Descending corticospinal control of intersegmental dynamics

Implicit motor sequence learning using three-dimensional reaching movements with the non-dominant left arm

Interlimb differences in reach control could impact the learning of a motor sequence that requires whole-arm movements. The purpose of this study was to investigate the learning of an implicit, 3-dimensional whole-arm sequence task with the non-dominant left arm compared to the dominant right arm. Thirty-one right-hand dominant adults completed two consecutive days of practice of a motor sequence task presented in a virtual environment with either their dominant right or non-dominant left arm. Targets were presented one-at-a-time alternating between Random and Repeated sequences. Task performance was indicated by the time to complete the sequence (response time), and kinematic measures (hand path distance, peak velocity) were used to examine how movements changed over time. While the Left Arm group was slower than the Right Arm group at baseline, both groups significantly improved response time with practice with the Left Arm group demonstrating greater gains. The Left Arm group improved performance by decreasing hand path distance (straighter path to targets) while the Right Arm group improved performance through a smaller decrease in hand path distance combined with increasing peak velocity. Gains made during practice on Day 1 were retained on Day 2 for both groups. Overall, individuals reaching with the non-dominant left arm learned the whole-arm motor sequence task but did so through a different strategy than individuals reaching with the dominant right arm. The strategy adopted for the learning of movement sequences that require whole-arm movements may be impacted by differences in reach control between the nondominant and dominant arms.

Muscle anatomy is reflected in the spatial organization of the spinal motoneuron pools

Neural circuits embed limb dynamics for motor control and sensorimotor integration. The somatotopic organization of motoneuron pools in the spinal cord may support these computations. Here, we tested if the spatial organization of motoneurons is related to the musculoskeletal anatomy. We created a 3D model of motoneuron locations within macaque spinal cord and compared the spatial distribution of motoneurons to the anatomical organization of the muscles they innervate. We demonstrated that the spatial distribution of motoneuron pools innervating the upper limb and the anatomical relationships between the muscles they innervate were similar between macaque and human species. Using comparative analysis, we found that the distances between motoneuron pools innervating synergistic muscles were the shortest, followed by those innervating antagonistic muscles. Such spatial organization can support the co-activation of synergistic muscles and reciprocal inhibition of antagonistic muscles. The spatial distribution of motoneurons may play an important role in embedding musculoskeletal dynamics.

Gravity-efficient motor control is associated with contraction-dependent intracortical inhibition

In humans, moving efficiently along the gravity axis requires shifts in muscular contraction modes. Raising the arm up involves shortening contractions of arm flexors, whereas the reverse movement can rely on lengthening contractions with the help of gravity. Although this control mode is universal, the neuromuscular mechanisms that drive gravity-oriented movements remain unknown. Here, we designed neurophysiological experiments that aimed to track the modulations of cortical, spinal, and muscular outputs of arm flexors during vertical movements with specific kinematics (i.e., optimal motor commands). We report a specific drop of corticospinal excitability during lengthening versus shortening contractions, with an increase of intracortical inhibition and no change in spinal motoneuron responsiveness. We discuss these contraction-dependent modulations of the supraspinal motor output in the light of feedforward mechanisms that may support gravity-tuned motor control. Generally, these results shed a new perspective on the neural policy that optimizes movement control along the gravity axis.

The human motor cortex contributes to gravity compensation to maintain posture and during reaching

The neural control of posture and movement is interdependent. During voluntary movement, the neural motor command is executed by the motor cortex through the corticospinal tract and its collaterals and subcortical targets. Here we address the question of whether the control mechanism for the postural adjustments at nonmoving joints is also involved in overcoming gravity at the moving joints. We used single-pulse transcranial magnetic stimulation to measure the corticospinal excitability in humans during postural and reaching tasks. We hypothesized that the corticospinal excitability is proportional to background muscle activity and the gravity-related joint moments during both static postures and reaching movements. To test this hypothesis, we used visual targets in virtual reality to instruct five postures and three movements with or against gravity. We then measured the amplitude and gain of motor evoked potentials in multiple arm and hand muscles at several phases of the reaching motion and during static postures. The stimulation caused motor evoked potentials in all muscles that were proportional to the muscle activity. During both static postures and reaching movements, the muscle activity and the corticospinal contribution to these muscles changed in proportion with the postural moments needed to support the arm against gravity, supporting the hypothesis. Notably, these changes happened not only in antigravity muscles. Altogether, these results provide evidence that the changes in corticospinal excitability cause muscle cocontraction that modulates limb stiffness. This suggests that the motor cortex is involved in producing postural adjustments that support the arm against gravity during posture maintenance and reaching.NEW & NOTEWORTHY Animal studies suggest that the corticospinal tract and its collaterals are crucial for producing postural adjustments that accompany movement in limbs other than the moving limb. Here we provide evidence for a similar control schema for both arm posture maintenance and gravity compensation during movement of the same limb. The observed interplay between the postural and movement control signals within the corticospinal tract may help explain the underlying neural motor deficits after stroke.

Linking Pain and Motor Control: Conceptualization of Movement Deficits in Patients With Painful Conditions

When people experience or expect pain, they move differently. Pain-altered movement strategies, collectively described here as pain-related movement dysfunction (PRMD), may persist well after pain resolves and, ultimately, may result in altered kinematics and kinetics, future reinjury, and disability. Although PRMD may manifest as abnormal movements that are often evident in clinical assessment, the underlying mechanisms are complex, engaging sensory-perceptual, cognitive, psychological, and motor processes. Motor control theories provide a conceptual framework to determine, assess, and target processes that contribute to normal and abnormal movement and thus are important for physical therapy and rehabilitation practice. Contemporary understanding of motor control has evolved from reflex-based understanding to a more complex task-dependent interaction between cognitive and motor systems, each with distinct neuroanatomic substrates. Though experts have recognized the importance of motor control in the management of painful conditions, there is no comprehensive framework that explicates the processes engaged in the control of goal-directed actions, particularly in the presence of pain. This Perspective outlines sensory-perceptual, cognitive, psychological, and motor processes in the contemporary model of motor control, describing the neural substrates underlying each process and highlighting how pain and anticipation of pain influence motor control processes and consequently contribute to PRMD. Finally, potential lines of future inquiry-grounded in the contemporary model of motor control-are outlined to advance understanding and improve the assessment and treatment of PRMD.

IMPACT

This Perspective proposes that approaching PRMD from a contemporary motor control perspective will uncover key mechanisms, identify treatment targets, inform assessments, and innovate treatments across sensory-perceptual, cognitive, and motor domains, all of which have the potential to improve movement and functional outcomes in patients with painful conditions.

Scaling of Joint Motion and Muscle Activation for 3-Dimensional Control of Reach Extent

This study investigated the scaling of upper arm kinematics, joint motion, and muscle activation for three-dimensional (3D) reaches to targets of increasing distance. Fifteen participants completed 108 total reaches to targets placed 7, 14, and 21 cm across midline. Peak velocity, acceleration, and time to peak velocity scaled to both target and movement distance. Shoulder and elbow excursion scaled to target distance and were highly coordinated. Anterior deltoid activation scaled to both target and movement distance in the early and late phases of reach control. Biceps and triceps activation scaled to movement distance primarily in the late phase. Scaling of these outcome variables provides a model for understanding the control of reach distance in a 3D environment.

Neurotransmitters, Cell Types, and Circuit Mechanisms of Motor Skill Learning and Clinical Applications

Animals acquire motor skills to better survive and adapt to a changing environment. The ability to learn novel motor actions without disturbing learned ones is essential to maintaining a broad motor repertoire. During motor learning, the brain makes a series of adjustments to build novel sensory–motor relationships that are stored within specific circuits for long-term retention. The neural mechanism of learning novel motor actions and transforming them into long-term memory still remains unclear. Here we review the latest findings with regard to the contributions of various brain subregions, cell types, and neurotransmitters to motor learning. Aiming to seek therapeutic strategies to restore the motor memory in relative neurodegenerative disorders, we also briefly describe the common experimental tests and manipulations for motor memory in rodents.

Shared internal models for feedforward and feedback control of arm dynamics in non-human primates

Previous work has shown that humans account for and learn novel properties or the arm's dynamics, and that such learning causes changes in both the predictive (i.e., feedforward) control of reaching and reflex (i.e., feedback) responses to mechanical perturbations. Here we show that similar observations hold in old-world monkeys (Macaca fascicularis). Two monkeys were trained to use an exoskeleton to perform a single-joint elbow reaching and to respond to mechanical perturbations that created pure elbow motion. Both of these tasks engaged robust shoulder muscle activity as required to account for the torques that typically arise at the shoulder when the forearm rotates around the elbow joint (i.e., intersegmental dynamics). We altered these intersegmental arm dynamics by having the monkeys generate the same elbow movements with the shoulder joint either free to rotate, as normal, or fixed by the robotic manipulandum, which eliminates the shoulder torques caused by forearm rotation. After fixing the shoulder joint, we found a systematic reduction in shoulder muscle activity. In addition, after releasing the shoulder joint again, we found evidence of kinematic aftereffects (i.e., reach errors) in the direction predicted if failing to compensate for normal arm dynamics. We also tested whether such learning transfers to feedback responses evoked by mechanical perturbations and found a reduction in shoulder feedback responses, as appropriate for these altered arm intersegmental dynamics. Demonstrating this learning and transfer in non-human primates will allow the investigation of the neural mechanisms involved in feedforward and feedback control of the arm's dynamics.

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

The sensorimotor integration during unconstrained reaching movements in the presence of variable environmental forces remains poorly understood. The objective of this study was to quantify how much the primary afferent activity of muscle spindles can contribute to shaping muscle coactivation patterns during reaching movements with complex dynamics. To achieve this objective, we designed a virtual reality task that guided healthy human participants through a set of planar reaching movements with controlled kinematic and dynamic conditions that were accompanied by variable muscle co-contraction. Next, we approximated the Ia afferent activity using a phenomenological model of the muscle spindle and muscle lengths derived from a musculoskeletal model. The parameters of the spindle model were altered systematically to evaluate the effect of fusimotor drive on the shape of the temporal profile of afferent activity during movement. The experimental and simulated data were analyzed with hierarchical clustering. We found that the pattern of co-activation of agonistic and antagonistic muscles changed based on whether passive forces in each movement played assistive or resistive roles in limb dynamics. The reaching task with assistive limb dynamics was associated with the most muscle co-contraction. In contrast, the simulated Ia afferent profiles were not changing between tasks and they were largely reciprocal with homonymous muscle activity. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce muscle co-contraction. These results largely rule out the static set and α-γ coactivation as the main types of fusimotor drive that transform the monosynaptic Ia afferent feedback into task-dependent co-contraction of antagonistic muscles. We speculate that another type of nonlinear transformation of Ia afferent signals that is independent of signals modulating the activity of α motoneurons is required for Ia afferent-based co-contraction. This transformation could either be applied through a complex nonlinear profile of fusimotor drive that is not yet experimentally observed or through presynaptic inhibition.

Learning New Feedforward Motor Commands Based on Feedback Responses

Learning a new motor task modifies feedforward (i.e., voluntary) motor commands and such learning also changes the sensitivity of feedback responses (i.e., reflexes) to mechanical perturbations [1-9]. For example, after people learn to generate straight reaching movements in the presence of an external force field or learn to reduce shoulder muscle activity when generating pure elbow movements with shoulder fixation, evoked stretch reflex responses to mechanical perturbations reflect the learning expressed during self-initiated reaching. Such a transfer from feedforward motor commands to feedback responses is thought to take place because of shared neural circuits at the level of the spinal cord, brainstem, and cerebral cortex [10-13]. The presence of shared neural resources also predicts the transfer from feedback responses to feedforward motor commands. Little is known about such a transfer presumably because it is relatively hard to elicit learning in reflexes without engaging associated voluntary responses following mechanical perturbations. Here, we demonstrate such transfer by leveraging two approaches to elicit stretch reflexes while minimizing engagement of voluntary motor responses in the learning process: applying very short mechanical perturbations [14-19] and instructing participants to not respond to them [20-26]. Taken together, our work shows that transfer between feedforward and feedback control is bidirectional, furthering the notion that these processes share common neural circuits that underlie motor learning and transfer.

Generalizing movement patterns following shoulder fixation

Generalizing newly learned movement patterns beyond the training context is challenging for most motor learning situations. Here we tested whether learning of a new physical property of the arm during self-initiated reaching generalizes to new arm configurations. Human participants performed a single-joint elbow reaching task and/or countered mechanical perturbations that created pure elbow motion with the shoulder joint free to rotate or locked by the manipulandum. With the shoulder free, we found activation of shoulder extensor muscles for pure elbow extension trials, appropriate for countering torques that arise at the shoulder due to forearm rotation. After locking the shoulder joint, we found a partial reduction in shoulder muscle activity, appropriate because locking the shoulder joint cancels the torques that arise at the shoulder due to forearm rotation. In our first three experiments, we tested whether and to what extent this partial reduction in shoulder muscle activity generalizes when reaching in different situations: 1) different initial shoulder orientation, 2) different initial elbow orientation, and 3) different reach distance/speed. We found generalization for the different shoulder orientation and reach distance/speed as measured by a reliable reduction in shoulder activity in these situations but no generalization for the different elbow orientation. In our fourth experiment, we found that generalization is also transferred to feedback control by applying mechanical perturbations and observing reflex responses in a distinct shoulder orientation. These results indicate that partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of arm dynamics.NEW & NOTEWORTHY Here we show that partially learning to reduce shoulder muscle activity following shoulder fixation generalizes to other movement conditions, but it does not generalize globally. These findings suggest that the partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of the arm's dynamics.

Corticomotor Excitability of Gluteus Maximus Is Associated with Hip Biomechanics During a Single-Leg Drop-Jump

The purpose of this study was to determine the association between corticomotor excitability (CME) of gluteus maximus (GM) and hip biomechanics during a single-leg drop-jump task. Thirty-two healthy individuals participated. The slope of the input-output curve (IOC) obtained from transcranial magnetic stimulation was used to assess CME of GM. The average hip extensor moment and peak hip flexion angle during the stance phase of the drop jump task was calculated. The slope of the IOC of GM was found to be a predictor of the average hip extensor moment (r² = 0.18, p = 0.016) and peak hip flexion angle (r² = 0.20, p = 0.01). Our results demonstrate that greater functional use of the hip was associated with enhanced descending neural drive of GM.

Feedforward and Feedback Control Share an Internal Model of the Arm's Dynamics

Recent work has shown that, when countering external forces, the nervous system adjusts not only predictive (i.e., feedforward) control of reaching but also reflex (i.e., feedback) responses to mechanical perturbations. Here we show that altering the physical properties of the arm (i.e., intersegmental dynamics) causes the nervous system to adjust feedforward control and that this learning transfers to feedback responses even though the latter were never directly trained. Forty-five human participants (30 females) performed a single-joint elbow reaching task and countered mechanical perturbations that created pure elbow motion. In our first experiment, we altered intersegmental dynamics by asking participants to generate pure elbow movements when the shoulder joint was either free to rotate or locked by the robotic manipulandum. With the shoulder unlocked, we found robust activation of shoulder flexor muscles for pure elbow flexion trials, as required to counter the interaction torques that arise at the shoulder because of forearm rotation. After locking the shoulder joint, which cancels these interaction torques, we found a substantial reduction in shoulder muscle activity over many trials. In our second experiment, we tested whether such learning transfers to feedback control. Mechanical perturbations applied to the arm with the shoulder unlocked revealed that feedback responses also account for intersegmental dynamics. After locking the shoulder joint, we found a substantial reduction in shoulder feedback responses, as appropriate for the altered intersegmental dynamics. Our work suggests that feedforward and feedback control share an internal model of the arm's dynamics.SIGNIFICANCE STATEMENT Here we show that altering the physical properties of the arm causes people to learn new motor commands and that this learning transfers to their reflex responses to unexpected mechanical perturbations, even though the reflex responses were never directly trained. Our results suggest that feedforward motor commands and reflex responses share an internal model of the arm's dynamics.

Contribution of interaction torques during dart throwing: Differences between novices and experts

We examined if experts and novices show different utilization of the torque components impulses during dart throwing. Participants threw darts continuously at a dartboard aiming for the centre (target bull's eye). The upper-limb joint torque impulses were obtained through inverse dynamics with anthropometric and motion capture data as input. Depending on the joint degree of freedom (DOF) and movement phase (acceleration and follow-through), three main strategies of net torque (NET) impulse generation through joint muscle (MUS) and interaction (INT) torque impulses were highlighted. Firstly, our results showed that the elbow flexion-extension DOF leads the movement according to the joint leading hypothesis. Then, considering the acceleration phase, the analysis revealed differences in torque impulse decomposition between expert and novices. For the glenohumeral (GH) joint abduction-adduction and for wrist flexion, the INT torque impulse contributed positively to NET joint torque impulse in the group of experts unlike novices. This allowed to lower the necessary MUS torque impulse at these DOFs. Also, GH axial rotation was actively controlled by muscle torque impulse in the group of experts. During the follow-through, the experts used the INT torque impulse more proficiently than novices to break the elbow extension. The comparison between experts and novices through inverse dynamics document the link between the exploitation of interaction torques impulses and expertise in dart throwing for which the main objective is precision rather than velocity.

Compensating for intersegmental dynamics across the shoulder, elbow, and wrist joints during feedforward and feedback control

Moving the arm is complicated by mechanical interactions that arise between limb segments. Such intersegmental dynamics cause torques applied at one joint to produce movement at multiple joints, and in turn, the only way to create single joint movement is by applying torques at multiple joints. We investigated whether the nervous system accounts for intersegmental limb dynamics across the shoulder, elbow, and wrist joints during self-initiated planar reaching and when countering external mechanical perturbations. Our first experiment tested whether the timing and amplitude of shoulder muscle activity account for interaction torques produced during single-joint elbow movements from different elbow initial orientations and over a range of movement speeds. We found that shoulder muscle activity reliably preceded movement onset and elbow agonist activity, and was scaled to compensate for the magnitude of interaction torques arising because of forearm rotation. Our second experiment tested whether elbow muscles compensate for interaction torques introduced by single-joint wrist movements. We found that elbow muscle activity preceded movement onset and wrist agonist muscle activity, and thus the nervous system predicted interaction torques arising because of hand rotation. Our third and fourth experiments tested whether shoulder muscles compensate for interaction torques introduced by different hand orientations during self-initiated elbow movements and to counter mechanical perturbations that caused pure elbow motion. We found that the nervous system predicted the amplitude and direction of interaction torques, appropriately scaling the amplitude of shoulder muscle activity during self-initiated elbow movements and rapid feedback control. Taken together, our results demonstrate that the nervous system robustly accounts for intersegmental dynamics and that the process is similar across the proximal to distal musculature of the arm as well as between feedforward (i.e., self-initiated) and feedback (i.e., reflexive) control.NEW & NOTEWORTHY Intersegmental dynamics complicate the mapping between applied joint torques and the resulting joint motions. We provide evidence that the nervous system robustly predicts these intersegmental limb dynamics across the shoulder, elbow, and wrist joints during reaching and when countering external perturbations.

Long-latency reflexes of elbow and shoulder muscles suggest reciprocal excitation of flexors, reciprocal excitation of extensors, and reciprocal inhibition between flexors and extensors

Postural corrections of the upper limb are required in tasks ranging from handling an umbrella in the changing wind to securing a wriggling baby. One complication in this process is the mechanical interaction between the different segments of the arm where torque applied at one joint induces motion at multiple joints. Previous studies have shown the long-latency reflexes of shoulder muscles (50-100 ms after a limb perturbation) account for these mechanical interactions by integrating information about motion of both the shoulder and elbow. It is less clear whether long-latency reflexes of elbow muscles exhibit a similar capability and what is the relation between the responses of shoulder and elbow muscles. The present study utilized joint-based loads tailored to the subjects' arm dynamics to induce well-controlled displacements of their shoulder and elbow. Our results demonstrate that the long-latency reflexes of shoulder and elbow muscles integrate motion from both joints: the shoulder and elbow flexors respond to extension at both joints, whereas the shoulder and elbow extensors respond to flexion at both joints. This general pattern accounts for the inherent flexion-extension coupling of the two joints arising from the arm's intersegmental dynamics and is consistent with spindle-based reciprocal excitation of shoulder and elbow flexors, reciprocal excitation of shoulder and elbow extensors, and across-joint inhibition between the flexors and extensors.

Cortical and corticospinal output modulations during reaching movements with varying directions and magnitudes of interaction torques

The neural command required to coordinate a multi-joint movement is inherently complex. During multi-joint movement of the limb, the force created from movement at one joint may create a torque at a second joint known as an interaction torque. Interaction torques may be assistive or resistive thereby aiding or opposing the motion of the second joint, respectively. For movement to be effectively controlled, the central nervous system should modulate neural output to the muscles to appropriately account for interaction torques. The present study examined the neural output from the primary motor cortex before and during reaching movements that required different combinations of assistive and resistive interaction torques occurring at the shoulder and elbow joints. Using transcranial magnetic stimulation to probe neural output from the primary motor cortex, results indicate that corticospinal output controlling the upper arm is related to resistive interaction torques occurring at the shoulder joint. Further, cortical output to bi-articular muscles is associated with interaction torque and this may be driven by the fact that these muscles are in an advantageous position to control torques produced between inter-connection segments. Humans have a tendency to avoid reaching movements that involve resistive interaction torques and this may be driven by the requirement of increased neural output associated with these movements.

Multifunctional Setup for Studying Human Motor Control Using Transcranial Magnetic Stimulation, Electromyography, Motion Capture, and Virtual Reality

The study of neuromuscular control of movement in humans is accomplished with numerous technologies. Non-invasive methods for investigating neuromuscular function include transcranial magnetic stimulation, electromyography, and three-dimensional motion capture. The advent of readily available and cost-effective virtual reality solutions has expanded the capabilities of researchers in recreating "real-world" environments and movements in a laboratory setting. Naturalistic movement analysis will not only garner a greater understanding of motor control in healthy individuals, but also permit the design of experiments and rehabilitation strategies that target specific motor impairments (e.g. stroke). The combined use of these tools will lead to increasingly deeper understanding of neural mechanisms of motor control. A key requirement when combining these data acquisition systems is fine temporal correspondence between the various data streams. This protocol describes a multifunctional system's overall connectivity, intersystem signaling, and the temporal synchronization of recorded data. Synchronization of the component systems is primarily accomplished through the use of a customizable circuit, readily made with off the shelf components and minimal electronics assembly skills.

An adaptive spinal-like controller: tunable biomimetic behavior for a robotic limb

Background

Spinal-like regulators have recently been shown to support complex behavioral patterns during volitional goal-oriented reaching paradigms. We use an interpretation of the adaptive spinal-like controller as inspiration for the development of a controller for a robotic limb. It will be demonstrated that a simulated robot arm with linear actuators can achieve biological-like limb movements. In addition, it will be shown that programmability in the regulator enables independent spatial and temporal changes to be defined for movement tasks, downstream of central commands using sensory stimuli. The adaptive spinal-like controller is the first to demonstrate such behavior for complex motor behaviors in multi-joint limb movements.

Methods

The controller is evaluated using a simulated robotic apparatus and three goal-oriented reaching paradigms: 1) shaping of trajectory profiles during reaching; 2) sensitivity of trajectories to sudden perturbations; 3) reaching to a moving target. The experiments were designed to highlight complex motor tasks that are omitted in earlier studies, and important for the development of improved artificial limb control.

Results

In all three cases the controller was able to reach the targets without a priori planning of end-point or segmental motor trajectories. Instead, trajectory spatio-temporal dynamics evolve from properties of the controller architecture using the spatial error (vector distance to goal). Results show that curvature amplitude in hand trajectory paths are reduced by as much as 98% using simple gain scaling techniques, while adaptive network behavior allows the regulator to successfully adapt to perturbations and track a moving target. An important observation for this study is that all motions resemble human-like movements with non-linear muscles and complex joint mechanics.

Conclusions

The controller shows that it can adapt to various behavioral contexts which are not included in previous biomimetic studies. The research supplements an earlier study by examining the tunability of the spinal-like controller for complex reaching tasks. This work is a step toward building more robust controllers for powered artificial limbs.

Spinal circuits can accommodate interaction torques during multijoint limb movements

The dynamic interaction of limb segments during movements that involve multiple joints creates torques in one joint due to motion about another. Evidence shows that such interaction torques are taken into account during the planning or control of movement in humans. Two alternative hypotheses could explain the compensation of these dynamic torques. One involves the use of internal models to centrally compute predicted interaction torques and their explicit compensation through anticipatory adjustment of descending motor commands. The alternative, based on the equilibrium-point hypothesis, claims that descending signals can be simple and related to the desired movement kinematics only, while spinal feedback mechanisms are responsible for the appropriate creation and coordination of dynamic muscle forces. Partial supporting evidence exists in each case. However, until now no model has explicitly shown, in the case of the second hypothesis, whether peripheral feedback is really sufficient on its own for coordinating the motion of several joints while at the same time accommodating intersegmental interaction torques. Here we propose a minimal computational model to examine this question. Using a biomechanics simulation of a two-joint arm controlled by spinal neural circuitry, we show for the first time that it is indeed possible for the neuromusculoskeletal system to transform simple descending control signals into muscle activation patterns that accommodate interaction forces depending on their direction and magnitude. This is achieved without the aid of any central predictive signal. Even though the model makes various simplifications and abstractions compared to the complexities involved in the control of human arm movements, the finding lends plausibility to the hypothesis that some multijoint movements can in principle be controlled even in the absence of internal models of intersegmental dynamics or learned compensatory motor signals.

A preferred pattern of joint coordination during arm movements with redundant degrees of freedom

Redundancy of degrees of freedom (DOFs) during natural human movements is a central problem of motor control research. This study tests a novel interpretation that during arm movements, the DOF redundancy is used to support a preferred, simplified joint control pattern that consists of rotating either the shoulder or elbow actively and the other (trailing) joint predominantly passively by interaction and gravitational torques. We previously revealed the preference for this control pattern during nonredundant horizontal arm movements. Here, we studied whether this preference persists during movements with redundant DOFs and the redundancy is used to enlarge the range of directions in which this control pattern can be utilized. A free-stroke drawing task was performed that involved production of series of horizontal center-out strokes in randomly selected directions. Two conditions were used, with the arm's joints unconstrained (U) and constrained (C) to the horizontal plane. In both conditions, directional preferences were revealed and the simplified control pattern was used in the preferred and not in nonpreferred directions. The directional preferences were weaker and the range of preferred directions was wider in the U condition, with higher percentage of strokes performed with the simplified control pattern. This advantage was related to the usage of additional DOFs. We discuss that the simplified pattern may represent a feedforward control strategy that reduces the challenge of joint coordination caused by signal-dependent noise during movement execution. The results suggest a possibility that the simplified pattern is used during the majority of natural, seemingly complex arm movements.

Immediate compensation for variations in self-generated Coriolis torques related to body dynamics and carried objects

We have previously shown that the Coriolis torques that result when an arm movement is performed during torso rotation do not affect movement trajectory. Our purpose in the present study was to examine whether torso motion-induced Coriolis and other interaction torques are counteracted during a turn and reach (T&R) movement when the effective mass of the hand is augmented, and whether the dominant arm has an advantage in coordinating intersegmental dynamics as predicted by the dynamic dominance hypothesis (Sainburg RL. Exp Brain Res 142: 241-258, 2002). Subjects made slow and fast T&R movements in the dark to just extinguished targets with either arm, while holding or not holding a 454-g object. Movement endpoints were equally accurate at both speeds, with either hand, and in both weight conditions, but subjects tended to angularly undershoot and produce more variable endpoints for targets requiring greater torso rotation. There were no changes in endpoint accuracy or trajectory deviation over repeated movements. The dominant right arm was more stable in its control of trajectory direction across targets, whereas the nondominant left arm had an improved ability to stop accurately on the target for higher levels of interaction torques. The trajectories to more eccentric targets were straighter when performed at higher speeds but slightly more deviated when subjects held the weight. Subjects did not slow their torso velocity or change the timing of the arm and torso velocities when holding the weight, although there was a slight decrease in their hand velocity relative to the torso. The delay between the onsets of torso and finger movements was almost twice as large for the right arm than the left, suggesting the right arm was better able to account for torso rotation in the arm movement. Holding the weight increased the peak Coriolis torque by 40% at the shoulder and 45% at the elbow and, for the most eccentric target, increased the peak net torque by 12% at the shoulder and 34% at the elbow. In accordance with Sainburg's dynamic dominance hypothesis, the right arm exhibited an advantage for coordinating intersegmental dynamics, showing a more stable finger velocity in relation to the torso across targets, decreasing error variability with movement speed, and more synchronized peaks of finger relative and torso angular velocities in conditions with greater joint torque requirements. The arm used had little effect on the movement path and the magnitude of the joint torques in any of the conditions. These results indicate that compensations for forthcoming Coriolis torque variations take into account the dynamic properties of the body and of external objects, as well as the planned velocities of the torso and arm.

Similarities in the neural control of the shoulder and elbow joints belie their structural differences

Movement of the hand in three dimensional space is primarily controlled by the orientation of the shoulder and elbow complexes. Due to discrepancies in proprioceptive acuity, overlap in motor cortex representation and grossly different anatomies between these joints, we hypothesized that there would be differences in the accuracy of aimed movements between the two joints. Fifteen healthy young adults were tested under four conditions – shoulder motion with the elbow constrained and unconstrained, and elbow motion with the shoulder constrained and unconstrained. End point target locations for each joint were set to coincide with joint excursions of 10, 20 or 30 degrees of either the shoulder or elbow joint. Targets were presented in a virtual reality environment. For the constrained condition, there were no significant differences in angular errors between the two joints, suggesting that the central nervous system represents linked segment models of the limb in planning and controlling movements. For the unconstrained condition, although angle errors were higher, hand position errors remained the same as those of the constrained trials. These results support the idea that the CNS utilizes abundant degrees of freedom to compensate for the potentially different contributions to end-point errors introduced by each joint.

The modulatory influence of end-point controllability on decisions between actions

Recent work has shown that human subjects are able to predict the biomechanical ease of potential reaching movements and use these predictions to influence their choices. Here, we examined how reach decisions are influenced by specific biomechanical factors related to the control of end-point stability, such as aiming accuracy or stopping control. Human subjects made free choices between two potential reaching movements that varied in terms of path distance and biomechanical cost in four separate blocks that additionally varied two constraints: the width of the targets (narrow or wide) and the requirement of stopping in them. When movements were unconstrained (very wide targets and no requirement of stopping), subjects' choices were strongly biased toward directions aligned with the direction of maximal mobility. However, as the movements became progressively constrained, factors related to the control of the end point gained relevance, thus reducing this bias. This demonstrates that, before movement onset, constraints such as stopping and aiming participate in a remarkably adaptive and flexible action selection process that trades off the advantage of moving along directions of maximal mobility for unconstrained movements against exploiting biomechanical anisotropies to facilitate control of end-point stability whenever the movement constraints require it. These results support a view of decision making between motor actions as a highly context-dependent gradual process in which the subjective desirability of potential actions is influenced by their dynamic properties in relation to the intrinsic properties of the motor apparatus.

Fast corrective responses are evoked by perturbations approaching the natural variability of posture and movement tasks

A wealth of studies highlight the importance of rapid corrective responses during voluntary motor tasks. These studies used relatively large perturbations to evoke robust muscle activity. Thus it remains unknown whether these corrective responses (latency 20–100 ms) are evoked at perturbation levels approaching the inherent variability of voluntary control. To fill this gap, we examined responses for large to small perturbations applied while participants either performed postural or reaching tasks. To address multijoint corrective responses, we induced various amounts of single-joint elbow motion with scaled amounts of combined elbow and shoulder torques. Indeed, such perturbations are known to elicit a response at the unstretched shoulder muscle, which reflects an internal model of arm intersegmental dynamics. Significant muscle responses were observed during both postural control and reaching, even when perturbation-related joint angle, velocity, and acceleration overlapped in distribution with deviations encountered in unperturbed trials. The response onsets were consistent across the explored range of perturbation loads, with short-latency onset for the muscles spanning the elbow joints (20–40 ms), and long-latency for shoulder muscles (onset > 45 ms). In addition, the evoked activity was strongly modulated by perturbation magnitude. These results suggest that multijoint responses are not specifically engaged to counter motor errors that exceed a certain threshold. Instead, we suggest that these corrective processes operate continuously during voluntary motor control.

Dorsal premotor cortex is involved in switching motor plans

Previous studies have shown that neural activity in primate dorsal premotor cortex (PMd) can simultaneously represent multiple potential movement plans, and that activity related to these movement options is modulated by their relative subjective desirability. These findings support the hypothesis that decisions about actions are made through a competition within the same circuits that guide the actions themselves. This hypothesis further predicts that the very same cells that guide initial decisions will continue to update their activities if an animal changes its mind. For example, if a previously selected movement option suddenly becomes unavailable, the correction will be performed by the same cells that selected the initial movement, as opposed to some different group of cells responsible for online guidance. We tested this prediction by recording neural activity in the PMd of a monkey performing an instructed-delay reach selection task. In the task, two targets were simultaneously presented and their border styles indicated whether each would be worth 1, 2, or 3 juice drops. In a random subset of trials (FREE), the monkey was allowed a choice while in the remaining trials (FORCED) one of the targets disappeared at the time of the GO signal. In FORCED-LOW trials the monkey was forced to move to the less valuable target and started moving either toward the new target (Direct) or toward the target that vanished and then curved to reach the remaining one (Curved). Prior to the GO signal, PMd activity clearly reflected the monkey's subjective preference, predicting his choices in FREE trials even with equally valued options. In FORCED-LOW trials, PMd activity reflected the switch of the monkey's plan as early as 100 ms after the GO signal, well before movement onset (MO). This confirms that the activity is not related to feedback from the movement itself, and suggests that PMd continues to participate in action selection even when the animal changes its mind on-line. These findings were reproduced by a computational model suggesting that switches between action plans can be explained by the same competition process responsible for initial decisions.

Are we ready for a natural history of motor learning?

Here we argue that general principles with regard to the contributions of the cerebellum, basal ganglia, and primary motor cortex to motor learning can begin to be inferred from explicit comparison across model systems and consideration of phylogeny. Both the cerebellum and the basal ganglia have highly conserved circuit architecture in vertebrates. The cerebellum has consistently been shown to be necessary for adaptation of eye and limb movements. The precise contribution of the basal ganglia to motor learning remains unclear but one consistent finding is that they are necessary for early acquisition of novel sequential actions. The primary motor cortex allows independent control of joints and construction of new movement synergies. We suggest that this capacity of the motor cortex implies that it is a necessary locus for motor skill learning, which we argue is the ability to execute selected actions with increasing speed and precision.

Interlimb differences of directional biases for stroke production

Directional preferences during center-out horizontal shoulder-elbow movements were previously characterized for the dominant arm. These preferences were attributed to a tendency to actively accelerate one joint, while exploiting largely passive motion at the other joint. Since the non-dominant arm is known for inefficient coordination of inter-segmental dynamics, here we hypothesized that directional preferences would differ between the arms. A center-out free-stroke drawing task was used that allowed freedom in the selection of movement directions. The task was performed both with and without a secondary cognitive task that has been shown to increase directional biases of the dominant arm. Mirror-symmetrical directional preferences were observed in both arms, with similar bias strength and secondary task effects. The preferred directions were characterized by maximal exploitation of interaction torques for movement production, but only in the dominant arm. The non-dominant arm failed to benefit from interaction torques. The results point to a hierarchical architecture of control. At the higher level, a movement capable to perform the task while satisfying preferences in joint control is specified through forward dynamic transformations. This process is mediated for both arms from a common neural network adapted to the dominant arm and, specifically, to its ability to exploit interaction torques. Dynamic transformations that determine actual control commands are specified at the lower level of control. An alternative interpretation that strokes might be planned evenly across directions, and biases emerge during movement execution due to anisotropic resistance of intrinsic factors that do not depend on arm dominance is also discussed.