposite left hindlimb and right forelimb) (Drew...; We first analyzed the step frequency of the left hindlimb according to the treadmill speed (Figure ) and found that the step frequency increased linearly from 5 cm/s before reac...; Step frequencies in relation to speed and gait. (A) Boxplot of step frequencies at different treadmill speeds. The upper and lower limits of the box correspond to the percentile...; As expected, there was an effect of gait on the step frequency (statistical comparison of distributions from Figure, p < 0.001, Kruskal-Wallis test, paired comparison by Tukey...
source structuredSource and audit
What supports the facts on this page?
Evidence quotes (8)
Six adult C57BL/6J mice (>3 weeks old) of either sex were used in this study. All procedures were performed according to the guidelines of the Canadian Council on Animal Care and were approved by the local committee of Université Laval (CPAUL and CPAC).
For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during steady-state treadmill locomotion, thus avoiding the acceleration and deceleration phases observed with a catwalk setup. The timing of foot lifts and contacts for all four limbs, as well as the two-dimensional spatial coordinates of joints, were manually extracted at a resolution of 5 ms (200 samples/s). Temporal and spatial data were exported and processed with custom-written routines in Matlab (MathWorks). We first evaluated basic locomotor parameters. The step cycle was defined by two successive foot contacts from the reference limb (here, the left hindlimb) to determine the instantaneous step frequency. The step cycle was divided in two phases: the stance phase initiated when the foot of a limb made contact with the ground, thus supporting a part of the body weight, and terminated when the foot was lifted at the onset of the swing phase. The duty cycle of the stance phase was computed as the stance duration divided by the cycle duration and expressed as a percentage. The phase value corresponded to t...
Mice were trained to walk on a commercially available single-lane mouse treadmill (LE 8700 Series, Panlab). The inner dimensions of the lane were 32 × 5 cm. Speed could be adjusted from 5 to 150 cm/s. The electrified grid at the rear of the lane was set at the minimal intensity (0.1 mA) to motivate locomotion of mice on the belt. First, mice were allowed to acclimate quietly on the lane for 20-30 min. They were then introduced to walk at 10-15 cm/s for 5 min. At that stage, the mice kept walking on the treadmill belt to avoid the electrified grid. Among the group of nine mice used during the training phase, six learned to avoid the electrified grid. The three remaining mice were excluded from the study. Mice were walked at increasing speed. Once they reached 100 cm/s, they were tested 3 times at each speed to obtain at least 10 contiguous strides (bouts of 10-60 s depending on the speed). All mice were filmed on the left and right sides by high-frequency (200 frames/s) cameras (Genie HM640, Dalsa Teledyne) during treadmill locomotion. To study inter-limb coordination over a wide range of locomotor speeds, mice were tested at treadmill belt speeds of 5, 10,...
Based on previous studies comparing several quadruped species (Hildebrand,,; Heglund and Taylor,; Abourachid et al., ) or focusing on dogs (Maes and Abourachid, ) or mice (Herbin et al., ), we identified and classified eight gaits: lateral walk, trot, rotary gallop, transverse gallop, half-bound, full-bound, hop, and out-of-phase walk (see procedure in Figure ). This last gait has not been previously described. To assign a step cycle in a particular gait, we used as criteria the phase values of homologous limbs and ipsilateral limbs and the duty cycle of the hindlimb stance (Table ). Once all step cycles were identified, we computed the mean phase and vector length (r) of hind-, fore-, ipsi-, and diagonal couplings of each gait. Coupling was identified as in-phase (phase = 0 ± 0.125), anti-phase (0.5 ± 0.125) or out-of-phase (low coupling: 0.125-0.375, high coupling: 0.625-0.875). We chose ± 0.125 (or 45°) to equally distribute coupling values among quadrants. For the intra-limb coordination, we analyzed the spatial and temporal data of reflective markers placed on fore- and hindlimb joints of 6 mice at 3 treadmill speeds (15, 45, and 90 cm/s)....
Graph analysis is a technique often applied to the study of complex network (Strogatz,; Mason and Verwoerd,; Bullmore and Sporns,; Ma'Ayan, ). Networks are represented as nodes (or vertices) connected by links (or edges). Gaits were defined as nodes, and transitions between gaits as edges. Graphs were constructed at each speed. The weight of a transition from one node to another (e.g., from node A to node B) was calculated as the ratio of this path occurrence on all transitions from the node of origin (node A). In the context of our study, we investigated for all speeds: (1) the probability that a gait remains the same from cycle to cycle (stability), (2) the probability that other gaits converge toward a specific gait (attractiveness), and (3) the probability that when a mouse breaks away from a given gait, it tends to move toward another gait (predictability of transition). For all speeds, we calculated the probability of stability of a gait as the ratio of consecutive step cycles corresponding to the same gait on the total number of step cycles. The attractiveness of a gait corresponded to probability that a step cycle of any other gait changed to this gait. The predictabi...
We next hypothesized that, given their high occurrence, preferential gaits could be considered as attractor gaits and should occur over a wide range of speeds, whereas the others would emerge as transitional gaits, occurring less often and over a narrower range of speeds. All mice could run up to 105 cm/s, and the number of mice running decreased beyond that speed (Figure ). As illustrated by the color-coded matrix in Figure, two attractor gaits emerged: trot at walking speed (30 cm/s) and full-bound at running speed (>120 cm/s). The out-of-phase walk was the dominant gait at speeds below 15 cm/s, but never at the extent observed for trot and full-bound. A somewhat similar phenomenon occurred at high speeds with half-bound. Although never dominant over the full-bound, half-bound occurred in similar proportion to full-bound at 90 and 105 cm/s. Mice running at 120-150 cm/s had a clear preference for full-bound. Although we cannot exclude the possibility that full-bound might have been over-represented at the expense of half-bound due to the decreasing number of mice running at and beyond 120 cm/s (Figure ), these results suggest that full-bound is a prerequisite to achievin...
The other gaits barely exceeded an occurrence of 30% at any speed. Surprisingly, lateral walk was found only at speeds below 30 cm/s and in lower proportion than out-of-phase walk or trot. Hop was the least frequent gait, and was mainly found at the lowest speeds (5-10 cm/s) and at the transition between walk and run (60-75 cm/s), which could explain its high occurrence in several mutant mice (Kullander,; Beg et al.,; Fawcett et al.,; Shi et al.,; Serradj and Jamon,; Asante et al., ). Also less frequent, transverse and rotary gallops occurred between 60 and 105 cm/s. Interestingly, we found that all gaits, except lateral walk, were equally adopted by mice at 75 cm/s, thus suggesting a state of instability in the neuronal networks generating and organizing locomotor gaits at that speed. In summary, our analysis demonstrates the existence of attractor and transitional gaits occurring over a wide or discrete range of speeds, respectively.
We first analyzed the step frequency of the left hindlimb according to the treadmill speed (Figure ) and found that the step frequency increased linearly from 5 cm/s before reaching a plateau (no more significant increase) at 60-75 cm/s ( p < 0.001, Kruskal-Wallis test and post-ho c Tukey's HSD test). Interestingly, as illustrated in Figure, there were no predominant gaits at 60-75 cm/s, which might reflect a transient state that could preclude the neural locomotor networks from setting a particular locomotor gait. However, half-bound and full-bound emerged as dominant gaits at high treadmill speeds above 75 cm/s (Figure ), therefore suggesting that other parameters might contribute to overcoming the temporal limitation of the step frequency beyond that speed.
Machine-readable layer
[
{
"@context": "https://schema.org",
"@type": "HowTo",
"name": "Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits methods",
"description": "Evidence-backed execution summary for Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits methods from Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits.",
"totalTime": "PT7230M",
"step": [
{
"@type": "HowToStep",
"position": 1,
"name": "Materials and methods",
"text": "Six adult C57BL/6J mice (>3 weeks old) of either sex were used in this study. All procedures were performed according to the guidelines of the Canadian Council on Animal Care and were approved by the local committee of Université Laval (CPAUL and CPAC)."
},
{
"@type": "HowToStep",
"position": 2,
"name": "Kinematic analysis",
"text": "For our kinematic studies, videos were analyzed by using custom-designed software (graciously provided by Drs. S. Rossignol and T. Drew, Université de Montréal) during steady-state treadmill locomotion, thus avoiding the acceleration and deceleration phases observed with a catwalk setup. The timing of foot lifts and contacts for all four limbs, as well as the two-dimensional spatial coordinates of joints, were manually extracted at a resolution of 5 ms (200 samples/s). Temporal and spatial data were exported and processed with custom-written routines in Matlab (MathWorks). We first evaluated basic locomotor parameters. The step cycle was defined by two successive foot contacts from the reference limb (here, the left hindlimb) to determine the instantaneous step frequency. The step cycle was divided in two phases: the stance phase initiated when the foot of a limb made contac..."
},
{
"@type": "HowToStep",
"position": 3,
"name": "Materials and methods",
"text": "Mice were trained to walk on a commercially available single-lane mouse treadmill (LE 8700 Series, Panlab). The inner dimensions of the lane were 32 × 5 cm. Speed could be adjusted from 5 to 150 cm/s. The electrified grid at the rear of the lane was set at the minimal intensity (0.1 mA) to motivate locomotion of mice on the belt. First, mice were allowed to acclimate quietly on the lane for 20-30 min. They were then introduced to walk at 10-15 cm/s for 5 min. At that stage, the mice kept walking on the treadmill belt to avoid the electrified grid. Among the group of nine mice used during the training phase, six learned to avoid the electrified grid. The three remaining mice were excluded from the study. Mice were walked at increasing speed. Once they reached 100 cm/s, they were tested 3 times at each speed to obtain at least 10 contiguous strides (bouts of 10-60..."
},
{
"@type": "HowToStep",
"position": 4,
"name": "Kinematic analysis",
"text": "Based on previous studies comparing several quadruped species (Hildebrand,,; Heglund and Taylor,; Abourachid et al., ) or focusing on dogs (Maes and Abourachid, ) or mice (Herbin et al., ), we identified and classified eight gaits: lateral walk, trot, rotary gallop, transverse gallop, half-bound, full-bound, hop, and out-of-phase walk (see procedure in Figure ). This last gait has not been previously described. To assign a step cycle in a particular gait, we used as criteria the phase values of homologous limbs and ipsilateral limbs and the duty cycle of the hindlimb stance (Table ). Once all step cycles were identified, we computed the mean phase and vector length (r) of hind-, fore-, ipsi-, and diagonal couplings of each gait. Coupling was identified as in-phase (phase = 0 ± 0.125), anti-phase (0.5 ± 0.125) or out-of-phase (low coupling: 0.125-0.375, high coupling..."
},
{
"@type": "HowToStep",
"position": 5,
"name": "Graph analysis",
"text": "Graph analysis is a technique often applied to the study of complex network (Strogatz,; Mason and Verwoerd,; Bullmore and Sporns,; Ma'Ayan, ). Networks are represented as nodes (or vertices) connected by links (or edges). Gaits were defined as nodes, and transitions between gaits as edges. Graphs were constructed at each speed. The weight of a transition from one node to another (e.g., from node A to node B) was calculated as the ratio of this path occurrence on all transitions from the node of origin (node A). In the context of our study, we investigated for all speeds: (1) the probability that a gait remains the same from cycle to cycle (stability), (2) the probability that other gaits converge toward a specific gait (attractiveness), and (3) the probability that when a mouse breaks away from a given gait, it tends to move toward another gait (predictability of transition). For a..."
},
{
"@type": "HowToStep",
"position": 6,
"name": "Attractor vs. transitional gaits",
"text": "We next hypothesized that, given their high occurrence, preferential gaits could be considered as attractor gaits and should occur over a wide range of speeds, whereas the others would emerge as transitional gaits, occurring less often and over a narrower range of speeds. All mice could run up to 105 cm/s, and the number of mice running decreased beyond that speed (Figure ). As illustrated by the color-coded matrix in Figure, two attractor gaits emerged: trot at walking speed (30 cm/s) and full-bound at running speed (>120 cm/s). The out-of-phase walk was the dominant gait at speeds below 15 cm/s, but never at the extent observed for trot and full-bound. A somewhat similar phenomenon occurred at high speeds with half-bound. Although never dominant over the full-bound, half-bound occurred in similar proportion to full-bound at 90 and 105 cm/s. Mice running at 120-150 cm/s had a..."
},
{
"@type": "HowToStep",
"position": 7,
"name": "Attractor vs. transitional gaits",
"text": "The other gaits barely exceeded an occurrence of 30% at any speed. Surprisingly, lateral walk was found only at speeds below 30 cm/s and in lower proportion than out-of-phase walk or trot. Hop was the least frequent gait, and was mainly found at the lowest speeds (5-10 cm/s) and at the transition between walk and run (60-75 cm/s), which could explain its high occurrence in several mutant mice (Kullander,; Beg et al.,; Fawcett et al.,; Shi et al.,; Serradj and Jamon,; Asante et al., ). Also less frequent, transverse and rotary gallops occurred between 60 and 105 cm/s. Interestingly, we found that all gaits, except lateral walk, were equally adopted by mice at 75 cm/s, thus suggesting a state of instability in the neuronal networks generating and organizing locomotor gaits at that speed. In summary, our analysis demonstrates the existence of attractor and transitional g..."
},
{
"@type": "HowToStep",
"position": 8,
"name": "Outcomes of locomotor programs",
"text": "We first analyzed the step frequency of the left hindlimb according to the treadmill speed (Figure ) and found that the step frequency increased linearly from 5 cm/s before reaching a plateau (no more significant increase) at 60-75 cm/s ( p < 0.001, Kruskal-Wallis test and post-ho c Tukey's HSD test). Interestingly, as illustrated in Figure, there were no predominant gaits at 60-75 cm/s, which might reflect a transient state that could preclude the neural locomotor networks from setting a particular locomotor gait. However, half-bound and full-bound emerged as dominant gaits at high treadmill speeds above 75 cm/s (Figure ), therefore suggesting that other parameters might contribute to overcoming the temporal limitation of the step frequency beyond that speed."
}
],
"tool": [
{
"@type": "HowToTool",
"name": "Kinematic analysis"
},
{
"@type": "HowToTool",
"name": "Gaits with an in-phase hindlimb coupling"
},
{
"@type": "HowToTool",
"name": "Gaits with an out-of-phase hindlimb coupling"
},
{
"@type": "HowToTool",
"name": "A dynamic system with attractor, semi-attractor, and transient gaits"
},
{
"@type": "HowToTool",
"name": "A dynamic system with attractor, semi-attractor, and transient gaits"
},
{
"@type": "HowToTool",
"name": "A dynamic system with attractor, semi-attractor, and transient gaits"
},
{
"@type": "HowToTool",
"name": "A dynamic system with attractor, semi-attractor, and transient gaits"
},
{
"@type": "HowToTool",
"name": "A dynamic system with attractor, semi-attractor, and transient gaits"
}
],
"supply": [
{
"@type": "HowToSupply",
"name": "Seeking postural stability: Distribution of supporting limbs"
}
],
"isBasedOn": {
"@type": "ScholarlyArticle",
"headline": "Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits",
"datePublished": "2016",
"author": [
{
"@type": "Person",
"name": "Maxime Lemieux"
},
{
"@type": "Person",
"name": "Nicolas Josset"
},
{
"@type": "Person",
"name": "Marie Roussel"
},
{
"@type": "Person",
"name": "Sébastien Couraud"
},
{
"@type": "Person",
"name": "Frédéric Bretzner"
}
],
"identifier": "10.3389/fnins.2016.00042"
}
},
{
"@context": "https://schema.org",
"@type": "BreadcrumbList",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Experiments",
"item": "https://replicatescience.com/experiments"
},
{
"@type": "ListItem",
"position": 2,
"name": "Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits methods",
"item": "https://replicatescience.com/experiments/speed-dependent-modulation-of-the-locomotor-behavior-in-adult-mice-reveals-attractor-and-transitional-gaits-methods-maxime-lemieux-pmc4763020/speed-dependent-modulation-of-the-locomotor-behavior-in-adult-mice-reveals-attractor-and-transitiona-mlph96kn"
}
]
}
]