Lacquaniti F. Changes in the limb kinematics and walking-distance estimation after shank elongati... more Lacquaniti F. Changes in the limb kinematics and walking-distance estimation after shank elongation: evidence for a locomotor body schema? When walking, step length provides critical information on traveled distance along the ongoing path.
Developmental Medicine & Child Neurology, Oct 6, 2021
ABBREVIATIONS sEMG Surface electromyography SnPM Statistical non-parametric mapping tVAF 1 Total ... more ABBREVIATIONS sEMG Surface electromyography SnPM Statistical non-parametric mapping tVAF 1 Total variance accounted for by one synergy AIM To determine if muscle synergy structure (activations and weights) differs between gait patterns in children with spastic cerebral palsy (CP). METHOD In this cross-sectional study, we classified 188 children with unilateral (n=82) or bilateral (n=106) spastic CP (mean age: 9y 5mo, SD: 4y 3mo, range: 3y 9mo-17y 7mo; 75 females; Gross Motor Function Classification System [GMFCS] level I: 106, GMFCS level II: 55, GMFCS level III: 27) into a minor deviations (n=34), drop foot (n=16), genu recurvatum (n=26), apparent equinus (n=53), crouch (n=39), and jump gait pattern (n=20). Surface electromyography recordings from eight lower limb muscles of the most affected side were used to calculate synergies with weighted non-negative matrix factorization. We compared synergy activations and weights between the patterns. RESULTS Synergy structure was similar between gait patterns, although weights differed in the more impaired children (crouch and jump gait) when compared to the other patterns. Variability in synergy structure between participants was high. INTERPRETATION The similarity in synergy structure between gait patterns suggests a generic motor control strategy to compensate for the brain lesion. However, the differences in weights and high variability between participants indicate that this generic motor control strategy might be individualized and dependent on impairment level.
Introduction: The ability to detect and control self motion based on patterns of optical flow is ... more Introduction: The ability to detect and control self motion based on patterns of optical flow is crucial to the control of posture and locomotion. However, little is know about the early coupling of vision and locomotion in infants. In the current experiments, we attempted to determine if terrestrial optical flow influenced neonatal stepping behavior. Methods: The number of steps taken by 48 3-day-old infants held in air stepping position was recorded for one minute in each of four randomly presented conditions of optic flow: 1) Terrestrial Flow, where a checkerboard, lamellar flow moved toward the infant, 2) Static Texture, where the checkerboard pattern was stationary, 3) Rotating Flow, where triangles rotated clockwise on the surface, and 4) Real Stepping, where the soles of the infant's feet contacted the support surface. Results: There were significant differences in the average number of steps taken per condition, F(3,66) 3.4, p <0.05. More steps were taken in the Terrestrial Flow condition than the Static Texture condition, in the Real Stepping condition than the Rotating Flow condition, and in the Real Stepping condition than the Static condition. A 2-Dimensional kinematic analysis indicated that neonates were more variable and stepped differently in the Terrestrial Flow condition than the other conditions. Discussion and conclusion: These findings suggest that newborns will make stepping movements even if their feet do not receive the tactile stimulation that was once thought necessary to elicit the stepping pattern. Moreover, air stepping was more easily elicited by terrestrial lamellar optical flow.
European Journal of Applied Physiology, Jan 13, 2021
Purpose We sought to identify the developing maturity of walking and running in young children. W... more Purpose We sought to identify the developing maturity of walking and running in young children. We assessed gait patterns for the presence of flight and double support phases complemented by mechanical energetics. The corresponding classification outcomes were contrasted via a shotgun approach involving several potentially informative gait characteristics. A subsequent clustering turned out very effective to classify the degree of gait maturity. Methods Participants (22 typically developing children aged 2-9 years and 7 young, healthy adults) walked/ran on a treadmill at comfortable speeds. We determined double support and flight phases and the relationship between potential and kinetic energy oscillations of the center-of-mass. Based on the literature, we further incorporated a total of 93 gait characteristics (including the above-mentioned ones) and employed multivariate statistics comprising principal component analysis for data compression and hierarchical clustering for classification. Results While the ability to run including a flight phase increased with age, the flight phase did not reach 20% of the gait cycle. It seems that children use a walk-run-strategy when learning to run. Yet, the correlation strength between potential and kinetic energies saturated and so did the amount of recovered mechanical energy. Clustering the set of gait characteristics allowed for classifying gait in more detail. This defines a metric for maturity in terms of deviations from adult gait, which disagrees with chronological age. Conclusions The degree of gait maturity estimated statistically using various gait characteristics does not always relate directly to the chronological age of the child.
OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been inter... more OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. APPROACH Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. MAIN RESULTS We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. SIGNIFICANCE Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds, are likely to provide more robust control strategies for the design of such neuroprostheses.
Slipping, sliding and stability: locomotor strategies for overcoming low-friction surfaces includ... more Slipping, sliding and stability: locomotor strategies for overcoming low-friction surfaces including high resolution figures, can be found at:
Muscle synergy assessments are often employed to evaluate the modular organization of the spinal ... more Muscle synergy assessments are often employed to evaluate the modular organization of the spinal cord during a locomotion task. While they provide valuable insights into the pattern formation of the a-motoneurons at the spinal cord, by construction they cannot capture control from supra-spinal layers. We examined how locomotor muscle synergies are represented in the sensorimotor cortex, with particular focus on the cortico-synergy coherence as a measure of coupling along the cortico-spinal tract. Non-negative matrix factorization served to decompose multivariate electromyographic signals into muscle synergies. Their representations were localized in the cortex using coherence-based beamforming. Overall, the cortico-synergy coherence was maximal in sensorimotor areas especially in the beta-frequency band. However, only for the synergies timed to heel strike, that are related to the double support phases, the coherence was significant. These coherences were closely related to the timing of the activation patterns of the synergies, suggesting sensorimotor cortex to be strongly involved in emergence and control of these synergies.
In this chapter, we explore the use of motion tracking methodology in developmental research. Wit... more In this chapter, we explore the use of motion tracking methodology in developmental research. With motion tracking, also called motion capture, human movements can be precisely recorded and analyzed. Motion tracking provides developmental researchers with objective measurements of motor and (socio-)cognitive development. It can further be used to create carefully-controlled stimuli videos and can offer means of measuring development outside of the lab. We discuss three types of motion tracking that lend themselves to developmental applications. First, marker-based systems track optical or electromagnetic markers or sensors placed on the body and offer high accuracy measurements. Second, markerless methods entail image processing of videos to track the movement of bodies without participants being hindered by physical markers. Third, inertial motion tracking measures three-dimensional movements and can be used in a variety of settings. The chapter concludes by examining three example topics from developmental literature in which motion tracking applications have contributed to our understanding of human development.
Background: Children with cerebral palsy (CP) often show impaired selective motor control (SMC) t... more Background: Children with cerebral palsy (CP) often show impaired selective motor control (SMC) that induces limitations in motor function. Children with CP can improve aspects of pathological gait in an immediate response to visual biofeedback. It is not known, however, how these gait adaptations are achieved at the neural level, nor do we know the extent of SMC plasticity in CP. Aim: Investigate the underlying SMC and changes that may occur when gait is adapted with biofeedback. Methods: Twenty-three ambulatory children with CP and related (hereditary) forms of spastic paresis (Aged: 10.4 ± 3.1, 6-16 years, M: 16/F: 9) were challenged with realtime biofeedback to improve step length, knee extension, and ankle power while walking on an instrumented treadmill in a virtual reality environment. The electromyograms of eight superficial muscles of the leg were analyzed and synergies were further decomposed using non-negative matrix factorization (NNMF) using 1 to 5 synergies, to quantify SMC. Total variance accounted for (tVAF) was used as a measure of synergy complexity. An imposed four synergy solution was investigated further to compare similarity in weightings and timing patterns of matched paired synergies between baseline and biofeedback trials. Results: Despite changes in walking pattern, changes in synergies were limited. The number of synergies required to explain at least 90% of muscle activation increased significantly, however, the change in measures of tVAF 1 from baseline (0.75 ± 0.08) were less than ±2% between trials. In addition, within-subject similarity of synergies to baseline walking was high (>0.8) across all biofeedback trials. Conclusion: These results suggest that while gait may be adapted in an immediate response, SMC as quantified by synergy analysis is perhaps more rigidly impaired in CP. Subtle changes in synergies were identified; however, it is questionable if these
Lacquaniti F. Changes in the limb kinematics and walking-distance estimation after shank elongati... more Lacquaniti F. Changes in the limb kinematics and walking-distance estimation after shank elongation: evidence for a locomotor body schema? When walking, step length provides critical information on traveled distance along the ongoing path.
Developmental Medicine & Child Neurology, Oct 6, 2021
ABBREVIATIONS sEMG Surface electromyography SnPM Statistical non-parametric mapping tVAF 1 Total ... more ABBREVIATIONS sEMG Surface electromyography SnPM Statistical non-parametric mapping tVAF 1 Total variance accounted for by one synergy AIM To determine if muscle synergy structure (activations and weights) differs between gait patterns in children with spastic cerebral palsy (CP). METHOD In this cross-sectional study, we classified 188 children with unilateral (n=82) or bilateral (n=106) spastic CP (mean age: 9y 5mo, SD: 4y 3mo, range: 3y 9mo-17y 7mo; 75 females; Gross Motor Function Classification System [GMFCS] level I: 106, GMFCS level II: 55, GMFCS level III: 27) into a minor deviations (n=34), drop foot (n=16), genu recurvatum (n=26), apparent equinus (n=53), crouch (n=39), and jump gait pattern (n=20). Surface electromyography recordings from eight lower limb muscles of the most affected side were used to calculate synergies with weighted non-negative matrix factorization. We compared synergy activations and weights between the patterns. RESULTS Synergy structure was similar between gait patterns, although weights differed in the more impaired children (crouch and jump gait) when compared to the other patterns. Variability in synergy structure between participants was high. INTERPRETATION The similarity in synergy structure between gait patterns suggests a generic motor control strategy to compensate for the brain lesion. However, the differences in weights and high variability between participants indicate that this generic motor control strategy might be individualized and dependent on impairment level.
Introduction: The ability to detect and control self motion based on patterns of optical flow is ... more Introduction: The ability to detect and control self motion based on patterns of optical flow is crucial to the control of posture and locomotion. However, little is know about the early coupling of vision and locomotion in infants. In the current experiments, we attempted to determine if terrestrial optical flow influenced neonatal stepping behavior. Methods: The number of steps taken by 48 3-day-old infants held in air stepping position was recorded for one minute in each of four randomly presented conditions of optic flow: 1) Terrestrial Flow, where a checkerboard, lamellar flow moved toward the infant, 2) Static Texture, where the checkerboard pattern was stationary, 3) Rotating Flow, where triangles rotated clockwise on the surface, and 4) Real Stepping, where the soles of the infant's feet contacted the support surface. Results: There were significant differences in the average number of steps taken per condition, F(3,66) 3.4, p <0.05. More steps were taken in the Terrestrial Flow condition than the Static Texture condition, in the Real Stepping condition than the Rotating Flow condition, and in the Real Stepping condition than the Static condition. A 2-Dimensional kinematic analysis indicated that neonates were more variable and stepped differently in the Terrestrial Flow condition than the other conditions. Discussion and conclusion: These findings suggest that newborns will make stepping movements even if their feet do not receive the tactile stimulation that was once thought necessary to elicit the stepping pattern. Moreover, air stepping was more easily elicited by terrestrial lamellar optical flow.
European Journal of Applied Physiology, Jan 13, 2021
Purpose We sought to identify the developing maturity of walking and running in young children. W... more Purpose We sought to identify the developing maturity of walking and running in young children. We assessed gait patterns for the presence of flight and double support phases complemented by mechanical energetics. The corresponding classification outcomes were contrasted via a shotgun approach involving several potentially informative gait characteristics. A subsequent clustering turned out very effective to classify the degree of gait maturity. Methods Participants (22 typically developing children aged 2-9 years and 7 young, healthy adults) walked/ran on a treadmill at comfortable speeds. We determined double support and flight phases and the relationship between potential and kinetic energy oscillations of the center-of-mass. Based on the literature, we further incorporated a total of 93 gait characteristics (including the above-mentioned ones) and employed multivariate statistics comprising principal component analysis for data compression and hierarchical clustering for classification. Results While the ability to run including a flight phase increased with age, the flight phase did not reach 20% of the gait cycle. It seems that children use a walk-run-strategy when learning to run. Yet, the correlation strength between potential and kinetic energies saturated and so did the amount of recovered mechanical energy. Clustering the set of gait characteristics allowed for classifying gait in more detail. This defines a metric for maturity in terms of deviations from adult gait, which disagrees with chronological age. Conclusions The degree of gait maturity estimated statistically using various gait characteristics does not always relate directly to the chronological age of the child.
OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been inter... more OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. APPROACH Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. MAIN RESULTS We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. SIGNIFICANCE Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds, are likely to provide more robust control strategies for the design of such neuroprostheses.
Slipping, sliding and stability: locomotor strategies for overcoming low-friction surfaces includ... more Slipping, sliding and stability: locomotor strategies for overcoming low-friction surfaces including high resolution figures, can be found at:
Muscle synergy assessments are often employed to evaluate the modular organization of the spinal ... more Muscle synergy assessments are often employed to evaluate the modular organization of the spinal cord during a locomotion task. While they provide valuable insights into the pattern formation of the a-motoneurons at the spinal cord, by construction they cannot capture control from supra-spinal layers. We examined how locomotor muscle synergies are represented in the sensorimotor cortex, with particular focus on the cortico-synergy coherence as a measure of coupling along the cortico-spinal tract. Non-negative matrix factorization served to decompose multivariate electromyographic signals into muscle synergies. Their representations were localized in the cortex using coherence-based beamforming. Overall, the cortico-synergy coherence was maximal in sensorimotor areas especially in the beta-frequency band. However, only for the synergies timed to heel strike, that are related to the double support phases, the coherence was significant. These coherences were closely related to the timing of the activation patterns of the synergies, suggesting sensorimotor cortex to be strongly involved in emergence and control of these synergies.
In this chapter, we explore the use of motion tracking methodology in developmental research. Wit... more In this chapter, we explore the use of motion tracking methodology in developmental research. With motion tracking, also called motion capture, human movements can be precisely recorded and analyzed. Motion tracking provides developmental researchers with objective measurements of motor and (socio-)cognitive development. It can further be used to create carefully-controlled stimuli videos and can offer means of measuring development outside of the lab. We discuss three types of motion tracking that lend themselves to developmental applications. First, marker-based systems track optical or electromagnetic markers or sensors placed on the body and offer high accuracy measurements. Second, markerless methods entail image processing of videos to track the movement of bodies without participants being hindered by physical markers. Third, inertial motion tracking measures three-dimensional movements and can be used in a variety of settings. The chapter concludes by examining three example topics from developmental literature in which motion tracking applications have contributed to our understanding of human development.
Background: Children with cerebral palsy (CP) often show impaired selective motor control (SMC) t... more Background: Children with cerebral palsy (CP) often show impaired selective motor control (SMC) that induces limitations in motor function. Children with CP can improve aspects of pathological gait in an immediate response to visual biofeedback. It is not known, however, how these gait adaptations are achieved at the neural level, nor do we know the extent of SMC plasticity in CP. Aim: Investigate the underlying SMC and changes that may occur when gait is adapted with biofeedback. Methods: Twenty-three ambulatory children with CP and related (hereditary) forms of spastic paresis (Aged: 10.4 ± 3.1, 6-16 years, M: 16/F: 9) were challenged with realtime biofeedback to improve step length, knee extension, and ankle power while walking on an instrumented treadmill in a virtual reality environment. The electromyograms of eight superficial muscles of the leg were analyzed and synergies were further decomposed using non-negative matrix factorization (NNMF) using 1 to 5 synergies, to quantify SMC. Total variance accounted for (tVAF) was used as a measure of synergy complexity. An imposed four synergy solution was investigated further to compare similarity in weightings and timing patterns of matched paired synergies between baseline and biofeedback trials. Results: Despite changes in walking pattern, changes in synergies were limited. The number of synergies required to explain at least 90% of muscle activation increased significantly, however, the change in measures of tVAF 1 from baseline (0.75 ± 0.08) were less than ±2% between trials. In addition, within-subject similarity of synergies to baseline walking was high (>0.8) across all biofeedback trials. Conclusion: These results suggest that while gait may be adapted in an immediate response, SMC as quantified by synergy analysis is perhaps more rigidly impaired in CP. Subtle changes in synergies were identified; however, it is questionable if these
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