The Spinal Control of Backward Locomotion

Harnie, Jonathan; Audet, Johannie; Klishko, Alexander N.; Doelman, Adam; Prilutsky, Boris I.; Frigon, Alain

doi:10.1523/jneurosci.0816-20.2020

Cited by 25 publications

(21 citation statements)

References 87 publications

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“…We followed ARRIVE guidelines for animal studies (Percie du Sert et al, 2020). In our effort to reduce the number of animals used in research, we used these cats in other studies to answer different scientific questions (Latash et al, 2020;Harnie et al, 2019Harnie et al, , 2021Merlet et al, 2020Merlet et al, , 2021.…”

Section: Animals and Ethical Informationmentioning

confidence: 99%

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State- and Condition-Dependent Modulation of the Hindlimb Locomotor Pattern in Intact and Spinal Cats Across Speeds

Harnie

Audet

Mari

et al. 2022

Front. Syst. Neurosci.

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Locomotion after complete spinal cord injury (spinal transection) in animal models is usually evaluated in a hindlimb-only condition with the forelimbs suspended or placed on a stationary platform and compared with quadrupedal locomotion in the intact state. However, because of the quadrupedal nature of movement in these animals, the forelimbs play an important role in modulating the hindlimb pattern. This raises the question: whether changes in the hindlimb pattern after spinal transection are due to the state of the system (intact versus spinal) or because the locomotion is hindlimb-only. We collected kinematic and electromyographic data during locomotion at seven treadmill speeds before and after spinal transection in nine adult cats during quadrupedal and hindlimb-only locomotion in the intact state and hindlimb-only locomotion in the spinal state. We attribute some changes in the hindlimb pattern to the spinal state, such as convergence in stance and swing durations at high speed, improper coordination of ankle and hip joints, a switch in the timing of knee flexor and hip flexor bursts, modulation of burst durations with speed, and incidence of bi-phasic bursts in some muscles. Alternatively, some changes relate to the hindlimb-only nature of the locomotion, such as paw placement relative to the hip at contact, magnitude of knee and ankle yield, burst durations of some muscles and their timing. Overall, we show greater similarity in spatiotemporal and EMG variables between the two hindlimb-only conditions, suggesting that the more appropriate pre-spinal control is hindlimb-only rather than quadrupedal locomotion.

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Section: Animals and Ethical Informationmentioning

confidence: 99%

“…We collected kinematic data as described previously (Harnie et al, 2018(Harnie et al, , 2021. Videos of the left and right sides were obtained with two cameras (Basler AcA640-100g) at 60 frames/s with a spatial resolution of 640 by 480 pixels.…”

Section: Data Collection and Analysismentioning

confidence: 99%

State- and Condition-Dependent Modulation of the Hindlimb Locomotor Pattern in Intact and Spinal Cats Across Speeds

Harnie

Audet

Mari

et al. 2022

Front. Syst. Neurosci.

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“…We followed the ARRIVE guidelines for animal studies (Percie du Sert et al, 2020). To reduce the number of animals used in research, we used the cats in other studies to answer different scientific questions (Harnie et al, 2018(Harnie et al, , 2019(Harnie et al, , 2021Merlet et al, 2020Merlet et al, , 2021.…”

Section: Animals and Ethical Informationmentioning

confidence: 99%

A Validation of Supervised Deep Learning for Gait Analysis in the Cat

Lecomte

Audet

Harnie

et al. 2021

Front. Neuroinform.

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Gait analysis in cats and other animals is generally performed with custom-made or commercially developed software to track reflective markers placed on bony landmarks. This often involves costly motion tracking systems. However, deep learning, and in particular DeepLabCutTM (DLC), allows motion tracking without requiring placing reflective markers or an expensive system. The purpose of this study was to validate the accuracy of DLC for gait analysis in the adult cat by comparing results obtained with DLC and a custom-made software (Expresso) that has been used in several cat studies. Four intact adult cats performed tied-belt (both belts at same speed) and split-belt (belts operating at different speeds) locomotion at different speeds and left-right speed differences on a split-belt treadmill. We calculated several kinematic variables, such as step/stride lengths and joint angles from the estimates made by the two software and assessed the agreement between the two measurements using intraclass correlation coefficient or Lin’s concordance correlation coefficient as well as Pearson’s correlation coefficients. The results showed that DLC is at least as precise as Expresso with good to excellent agreement for all variables. Indeed, all 12 variables showed an agreement above 0.75, considered good, while nine showed an agreement above 0.9, considered excellent. Therefore, deep learning, specifically DLC, is valid for measuring kinematic variables during locomotion in cats, without requiring reflective markers and using a relatively low-cost system.

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“…While the neural mechanisms responsible for the control of forward locomotion have been studied in considerable detail (for review, see Grillner, 1975;Grillner and Zangger, 1979;Orlovsky et al, 1999;Rossignol et al, 2006;Kiehn, 2016), our knowledge about the neural mechanisms generating locomotion in other directions is scarce (Deliagina et al, 2019). Although the comparison of the kinematics of forward walking (FW) and backward walking (BW) in humans and animals has revealed substantial differences (Thorstensson, 1986;Eilam and Shefer, 1992;Ashley-Ross and Lauder, 1997;Vemula et al, 2019), the analysis of the muscle activity patterns revealed similar basic flexor-extensor synergies (Pratt et al, 1996;Jansen et al, 2012;Zelik et al, 2014;Harnie et al, 2021). It has been suggested that there are some common direction-independent neuronal networks contributing to the generation of both FW and BW.…”

Section: Introductionmentioning

confidence: 99%

Activity of Spinal Interneurons during Forward and Backward Locomotion

et al. 2022

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Higher vertebrates are capable not only of forward but also backward and sideways locomotion. Also, single steps in different directions are generated for postural corrections. While the networks responsible for the control of forward walking (FW) have been studied in considerable detail, the networks controlling steps in other directions are mostly unknown. Here, to characterize the operation of the spinal locomotor network during FW and backward walking (BW), we recorded the activity of individual spinal interneurons from L4 to L6 during both FW and BW evoked by epidural stimulation (ES) of the spinal cord at L5-L6 in decerebrate cats of either sex. Three groups of neurons were revealed. Group 1 (45%) had a similar phase of modulation during both FW and BW. Group 2 (27%) changed the phase of modulation in the locomotor cycle depending on the direction of locomotion. Group 3 neurons were modulated during FW only (Group 3a, 21%) or during BW only (Group 3b, 7%). We suggest that Group 1 neurons belong to the network generating the vertical component of steps (the limb elevation and lowering) because it should operate similarly during locomotion in any direction, while Groups 2 and 3 neurons belong to the networks controlling the direction of stepping. Results of this study provide new insights into the organization of the spinal locomotor circuits, advance our understanding of ES therapeutic effects, and can potentially be used for the development of novel strategies for recuperation of impaired balance control, which requires the generation of corrective steps in different directions.

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The Spinal Control of Backward Locomotion

Cited by 25 publications

References 87 publications

State- and Condition-Dependent Modulation of the Hindlimb Locomotor Pattern in Intact and Spinal Cats Across Speeds

State- and Condition-Dependent Modulation of the Hindlimb Locomotor Pattern in Intact and Spinal Cats Across Speeds

A Validation of Supervised Deep Learning for Gait Analysis in the Cat

Activity of Spinal Interneurons during Forward and Backward Locomotion

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