Changes of steady state activity in motor cortex consistent with the length-tension relation of muscle

Maintained Representations of the Ipsilateral and Contralateral Limbs during Bimanual Control in Primary Motor Cortex

Primary motor cortex (M1) almost exclusively controls the contralateral side of the body. However, M1 activity is also modulated during ipsilateral body movements. Previous work has shown that M1 activity related to the ipsilateral arm is independent of the M1 activity related to the contralateral arm. How do these patterns of activity interact when both arms move simultaneously? We explored this problem by training 2 monkeys (male, Macaca mulatta) in a postural perturbation task while recording from M1. Loads were applied to one arm at a time (unimanual) or both arms simultaneously (bimanual). We found 83% of neurons (n = 236) were responsive to both the unimanual and bimanual loads. We also observed a small reduction in activity magnitude during the bimanual loads for both limbs (25%). Across the unimanual and bimanual loads, neurons largely maintained their preferred load directions. However, there was a larger change in the preferred loads for the ipsilateral limb (∼25%) than the contralateral limb (∼9%). Lastly, we identified the contralateral and ipsilateral subspaces during the unimanual loads and found they captured a significant amount of the variance during the bimanual loads. However, the subspace captured more of the bimanual variance related to the contralateral limb (97%) than the ipsilateral limb (66%). Our results highlight that, even during bimanual motor actions, M1 largely retains its representations of the contralateral and ipsilateral limbs.SIGNIFICANCE STATEMENT Previous work has shown that primary motor cortex (M1) represents information related to the contralateral limb, its downstream target, but also reflects information related to the ipsilateral limb. Can M1 still represent both sources of information when performing simultaneous movements of the limbs? Here we record from M1 during a postural perturbation task. We show that activity related to the contralateral limb is maintained between unimanual and bimanual motor actions, whereas the activity related to the ipsilateral limb undergoes a small change between unimanual and bimanual motor actions. Our results indicate that two independent representations can be maintained and expressed simultaneously in M1.

Influence of joint position on synergistic muscle activity after fatigue of a single muscle head

INTRODUCTION

We investigated synergistic muscle activity after fatigue of a single muscle in different joint positions.

METHODS

Two experimental groups (n = 12 each) performed maximal voluntary contractions (MVCs) before and after fatiguing the gastrocnemius lateralis (GL), using neuromuscular electrical stimulation (NMES). Neuromuscular tests, including muscle activity during MVC, H-reflex, and twitch interpolation, were performed. One group completed the experiment in a knee-extended position with the second group in a knee-flexed position.

RESULTS

In the knee-flexed position, the muscle activity increased in non-stimulated synergistic muscles. In contrast, in the knee-extended position, muscle activity of the synergistic muscles remained unaltered. The MVC force remained unaltered in the flexed position and decreased in the extended position.

CONCLUSIONS

Synergistic muscles compensate for the fatigued muscle in the flexed position but not in the extended position. Compensation mechanisms seem to depend on joint position.

Perturbation-evoked responses in primary motor cortex are modulated by behavioral context

Corrective responses to external perturbations are sensitive to the behavioral task being performed. It is believed that primary motor cortex (M1) forms part of a transcortical pathway that contributes to this sensitivity. Previous work has identified two distinct phases in the perturbation response of M1 neurons, an initial response starting ∼20 ms after perturbation onset that does not depend on the intended motor action and a task-dependent response that begins ∼40 ms after perturbation onset. However, this invariant initial response may reflect ongoing postural control or a task-independent response to the perturbation. The present study tested these two possibilities by examining if being engaged in an ongoing postural task before perturbation onset modulated the initial perturbation response in M1. Specifically, mechanical perturbations were applied to the shoulder and/or elbow while the monkey maintained its hand at a central target or when it was watching a movie and not required to respond to the perturbation. As expected, corrective movements, muscle stretch responses, and M1 population activity in the late perturbation epoch were all significantly diminished in the movie task. Strikingly, initial perturbation responses (<40 ms postperturbation) remained the same across tasks, suggesting that the initial phase of M1 activity constitutes a task-independent response that is sensitive to the properties of the mechanical perturbation but not the goal of the ongoing motor task.

Motor cortex single-neuron and population contributions to compensation for multiple dynamic force fields

To elucidate how primary motor cortex (M1) neurons contribute to the performance of a broad range of different and even incompatible motor skills, we trained two monkeys to perform single-degree-of-freedom elbow flexion/extension movements that could be perturbed by a variety of externally generated force fields. Fields were presented in a pseudorandom sequence of trial blocks. Different computer monitor background colors signaled the nature of the force field throughout each block. There were five different force fields: null field without perturbing torque, assistive and resistive viscous fields proportional to velocity, a resistive elastic force field proportional to position and a resistive viscoelastic field that was the linear combination of the resistive viscous and elastic force fields. After the monkeys were extensively trained in the five field conditions, neural recordings were subsequently made in M1 contralateral to the trained arm. Many caudal M1 neurons altered their activity systematically across most or all of the force fields in a manner that was appropriate to contribute to the compensation for each of the fields. The net activity of the entire sample population likewise provided a predictive signal about the differences in the time course of the external forces encountered during the movements across all force conditions. The neurons showed a broad range of sensitivities to the different fields, and there was little evidence of a modular structure by which subsets of M1 neurons were preferentially activated during movements in specific fields or combinations of fields.

Motor cortical prediction of EMG: evidence that a kinetic brain-machine interface may be robust across altered movement dynamics

During typical movements, signals related to both the kinematics and kinetics of movement are mutually correlated, and each is correlated to some extent with the discharge of neurons in the primary motor cortex (M1). However, it is well known, if not always appreciated, that causality cannot be inferred from correlations. Although these mutual correlations persist, their nature changes with changing postural or dynamical conditions. Under changing conditions, only signals directly controlled by M1 can be expected to maintain a stable relationship with its discharge. If one were to rely on noncausal correlations for a brain-machine interface, its generalization across conditions would likely suffer. We examined this effect, using multielectrode recordings in M1 as input to linear decoders of both end point kinematics (position and velocity) and proximal limb myoelectric signals (EMG) during reaching. We tested these decoders across tasks that altered either the posture of the limb or the end point forces encountered during movement. Within any given task, the accuracy of the kinematic predictions tended to be somewhat better than the EMG predictions. However, when we used the decoders developed under one task condition to predict the signals recorded under different postural or dynamical conditions, only the EMG decoders consistently generalized well. Our results support the view that M1 discharge is more closely related to kinetic variables like EMG than it is to limb kinematics. These results suggest that brain-machine interface applications using M1 to control kinetic variables may prove to be more successful than the more standard kinematic approach.

Characterization of torque-related activity in primary motor cortex during a multijoint postural task

The present study examined neural activity in the shoulder/elbow region of primary motor cortex (M1) during a whole-limb postural task. By selectively imposing torques at the shoulder, elbow, or both joints we addressed how neurons represent changes in torque at a single joint, multiple joints, and their interrelation. We observed that similar proportions of neurons reflected changes in torque at the shoulder, elbow, and both joints and these neurons were highly intermingled across the cortical surface. Most torque-related neurons were reciprocally excited and inhibited (relative to their unloaded baseline activity) by opposing flexor and extensor torques at a single joint. Although coexcitation/coinhibition was occasionally observed at a single joint, it was rarely observed at both joints. A second analysis assessed the relationship between single-joint and multijoint activity. In contrast to our previous observations, we found that neither linear nor vector summation of single-joint activities could capture the breadth of neural responses to multijoint torques. Finally, we studied the neurons' directional tuning across all the torque conditions, i.e., in joint-torque space. Our population of M1 neurons exhibited a strong bimodal distribution of preferred-torque directions (PTDs) that was biased toward shoulder-extensor/elbow-flexor (whole-limb flexor) and shoulder-flexor/elbow-extensor (whole-limb extensor) torques. Notably, we recently observed a similar bimodal distribution of PTDs in a sample of proximal arm muscles. This observation illustrates the intimate relationship between M1 and the motor periphery.

On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional dynamic isometric force

The role of the motor cortex in the control of both the direction and magnitude of dynamic force, when both are allowed to vary in 3D, is not known. We recorded the activity of 504 cells in the motor cortex of two monkeys during a behavioral task in which the subjects used a manipulandum to vary both the direction and magnitude of isometric force in 3D space. The majority (86%) of cells active in the task related to the direction, a tiny number (2.5%) to the magnitude, and a moderate number (11.5%) to both the direction and magnitude of dynamic force output. Finally, we compared neural activity in the same population of neurons during dynamic and static force output and found that the relations to direction and magnitude were very similar in both epochs. Our results indicate that during dynamic force production, cells in the motor cortex are primarily concerned with specifying the direction of force. The magnitude signal is not prominent in motor cortex neurons, and in general, magnitude and direction of force are specified together. Furthermore, the data suggest that the control of static and dynamic motor systems is based, to a great extent, on a common control process.

Neuronal correlates of movement dynamics in the dorsal and ventral premotor area in the monkey

We investigated how neurons in the different motor areas of the frontal lobe reflect the movement dynamics, and how their neuronal activity undergoes plastic changes when monkeys adapt to perturbing forces (they learn new dynamics). Here we describe the results obtained in the dorsal premotor area (PMd) and ventral premotor area (PMv). Monkeys performed visually instructed, delayed reaching movements before, during and after exposure and adaptation to a viscous, curl force field. During movement planning (i.e., during an instructed delay that followed the cue and preceded the go signal), we found dynamics-related activity in PMd but not in PMv. A closer analysis revealed that the population of PMd reflected the dynamics of the upcoming movement increasingly over the course of the delay, starting from a kinematics-related signal. During movement execution, dynamics-related activity was present in both PMd and PMv. In this respect, the results for PMd were similar to that previously found for the supplementary motor area (SMA) whereas the results for PMv were more similar to that previously found for the primary motor cortex (M1). Plastic changes associated with the acquisition of new dynamics found in PMd and PMv were qualitatively similar to those previously observed in M1 and SMA. The ensemble of our experiments suggest a broader picture of the cortical control of movements, whereby multiple areas all contribute to the various sensorimotor processes, including "low" computations such as the movement dynamics, but also express a degree of specialization.

Systematic changes in motor cortex cell activity with arm posture during directional isometric force generation

We report here the activity of 96 cells in primate primary motor cortex (MI) during exertion of isometric forces at the hand in constant spatial directions, while the hand was at five to nine different spatial locations on a plane. The discharge of nearly all cells varied significantly with both hand location and the direction of isometric force before and during force-ramp generation as well as during static force-hold. In addition, nearly all cells displayed changes in the variation of their activity with force direction at different hand locations. This change in relationship was often expressed in part as a change in the cell's directional tuning at different hand locations. Cell directional tuning tended to shift systematically with hand location even though the direction of static force output at the hand remained constant. These directional effects were less pronounced before the onset of force output than after force onset. Cells also often showed planar modulations of discharge level with hand location. Sixteen proximal arm muscles showed similar effects, reflecting how hand location-dependent biomechanical factors altered their task-related activity. These findings indicate that MI single-cell activity does not covary exclusively with the level and direction of net force output at the hand and provides further evidence that MI contributes to the transformation between extrinsic and intrinsic representations of motor output during isometric force production.

Neuronal correlates of motor performance and motor learning in the primary motor cortex of monkeys adapting to an external force field

The primary motor cortex (M1) is known to control motor performance. Recent findings have also implicated M1 in motor learning, as neurons in this area show learning-related plasticity. In the present study, we analyzed the neuronal activity recorded in M1 in a force field adaptation task. Our goal was to investigate the neuronal reorganization across behavioral epochs (before, during, and after adaptation). Here we report two main findings. First, memory cells were present in two classes. With respect to the changes of preferred direction (Pd), these two classes complemented each other after readaptation. Second, for the entire neuronal population, the shift of Pd matched the shift observed for muscles. These results provide a framework whereby the activity of distinct neuronal subpopulations combines to subserve both functions of motor performance and motor learning.

Morphometry of Macaca mulatta forelimb. I. Shoulder and elbow muscles and segment inertial parameters

The present study examined the morphometric properties of the forelimb, including the inertial properties of the body segments and the morphometric parameters of 21 muscles spanning the shoulder and/or elbow joints of six Macaca mulatta and three M. fascicularis. Five muscle parameters are presented: optimal fascicle length (L(0)(M)), tendon slack length (L(S)(T)), physiological cross-sectional area (PCSA), pennation angle (alpha(0)), and muscle mass (m). Linear regressions indicate that muscle mass, and to a lesser extent PCSA, correlated with total body weight. Segment mass, center-of-mass, and the moment of inertia of the upper arm, forearm, and hand are also presented. Our data indicate that for some segments, radius of gyration (rho) predicts segment moment of inertia better than linear regressions based on total body weight. Key differences between the monkey and human forelimb are highlighted.

Online visual control of the arm

The psychophysical and cerebrocortical mechanisms in visually guided reaching movements and isometric force pulses are discussed. The results of psychophysical studies of pointing movements have demonstrated a tight coupling between the visual information and the direction of the movement, and those of studies of directed isometric force pulses have documented the sensitive dependence of the motor system on the continuous availability of visual information for the ongoing correction of directional deviations from the instructed direction. Recordings of the activity of single cells in the motor cortex and parietal areas 2 and 5 have revealed the same tight, online coupling between visual information and cell discharge, and have partially elucidated the neural mechanisms underlying this function at the cortical level.

Force and the motor cortex

The relation between the activity of cells in the motor cortex and static force has been studied extensively. Most studies have concentrated on the relation to the magnitude of force; this relation is more or less monotonic. The slope of the relation, however, shows considerable variation among different studies and seems to be inversely associated with the range of forces over which the cell activity has been studied. Cells in the motor cortex also show variation in activity with the direction of static force. When both the direction and the magnitude of static force are allowed to vary, a majority of cells show significant changes in activity with direction of force alone, an intermediate number relate to both direction and magnitude, while a small number relate purely to the magnitude. This suggests that the direction of static force can be controlled independently of its magnitude and that this directional signal is especially prominent in the motor cortex. In general, it has been more difficult to study the relations to dynamic force. There is a correlation between motor cortex cell activity and the rate of change of force. The direction of dynamic force is also an important determinant of cell activity. When both static and dynamic force output are required (for example, with arm movement in the presence of gravity) it is the dynamic signal that is most clearly reflected in motor cortex activity. The relations between motor cortex activity and static or dynamic force are not invariant, but may be modified by the behavioral context of the motor output.

Systematic changes in directional tuning of motor cortex cell activity with hand location in the workspace during generation of static isometric forces in constant spatial directions

We examined the activity of 46 proximal-arm-related cells in the primary motor cortex (MI) during a task in which a monkey uses the arm to exert isometric forces at the hand in constant spatial directions while the hand is in one of nine different spatial locations on a plane. The discharge rate of all 46 cells was significantly affected by both hand location and by the direction of static force during the final static-force phase of the task. In addition, all cells showed a significant interaction between force direction and hand location. That is, there was a significant modulation in the relationship between cell activity and the direction of exerted force as a function of hand location. For many cells, this modulation was expressed in part as a systematic arclike shift in the cell's directional tuning at the different hand locations, even though the direction of static force output at the hand remained constant. These effects of hand location in the workspace indicate that the discharge of single MI cells does not covary exclusively with the level and direction of force output at the hand. Sixteen proximal-arm-related muscles showed similar effects in the task, reflecting their dependence on various mechanical factors that varied with hand location. The parallel changes found for both MI cell activity and muscle activity for static force production at different hand locations are further evidence that MI contributes to the transformation between extrinsic and intrinsic representations of limb movement.

Force and the motor cortex

The relation between the activity of cells in the motor cortex and static force has been studied extensively. Most studies have concentrated on the relation to the magnitude of force; this relation is more or less monotonic. The slope of the relation, however, shows considerable variation among different studies and seems to be inversely associated with the range of forces over which the cell activity has been studied. Cells in the motor cortex also show variation in activity with the direction of static force. When both the direction and the magnitude of static force are allowed to vary, a majority of cells show significant changes in activity with direction of force alone, an intermediate number relate to both direction and magnitude, while a small number relate purely to the magnitude. This suggests that the direction of static force can be controlled independently of its magnitude and that this directional signal is especially prominent in the motor cortex. In general, it has been more difficult to study the relations to dynamic force. There is a correlation between motor cortex cell activity and the rate of change of force. The direction of dynamic force is also an important determinant of cell activity. When both static and dynamic force output are required (for example, with arm movement in the presence of gravity) it is the dynamic signal that is most clearly reflected in motor cortex activity. The relations between motor cortex activity and static or dynamic force are not invariant, but may be modified by the behavioral context of the motor output.

Reaching movements with similar hand paths but different arm orientations. I. Activity of individual cells in motor cortex

This study shows that the discharge of many motor cortical cells is strongly influenced by attributes of movement related to the geometry and mechanics of the arm and not only by spatial attributes of the hand trajectory. The activity of 619 directionally tuned cells was recorded from the motor cortex of two monkeys during reaching movements with the use of similar hand paths but two different arm orientations, in the natural parasagittal plane and abducted into the horizontal plane. Nearly all cells (588 of 619, 95%) showed statistically significant changes in activity between the two arm orientations [analysis of variance (ANOVA). P < 0.01]. A majority of cells showed a significant change in their overall level of activity (ANOVA, main effect of task, P < 0.01) between arm orientations before, during, and after movement. Many cells (433 of 619, 70%) also showed a significant change in the relation of their discharge with movement direction (ANOVA, task x direction interaction term, P < 0.01) during movement, including changes in the dynamic range of discharge with movement and changes in the directional preference of cells that were directionally tuned in both arm orientations. Similar effects were seen for the discharge of cells while the monkey maintained constant arm postures over the different peripheral targets with the use of different arm orientations. Repeated data files from the same cell with the use of the same arm orientation showed only small changes in the level of discharge or in directional tuning, suggesting that changes in cell discharge between arm orientations cannot be explained by random temporal variations in cell activity. The distribution of movement-related preferred directions of the whole sample differed between arm orientations, and also differed strongly between cells receiving passive input predominantly from the shoulder or elbow. The electromyographic activity of most prime mover muscles at the shoulder and elbow was also strongly affected by arm orientation, resulting in changes in overall level of activity and/or directional tuning that often resembled those of the proximal arm-related motor cortical cells. A mathematical model that represented movements in terms of movement direction centered on the hand could not account for any of the arm-orientation-related response changes seen in this task, whereas models in intrinsic parameter spaces of joint kinematics and joint torques predicted many of the effects.

Current issues in directional motor control

Many studies during the past 15 years have shown that the direction of motor output (movement or isometric force) is an important factor for neuronal activity in the motor cortex, both at the level of single cells and at the level of neuronal populations. Recent studies have investigated several new aspects of this problem including the effect of posture, the relations to time-varying movement parameters (for example, position, velocity and acceleration) and the cortical representation of memorized simple movements and complex-movement trajectories. Furthermore, the neural correlates of directional operations, such as mental rotation and memory-scanning of visuomotor directions, have also been investigated. In addition, neural networks have been used to model dynamic, time-varying, spatial motor trajectories.

The motor cortex and the coding of force

The relation of cellular activity in the motor cortex to the direction of two-dimensional isometric force was investigated under dynamic conditions in monkeys. A task was designed so that three force variables were dissociated: the force exerted by the subject, the net force, and the change in force. Recordings of neuronal activity in the motor cortex revealed that the activity of single cells was directionally tuned and that this tuning was invariant across different directions of a bias force. Cell activity was not related to the direction of force exerted by the subject, which changed drastically as the bias force changed. In contrast, the direction of net force, the direction of force change, and the visually instructed direction all remained quite invariant and congruent and could be the directional variables, alone or in combination, to which cell activity might relate.