During goal-directed locomotion, descending signals from supraspinal structures act through spinal interneuron pathways to effect modifications of muscle activity that are appropriate to the task requirements. Recent studies using decomposition methods suggest that this control might be facilitated by activating synergies organized at the level of the spinal cord. However, it is difficult to directly relate these mathematically defined synergies to the patterns of electromyographic activity observed in the original recordings. To address this issue, we have used a novel cluster analysis to make a detailed study of the organization of the synergistic patterns of muscle activity observed in the fore- and hindlimb during treadmill locomotion. The results show that the activity of a large number of forelimb muscles (26 bursts of activity from 18 muscles) can be grouped into 11 clusters on the basis of synchronous co-activation. Nine (9/11) of these clusters defined muscle activity during the swing phase of locomotion; these clusters were distributed in a sequential manner and were related to discrete behavioral events. A comparison with the synergies identified by linear decomposition methods showed some striking similarities between the synergies identified by the different methods. In the hindlimb, a simpler organization was observed, and a sequential activation of muscles similar to that observed in the forelimb during swing was less clear. We suggest that this organization of synergistic muscles provides a means by which descending signals could provide the detailed control of different muscle groups that is necessary for the flexible control of multi-articular movements.

It is well established that the motor cortex makes an important contribution to the control of visually guided gait modifications, such as those required to step over an obstacle. However, it is less clear how the descending cortical signal interacts with the interneuronal networks in the spinal cord to ensure that precise changes in limb trajectory are appropriately incorporated into the base locomotor rhythm. Here we suggest that subpopulations of motor cortical neurones, active sequentially during the step cycle, may regulate the activity of small groups of synergistic muscles, likewise active sequentially throughout the step cycle. These synergies, identified by a novel associative cluster analysis, are defined by periods of muscle activity that are coextensive with respect to the onset and offset of the EMG activity. Moreover, the synergies are sparse and are frequently composed of muscles acting around more than one joint. During gait modifications, we suggest that subpopulations of motor cortical neurones may modify the magnitude and phase of the EMG activity of all muscles contained within a given synergy. Different limb trajectories would be produced by differentially modifying the activity in each synergy thus providing a flexible substrate for the control of intralimb coordination during locomotion.

Psychophysical studies have reported an overestimation of limb position in the direction of movement during the early part of active movements. The main hypothesis tested in this study is that the overestimation results from a process of forward prediction of limb state driven by an efference copy of the outgoing motor command. This hypothesis predicts that position overestimation should decrease or disappear during passive movements, for which there should be no efference copy. Seven subjects were asked to remember and to report the perceived angle of their elbow joint at different times during active and passive movements. They showed a highly velocity-dependent overestimation of the elbow joint angle near the beginning of the movement in both active and passive trials. Toward the end of the movement, subjects showed a relatively velocity-independent underestimation of their elbow angle in all trials. Contrary to the prediction of the efference copy hypothesis, the amplitude and the velocity-dependent slope of the elbow angle overestimation were both greater during the early part of passive movements than active movements. This indicates that psychophysical evidence of early overestimation of arm position on its own is not a sufficient proof of forward prediction based on an efference copy, at least under the conditions of this study. Decreased errors during active movements suggest that an efference copy can improve the accuracy of state estimation during active movements. Error patterns seem to parallel the likely level of sensorimotor noise, suggesting a probabilistic mechanism for position estimation.

We examined the contribution of the motor cortex to the control of intralimb coordination during reaching in the standing cat. We recorded the activity of 151 pyramidal tract neurons (PTNs) in the forelimb representation of three cats during a task in which the cat reached forward from a standing position to press a lever. We simultaneously recorded the activity of muscles in the contralateral forelimb acting around each of the major joints. Cell activity was recorded with and without the presence of an obstacle requiring a modification of limb trajectory. The majority of the PTNs (134/151, 89%) modulated their discharge activity at some period of the reach while 84/151 (56%) exhibited a significant peak or trough of activity as the limb was transported from its initial position to the lever. These phasic changes of activity were distributed sequentially throughout the transport phase. A cluster analysis of muscle activity in two of the cats showed the presence of five muscle synergies during this transport period. One of the synergies was related to the lift of the paw from the support surface, two to flexion of the limb and dorsiflexion of the paw, one to preparation for contact with the lever, and one to the transport of the entire limb forward; a sixth synergy was activated during the lever press. An analysis of the phase of cell activity with respect to the phase of activity of muscles selected to represent each of these synergies showed that different populations of PTNs were activated sequentially and coincidentally with each synergy. We suggest that this sequential activation of populations of PTNs is compatible with a contribution to the initiation and modulation of functionally distinct groups of synergistic muscles and ultimately serves to ensure the appropriate multiarticular, intralimb coordination of the limb during reaching.

Recent studies have reported that human subjects show varying degrees of ability to use contextual cues to recall the motor skills required to compensate for different dynamic external force fields during arm movements. In particular, the subjects showed little or no ability to use color cues to adjust motor outputs in anticipation of the perturbing fields after limited periods of training that were sufficient to learn to compensate for the fields themselves. This is unexpected since humans and monkeys can use color cues to perform a wide range of visuomotor tasks. Here we show that a monkey with extensive practice compensating for viscous fields in an elbow-movement task can use associated color cues to adjust motor output in anticipation of an impending field before physically encountering it.

We tested the efficacy of color context cues during adaptation to dynamic force fields. Four groups of human subjects performed elbow flexion/extension movements to move a cursor between targets on a monitor while encountering a resistive (Vr) or assistive (Va) viscous force field. They performed two training sets of 256 trials daily, for 10 days. The monitor background color changed (red, green) every four successful trials but provided different degrees of force field context information to each group. For the irrelevant-cue groups, the color changed every four trials, but one group encountered only the Va field and the other only the Vr field. For the reliable-cue group, the force field alternated between Va and Vr each time the monitor changed color (Vr, red; Va, green). For the unreliable-cue group, the force field changed between Va and Vr pseudorandomly at each color change. All subjects made increasingly stereotyped movements over 10 training days. Reliable-cue subjects typically learned the association between color cues and fields and began to make predictive changes in motor output at each color change during the first day. Their performance continued to improve over the remaining days. Unreliable-cue subjects also improved their performance across training days but developed a strategy of probing the nature of the field at each color change by emitting a default motor response and then adjusting their motor output in subsequent trials. These findings show that subjects can extract explicit and implicit information from color context cues during force field adaptation.

We have previously described a modular organization of the locomotor step cycle in the cat in which a number of sparse synergies are activated sequentially during the swing phase of the step cycle (Krouchev et al., 2006). Here, we address how these synergies are modified during voluntary gait modifications. Data were analysed from 27 bursts of muscle activity (recorded from 18 muscles) recorded in the forelimb of the cat during locomotion. These were grouped into 10 clusters, or synergies, during unobstructed locomotion. Each synergy was comprised of only a small number of muscles bursts (sparse synergies), some of which included both proximal and distal muscles. Eight (8/10) of these synergies were active during the swing phase of locomotion. Synergies observed during the gait modifications were very similar to those observed during unobstructed locomotion. Constraining these synergies to be identical in both the lead (first forelimb to pass over the obstacle) and the trail (second limb) conditions allowed us to compare the changes in phase and magnitude of the synergies required to modify gait. In the lead condition, changes were observed particularly in those synergies responsible for transport of the limb and preparation for landing. During the trail condition, changes were particularly evident in those synergies responsible for lifting the limb from the ground at the onset of the swing phase. These changes in phase and magnitude were adapted to the size and shape of the obstacle over which the cat stepped. These results demonstrate that by modifying the phase and magnitude of a finite number of muscle synergies, each comprised of a small number of simultaneously active muscles, descending control signals could produce very specific modifications in limb trajectory during locomotion. We discuss the possibility that these changes in phase and magnitude could be produced by changes in the activity of neurones in the motor cortex.

Electrical stimulation (ES) devices interact with excitable neural tissue toward eliciting action potentials (AP’s) by specific current patterns. Low-energy ES prevents tissue damage and loss of specificity. Hence to identify optimal stimulation-current waveforms is a relevant problem, whose solution may have significant impact on the related medical (e.g. minimized side-effects) and engineering (e.g. maximized battery-life) efficiency. This has typically been addressed by simulation (of a given excitable-tissue model) and iterative numerical optimization with hard discontinuous constraints - e.g. AP’s are all-or-none phenomena. Such approach is computationally expensive, while the solution is uncertain - e.g. may converge to local-only energy-minima and be model-specific. We exploit the Least-Action Principle (LAP). First, we derive in closed form the general template of the membrane-potential’s temporal trajectory, which minimizes the ES energy integral over time and over any space-clamp ionic current model. From the given model we then obtain the specific energy-efficient current waveform, which is demonstrated to be globally optimal. The solution is model-independent by construction. We illustrate the approach by a broad set of example situations with some of the most popular ionic current models from the literature. The proposed approach may result in the significant improvement of solution efficiency: cumbersome and uncertain iteration is replaced by a single quadrature of a system of ordinary differential equations. The approach is further validated by enabling a general comparison to the conventional simulation and optimization results from the literature, including one of our own, based on finite-horizon optimal control. Applying the LAP also resulted in a number of general ES optimality principles. One such succinct observation is that ES with long pulse durations is much more sensitive to the pulse’s shape whereas a rectangular pulse is most frequently optimal for short pulse durations.