Neuromuscular and biomechanical factors codetermine the solution to motor redundancy in rhythmic multijoint arm movement

How the CNS deals with the issue of motor redundancy remains a central question for motor control research. Here we investigate the means by which neuromuscular and biomechanical factors interact to resolve motor redundancy in rhythmic multijoint arm movements. We used a two-df motorised robot arm to manipulate the dynamics of rhythmic flexion-extension (FE) and supination-pronation (SP) movements at the elbow-joint complex. Participants were required to produce rhythmic FE and SP movements, either in isolation, or in combination (at the phase relationship of their choice), while we recorded the activity of key bi-functional muscles. When performed in combination, most participants spontaneously produced an in-phase pattern of coordination in which flexion is synchronised with supination. The activity of the Biceps Brachii (BB), the strongest arm muscle which also has the largest moment arms in both flexion and supination was significantly higher for FE and SP performed in combination than in isolation, suggesting optimal exploitation of the mechanical advantage of this muscle. In a separate condition, participants were required to produce a rhythmic SP movement while a rhythmic FE movement was imposed by the motorised robot. Simulations based upon a musculoskeletal model of the arm demonstrated that in this context, the most efficient use of the force-velocity relationship of BB requires that an anti-phase pattern of coordination (flexion synchronized with pronation) be produced. In practice, the participants maintained the in-phase behavior, and BB activity was higher than for SP performed in isolation. This finding suggests that the neural organisation underlying the exploitation of bifunctional muscle properties, in the natural context, constrains the system to maintain the

Influence of predominant patterns of coordination on the exploitation of interaction torques in a two-joint rhythmic arm movement

In this study we investigate the coordination between rhythmic flexion-extension (FE) and supination-pronation (SP) movements at the elbow joint-complex, while manipulating the intersegmental dynamics by means of a 2-degrees of freedom (df) robot arm. We hypothesized that constraints imposed by the structure of the neuromuscular-skeletal system would (1) result in predominant pattern(s) of coordination in the absence of interaction torques and (2) influence the capabilities of participants to exploit artificially induced interaction torques. Two experiments were conducted in which different conditions of interaction torques were applied on the SP-axis as a function of FE movements. These conditions promoted different patterns of coordination between the 2-df. Control trials conducted in the absence of interaction torques revealed that both the in-phase (supination synchronized with flexion) and the anti-phase (pronation synchronized with flexion) patterns were spontaneously established by participants. The predominance of these patterns of coordination is explained in terms of the mechanical action of bi-articular muscles acting at the elbow joint-complex, and in terms of the reflexes that link the activity of the muscles involved. Results obtained in the different conditions of interaction torques revealed that those neuromuscular-skeletal constraints either impede or favor the exploitation of intersegmental dynamics depending on the context. Interaction torques were indeed found to be exploited to a greater extent in conditions in which the profiles of interaction torques favored one of the two predominant patterns of coordination (i.e., in-phase or anti-phase) as opposed to other patterns of coordination (e.g., 90 degrees or 270 degrees). Those results are discussed in relation to recent studies reporting exploitation of interaction torques in the context of rhythmic movements.

Neuromuscular-skeletal origins of predominant patterns of coordination in a rhythmic two-joint arm movement

The authors tested for predominant patterns of coordination in the combination of rhythmic flexion-extension (FE) and supination-pronation (SP) at the elbow-joint complex. Participants (N = 10) spontaneously established in-phase (supination synchronized with flexion) and antiphase (pronation synchronized with flexion) patterns. In addition, the authors used a motorized robot arm to generate involuntary SP movements with different phase relations with respect to voluntary FE. The involuntarily induced in-phase pattern was accentuated and was more consistent than other patterns. That result provides evidence that the predominance of the in-phase pattern originates in the influence of neuro-muscular-skeletal constraints rather than in a preference dictated by perceptual-cognitive factors implicated in voluntary control. Neuromuscular-skeletal constraints involved in the predominance of the in-phase and the antiphase patterns are discussed.

The Control of Human Arm Movement Models and Mechanical Constraints

A serial-link manipulator may form a mobile closed kinematic chain when interacting with the environment, if it is redundant with respect to the task degrees of freedom (DOFs) at the endpoint. If the mobile closed chain assumes a number of configurations, then loop consistency equations permit the manipulator and task kinematics to be calibrated simultaneously using only the joint angle readings; endpoint sensing is not required. Example tasks include a fixed endpoint (0 DOF task), the opening of a door (1 DOF task), and point contact (3 DOF task). Identifiability conditions are derived for these various tasks.

Influence of predominant patterns of coordination on the exploitation of interaction torques in a two-joint rhythmic arm movement

In this study we investigate the coordination between rhythmic flexion-extension (FE) and supination-pronation (SP) movements at the elbow joint-complex, while manipulating the intersegmental dynamics by means of a 2-degrees of freedom (df) robot arm. We hypothesized that constraints imposed by the structure of the neuromuscular-skeletal system would (1) result in predominant pattern(s) of coordination in the absence of interaction torques and (2) influence the capabilities of participants to exploit artificially induced interaction torques. Two experiments were conducted in which different conditions of interaction torques were applied on the SP-axis as a function of FE movements. These conditions promoted different patterns of coordination between the 2-df. Control trials conducted in the absence of interaction torques revealed that both the in-phase (supination synchronized with flexion) and the anti-phase (pronation synchronized with flexion) patterns were spontaneously established by participants. The predominance of these patterns of coordination is explained in terms of the mechanical action of bi-articular muscles acting at the elbow joint-complex, and in terms of the reflexes that link the activity of the muscles involved. Results obtained in the different conditions of interaction torques revealed that those neuromuscular-skeletal constraints either impede or favor the exploitation of intersegmental dynamics depending on the context. Interaction torques were indeed found to be exploited to a greater extent in conditions in which the profiles of interaction torques favored one of the two predominant patterns of coordination (i.e., in-phase or anti-phase) as opposed to other patterns of coordination (e.g., 90 degrees or 270 degrees). Those results are discussed in relation to recent studies reporting exploitation of interaction torques in the context of rhythmic movements.

Neuromuscular-skeletal origins of predominant patterns of coordination in a rhythmic two-joint arm movement

The authors tested for predominant patterns of coordination in the combination of rhythmic flexion-extension (FE) and supination-pronation (SP) at the elbow-joint complex. Participants (N = 10) spontaneously established in-phase (supination synchronized with flexion) and antiphase (pronation synchronized with flexion) patterns. In addition, the authors used a motorized robot arm to generate involuntary SP movements with different phase relations with respect to voluntary FE. The involuntarily induced in-phase pattern was accentuated and was more consistent than other patterns. That result provides evidence that the predominance of the in-phase pattern originates in the influence of neuro-muscular-skeletal constraints rather than in a preference dictated by perceptual-cognitive factors implicated in voluntary control. Neuromuscular-skeletal constraints involved in the predominance of the in-phase and the antiphase patterns are discussed.

Reflex contributions to the directional tuning of arm stiffness

It has been shown that during arm movement, humans selectively change the endpoint stiffness of their arm to compensate for the instability in an unstable environment. When the direction of the instability is rotated with respect to the direction of movement, it was found that humans modify the antisymmetric component of their endpoint stiffness. The antisymmetric component of stiffness arises due to reflex responses suggesting that the subjects may have tuned their reflex responses as part of the feedforward adaptive control. The goal of this study was to examine whether the CNS modulates the gain of the reflex response for selective tuning of endpoint impedance. Subjects performed reaching movements in three unstable force fields produced by a robotic manipulandum, each field differing only in the rotational component. After subjects had learned to compensate for the field, allowing them to make unperturbed movements to the target, the endpoint stiffness of the arm was estimated in the middle of the movements. At the same time electromyographic activity (EMG) of six arm muscles was recorded. Analysis of the EMG revealed differences across force fields in the reflex gain of these muscles consistent with stiffness changes. This study suggests that the CNS modulates the reflex gain as part of the adaptive feedforward command in which the endpoint impedance is selectively tuned to overcome environmental instability. © 2008 Springer-Verlag Berlin Heidelberg.

Vector Associative Maps: Unsupervised Real-time Error-based Learning and Control of Movement Trajectories

This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.

Adaptive Neural Networks for Control of Movement Trajectories Invariant under Speed and Force Rescaling

This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-Integration-To-Endpoint (VITE) model suggests how synchronous multi-joint trajectories are generated and performed at variable speeds. The Factorization-of-LEngth-and-TEnsion (FLETE) model suggests how outflow movement commands from a VITE model may be performed at variable force levels without a loss of positional accuracy. The invariance of positional control under speed and force rescaling sheds new light upon a familiar strategy of motor skill development: Skill learning begins with performance at low speed and low limb compliance and proceeds to higher speeds and compliances. The VITE model helps to explain many neural and behavioral data about trajectory formation, including data about neural coding within the posterior parietal cortex, motor cortex, and globus pallidus, and behavioral properties such as Woodworth's Law, Fitts Law, peak acceleration as a function of movement amplitude and duration, isotonic arm movement properties before and after arm-deafferentation, central error correction properties of isometric contractions, motor priming without overt action, velocity amplification during target switching, velocity profile invariance across different movement distances, changes in velocity profile asymmetry across different movement durations, staggered onset times for controlling linear trajectories with synchronous offset times, changes in the ratio of maximum to average velocity during discrete versus serial movements, and shared properties of arm and speech articulator movements. The FLETE model provides new insights into how spina-muscular circuits process variable forces without a loss of positional control. These results explicate the size principle of motor neuron recruitment, descending co-contractive compliance signals, Renshaw cells, Ia interneurons, fast automatic reactive control by ascending feedback from muscle spindles, slow adaptive predictive control via cerebellar learning using muscle spindle error signals to train adaptive movement gains, fractured somatotopy in the opponent organization of cerebellar learning, adaptive compensation for variable moment-arms, and force feedback from Golgi tendon organs. More generally, the models provide a computational rationale for the use of nonspecific control signals in volitional control, or "acts of will", and of efference copies and opponent processing in both reactive and adaptive motor control tasks.

A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.

Gaze pursuit and arm control of adolescent males diagnosed with attention deficit hyperactivity disorder (ADHD) and normal controls: evidence of a dissociation in processing visual information of short and long duration

Three-dimensional kinematic analysis of line of gaze, arm and ball was used to describe the visual and motor behaviour of male adolescents diagnosed with attention deficit hyperactivity disorder (ADHD). The ADHD participants were tested when both on (ADHD-On) and off (ADHD-Off) their medication and compared to age-matched normal controls in a modified table tennis task that required tracking the ball and hitting to cued right and left targets. Long-duration information was provided by a pre-cue, in which the target was illuminated approximately 2 s before the serve, and short-duration information by an early-cue illuminated about 350 ms after the serve, leaving -500 ms to select the target and perform the action. The ADHD groups differed significantly from the control group in both the pre-cue and early-cue conditions in being less accurate, in having a later onset and duration of pursuit tracking, and a higher frequency of gaze on and off the ball. The use of medication significantly reduced the gaze frequency of the ADHD participants, but surprisingly this did not lead to an increase in pursuit tracking, suggesting a barrier was reached beyond which ball flight information could not be processed. The control and ADHD groups did not differ in arm movement onset, duration and velocity in the short-duration early-cue condition; in the long-duration pre-cue condition, however, the ADHD group's movement time onset and arm velocity differed significantly from controls. The results show that the ADHD groups were able to process short-duration information without experiencing adverse effects on their motor behaviour; however, long-duration information contributed to irregular movement control.

Electromyographic study of the trapezius (pars media) and rhomboideus major muscles in movements of the arm (part 1)

The participation of the trapezius (pars media) and rhomboideus major muscles in free movements of abduction, adduction, flexion, extension and hyperextension of the arm was studied electromyographically. These muscles were active and synergic in all analysed movements, both acting with intensity that ranged from moderate to very marked.

Electromyographic study of the trapezius (pars media) and rhomboideus major muscles in movements of the arm (part 2)

The participation of the trapezius (pars media) and rhomboideus major muscles were studied electromyographically in movements of lateral and medial rotation (free and against resistance) of the arm. In the majority of cases both muscles were inactive during the performance of the analysed movements. Cases in which only one or both muscles acted in free rotation occurred only at the second half or ending of the movement. Records of electrical potentials during against resistance rotation were due to tensional efforts at the shoulder level.