Motor control programs and walking

The question of how the central nervous system coordinates muscle activity is central to an understanding of motor control. The authors argue that motor programs may be considered as a characteristic timing of muscle activations linked to specific kinematic events. In particular, muscle activity occurring during human locomotion can be accounted for by five basic temporal components in a variety of locomotion conditions. Spatiotemporal maps of spinal cord motoneuron activation also show discrete periods of activity. Furthermore, the coordination of locomotion with voluntary tasks is accomplished through a superposition of motor programs or activation timings that are separately associated with each task. As a consequence, the selection of muscle synergies appears to be downstream from the processes that generate activation timings. Copyright © 2006 Sage Publications

Five basic muscle activation patterns account for muscle activity during human locomotion

An electromyographic (EMG) activity pattern for individual muscles in the gait cycle exhibits a great deal of intersubject, intermuscle and context-dependent variability. Here we examined the issue of common underlying patterns by applying factor analysis to the set of EMG records obtained at different walking speeds and gravitational loads. To this end healthy subjects were asked to walk on a treadmill at speeds of 1, 2,3 and 5 km h(-1) as well as when 35-95% of the body weight was supported using a harness. We recorded from 12-16 ipsilateral leg and trunk muscles using both surface and intramuscular recording and determined the average, normalized EMG of each record for 10-15 consecutive step cycles. We identified five basic underlying factors or component waveforms that can account for about 90% of the total waveform variance across different muscles during normal gait. Furthermore, while activation patterns of individual muscles could vary dramatically with speed and gravitational load, both the limb kinematics and the basic EMG components displayed only limited changes. Thus, we found a systematic phase shift of all five factors with speed in the same direction as the shift in the onset of the swing phase. This tendency for the factors to be timed according to the lift-off event supports the idea that the origin of the gait cycle generation is the propulsion rather than heel strike event. The basic invariance of the factors with walking speed and with body weight unloading implies that a few oscillating circuits drive the active muscles to produce the locomotion kinematics. A flexible and dynamic distribution of these basic components to the muscles may result from various descending and proprioceptive signals that depend on the kinematic and kinetic demands of the movements

Spinal cord maps of spatiotemporal alpha-motoneuron activation in humans walking at different speeds

Spinal cord maps of spatiotemporal alpha-motoneuron activation in humans walking at different speeds. J Neurophysiol 95: 602-618, 2006. First published November 9, 2005; doi: 10.1152/jn. 00767.2005. Functional MRI (fMRI) imaging of motoneuron activity in the human spinal cord is still in its infancy, and it will remain difficult to apply to walking. Here we present a viable alternative for documenting the spatiotemporal maps of alpha-motorneuron (MN) activity in the human spinal cord during walking, similar to the method recently reported for the cat. We recorded EMG activity from 16 to 32 ipsilateral limb and trunk muscles in 13 healthy subjects walking on a treadmill at different speeds (1-7 km/h) and mapped the recorded patterns onto the spinal cord in approximate rostrocaudal locations of the motoneuron pools. This approach can provide information about pattern generator output during locomotion in terms of segmental control rather than in terms of individual muscle control. A striking feature we found is that nearly every spinal segment undergoes at least two cycles of activation in the step cycle, thus supporting the idea of half-center oscillators controlling MN activation at any segmental level. The resulting spatiotemporal map patterns seem highly stereotyped over the range of walking speeds studied, although there were also some systematic redistributions of MN activity with speed. Bursts of MN activity were either temporally aligned across several spinal segments or switched between different segments. For example, the center of mass of MN activity in the lumbosacral levels generally shifted from rostral to caudal positions in two cycles for each step, revealing four major activation foci: two in the upper lumbar segments and two in the sacral segments. The results are consistent with the presence of at least two and possibly more pattern generators controlling the activation of lumbosacral MNs

Spinal cord maps of spatiotemporal alpha-motoneuron activation in humans walking at different speeds

Spinal cord maps of spatiotemporal alpha-motoneuron activation in humans walking at different speeds. J Neurophysiol 95: 602-618, 2006. First published November 9, 2005; doi: 10.1152/jn. 00767.2005. Functional MRI (fMRI) imaging of motoneuron activity in the human spinal cord is still in its infancy, and it will remain difficult to apply to walking. Here we present a viable alternative for documenting the spatiotemporal maps of alpha-motorneuron (MN) activity in the human spinal cord during walking, similar to the method recently reported for the cat. We recorded EMG activity from 16 to 32 ipsilateral limb and trunk muscles in 13 healthy subjects walking on a treadmill at different speeds (1-7 km/h) and mapped the recorded patterns onto the spinal cord in approximate rostrocaudal locations of the motoneuron pools. This approach can provide information about pattern generator output during locomotion in terms of segmental control rather than in terms of individual muscle control. A striking feature we found is that nearly every spinal segment undergoes at least two cycles of activation in the step cycle, thus supporting the idea of half-center oscillators controlling MN activation at any segmental level. The resulting spatiotemporal map patterns seem highly stereotyped over the range of walking speeds studied, although there were also some systematic redistributions of MN activity with speed. Bursts of MN activity were either temporally aligned across several spinal segments or switched between different segments. For example, the center of mass of MN activity in the lumbosacral levels generally shifted from rostral to caudal positions in two cycles for each step, revealing four major activation foci: two in the upper lumbar segments and two in the sacral segments. The results are consistent with the presence of at least two and possibly more pattern generators controlling the activation of lumbosacral MNs

Distributed neural networks for controlling human locomotion Lessons from normal and SCI subjects

The control of human locomotion engages various brain structures and numerous muscles. Even though the hypothetical central pattern generator (CPG) and sensory feedback can sustain the basic locomotor rhythm, the resultant motor output is highly adaptable and context-dependent. Indeed, while the temporal architecture of the locomotor output (basic EMG components) is relatively conserved across subjects and conditions, the spatial architecture (muscle activations) shows considerable non-linear changes with walking speed, level of body unloading or the direction of progression. Even so, leg kinematics are remarkably similar in all cases. Spinal cord injured (SCI) patients may learn new motor patterns with training rather than re-activate normal motor patterns, and such locomotor improvements may not transfer to untrained tasks. Redundancy in the neuromuscular system or malfunctioning of injured 'elements' may often result in motor equivalent compensatory solutions. injured pathways can partially recover while uninjured pathways can augment or modify their activity. As a result, the reconstructed spatiotemporal maps of motor neuron activity in SCI patients might be quite different from those of healthy subjects but they nevertheless achieve nearly normal foot kinematics. Kinematics training may thus provide a more successful rehabilitation than training based on reconstructing normal muscle activation patterns. Taken together, recent data support the idea of plasticity and distributed networks for controlling human locomotion. A new generation of robotic devices takes advantage of this by providing the opportunity for patients to generate and correct limb movements rather than just adapting muscle activation to the fixed kinematic template imposed by a gait orthosis. (c) 2008 Elsevier Inc. All rights reserved

On the origin of planar covariation of elevation angles during human locomotion

Leg segment rotations in human walking covary, so that the three-dimensional trajectory of temporal changes in the elevation angles lies close to a plane. Recently the role of central versus biomechanical constraints on the kinematics control of human locomotion has been questioned. Here we show, based on both modeling and experimental data, that the planar law of intersegmental coordination is not a simple consequence of biomechanics. First, the full limb behavior in various locomotion modes (walking on inclined surface, staircase stepping, air-stepping, crouched walking, hopping) can be expressed as 2 degrees of freedom planar motion even though the orientation of the plane and pairwise segment angle correlations may differ substantially. Second, planar covariation is not an inevitable outcome of any locomotor movement. It can be systematically violated in some conditions (e. g., when stooping and grasping an object on the floor during walking or in toddlers at the onset of independent walking) or transferred into a simple linear relationship in others (e. g., during stepping in place). Finally, all three major limb segments contribute importantly to planar covariation and its characteristics resulting in a certain endpoint trajectory defined by the limb axis length and orientation. Recent advances in the neural control of movement support the hypothesis about central representation of kinematics components

Spatiotemporal organization of alpha-motoneuron activity in the human spinal cord during different gaits and gait transitions

Here we studied the spatiotemporal organization of motoneuron (MN) activity during different human gaits. We recorded the electromyographic (EMG) activity patterns in 32 ipsilateral limb and trunk muscles from normal subjects while running and walking on a treadmill (3-12 km/h). In addition, we recorded backward walking and skipping, a distinct human gait that comprises the features of both walking and running. We mapped the recorded EMG activity patterns onto the spinal cord in approximate rostrocaudal locations of the MN pools. The activation of MNs tends to occur in bursts and be segregated by spinal segment in a gait-specific manner. In particular, sacral and cervical activation timings were clearly gait-dependent. Swing-related activity constituted an appreciable fraction (> 30%) of the total MN activity of leg muscles. Locomoting at non-preferred speeds (running and walking at 5 and 9 km/h, respectively) showed clear differences relative to preferred speeds. Running at low speeds was characterized by wider sacral activation. Walking at high non-preferred speeds was accompanied by an 'atypical' locus of activation in the upper lumbar spinal cord during late stance and by a drastically increased activation of lumbosacral segments. The latter findings suggest that the optimal speed of gait transitions may be related to an optimal intensity of the total MN activity, in addition to other factors previously described. The results overall support the idea of flexibility and adaptability of spatiotemporal activity in the spinal circuitry with constraints on the temporal functional connectivity of hypothetical pulsatile burst generators

Motor patterns in human walking and running

Despite distinct differences between walking and running, the two types of human locomotion are likely to be controlled by shared pattern-generating networks. However, the differences between their kinematics and kinetics imply that corresponding muscle activations may also be quite different. We examined the differences between walking and running by recording kinematics and electromyographic (EMG) activity in 32 ipsilateral limb and trunk muscles during human locomotion, and compared the effects of speed (3-12 km/h) and gait. We found that the timing of muscle activation was accounted for by five basic temporal activation components during running as we previously found for walking. Each component was loaded on similar sets of leg muscles in both gaits but generally on different sets of upper trunk and shoulder muscles. The major difference between walking and running was that one temporal component, occurring during stance, was shifted to an earlier phase in the step cycle during running. These muscle activation differences between gaits did not simply depend on locomotion speed as shown by recordings during each gait over the same range of speeds (5-9 km/h). The results are consistent with an organization of locomotion motor programs having two parts, one that organizes muscle activation during swing and another during stance and the transition to swing. The timing shift between walking and running reflects therefore the difference in the relative duration of the stance phase in the two gaits

Modular control of limb movements during human locomotion

The idea that the CNS may control complex interactions by modular decomposition has received considerable attention. We explored this idea for human locomotion by examining limb kinematics. The coordination of limb segments during human locomotion has been shown to follow a planar law for walking at different speeds, directions, and levels of body unloading. We compared the coordination for different gaits. Eight subjects were asked to walk and run on a treadmill at different speeds or to walk, run, and hop over ground at a preferred speed. To explore various constraints on limb movements, we also recorded stepping over an obstacle, walking with the knees flexed, and air-stepping with body weight support. We found little difference among covariance planes that depended on speed, but there were differences that depended on gait. In each case, we could fit the planar trajectories with a weighted sum of the limb length and orientation trajectories. This suggested that limb length and orientation might provide independent predictors of limb coordination. We tested this further by having the subjects step, run, and hop in place, thereby varying only limb length and maintaining limb orientation fixed, and also by marching with knees locked to maintain limb length constant while varying orientation. The results were consistent with a modular control of limb kinematics where limb movements result from a superposition of separate length- and orientation-related angular covariance. The hypothesis finds support in the animal findings that limb proprioception may also be encoded in terms of these global limb parameters