Natalia Dounskaia

The strategy used by the brain to organize human goal-directed movements is still debated. Here, I argue that without the knowledge of this strategy, teaching movement skills required in complex sports activities and for rehabilitation of motor disorders remains an art and can often result in inefficient techniques and misleading instructions. However, the leading joint hypothesis offers a solution to this problem. It suggests that the control strategy consists in rotation of a single ('leading') joint actively and using the biomechanical effect produced by the leading joint as the primary contributor to motion of the other ('trailing') joints. This "trailing joint control pattern" was found in a large variety of movement types. This pattern is simple even for seemingly complex movements, it can be easily verbalized, and it requires focusing attention during learning only on one or two movement elements at a time. The use of the trailing joint control strategy therefore allows development of better targeted techniques of motor learning and rehabilitation.

Most actions of daily life engage the two upper extremities (UEs) in a highly coordinated manner. While it is recognized that bimanual movements are impaired post-stroke, understanding how the paretic and non-paretic UE contributes to this impairment is important for future interventions. We investigated kinetic and kinematics at the shoulder, elbow, and wrist joints in the paretic and non-paretic UE in 8 individuals with chronic stroke and non-dominant UE in 8 healthy controls during unimanual and bimanual tasks. Kinematic analysis revealed little effect of stroke. However, kinetic analysis revealed that during unimanual movements, joint control was impaired during unimanual and bimanual movements in both UEs, although to a lesser extent in the non-paretic than paretic UE. During bimanual movements, joint control did not change in the paretic UE, and it further deteriorated in the non-paretic UE compared with the unimanual movements. Our findings suggest that a single session of bimanual task performance does not improve joint control of the paretic UE and it impairs control of the non-paretic UE, making it more like that of the paretic UE.

A trailing joint control pattern, during which a single joint is rotated actively and the mechanical effect of this motion is used to move the other joints, was previously observed during simplified, laboratory-based tasks. We examined whether this simple pattern also underlies control of complex, unconstrained arm movements of daily activities. Six tasks were analyzed. Using kinematic data, we estimated motion of 7 degrees of freedom (DOF) of the shoulder, elbow, and wrist, and the contribution of muscle and passive interaction and gravitational torques to net torque at each joint. Despite task variety, the hand was transported predominantly by shoulder and elbow flexion/extension, although shoulder external/internal rotation also contributed in some tasks. The other DOF were used to orient the hand in space. The trailing pattern represented by production of net torque by passive torques at the shoulder or elbow or both was observed during the biggest portion of each movement. Net torque generation by muscle torque at both joints simultaneously was mainly limited to movement initiation toward the targets and movement termination when returning to the initial position, and associated with needing to overcome gravity. The results support the interpretation of previous studies that prevalence of the trailing pattern is a feature of skillful, coordinated movements. The simplicity of the trailing pattern is promising for quantification of dyscoordination caused by motor disorders and formulation of straightforward instructions to facilitate rehabilitation and motor learning.

We review evidence that the resource-rationality principle generalizes to human movement control. Optimization of the use of limited neurocomputational resources is described by the inclusion of the "neurocomputational cost" of sensory information processing and decision making in the optimality criterion of movement control. A resulting tendency to decrease this cost can account for various phenomena observed during goal-directed movements.

We investigated changes in control of inter-segmental dynamics underlying upper extremity dyscoordination caused by stroke. Individuals with stroke and healthy individuals performed a natural reach-to-grasp movement. Kinetic analysis revealed that both groups rotated the shoulder by muscle torque and used interaction torque to rotate the elbow. However, individuals with stroke used interaction torque less than healthy individuals, actively suppressing a substantial portion of it. This resulted in inefficient use of active control and dyscoordination of the upper extremity. The degree of interaction torque suppression and inefficiency of active control at the elbow positively correlated with stroke severity. The increased interaction torque suppression can be a strategy used by individuals with stroke to compensate for deficient feedforward control of this torque.

Joint coordination during locomotion and how this coordination changes in response to perturbations remains poorly understood. We investigated coordination among forelimb joints during the swing phase of skilled locomotion in the cat. While cats walked on a horizontal ladder, one of the cross-pieces moved before the cat reached it, requiring the cat to alter step size. Direction and timing of the cross-piece displacement were manipulated. We found that the paw was transported in space through body translation and shoulder and elbow rotations, whereas the wrist provided paw orientation required to step on cross-pieces. Kinetic analysis revealed a consistent joint control pattern in all conditions. Although passive interaction and gravitational torques were the main sources of shoulder and elbow motions for most of the movement time, shoulder muscle torque influenced movement of the entire limb at the end of the swing phase, accelerating the shoulder and causing interaction torque that determined elbow motion. At the wrist, muscle and passive torques predominantly compensated for each other. In all perturbed conditions, although all joints and the body slightly contributed to changes in the step length throughout the entire movement, the major adjustment was produced by the shoulder at the movement end. We conclude that joint coordination during the swing phase is produced mainly passively, by exploiting gravity and the limb’s intersegmental dynamics, which may simplify the neural control of locomotion. The use of shoulder musculature at the movement end enables flexible responses to environmental disturbances. NEW & NOTEWORTHY This is the first study to investigate joint control during the swing phase of skilled, accuracy-dependent locomotion in the cat and how this control is altered to adapt to known and unexpected perturbations. We demonstrate that a pattern of joint control that exploits gravitational and interaction torques is used in all conditions and that movement modifications are produced mainly by shoulder muscle torque during the last portion of the movement.

A more general form of optimality approach applied to the entire behavioral paradigm should be used instead of abandoning the optimality approach. Adding the cost of information processing to the optimality criterion and taking into account some other recently proposed aspects of decision optimization could substantially increase the explanatory power of an optimality approach to modeling perceptual decision making.

The inverted pendulum model predicts that the major challenge for neural control of the upright posture is the inherent instability of the body due to the center of mass (COM) being above the base of support (BOS). If so, even slight elevation of the COM may substantially destabilize posture. The destabilizing effect of heavy load positioned above the COM has been demonstrated. We examined sensitivity of posture to light (1–5% of body weight) load by placing weights on the shoulders and assessing functional reach distance in the forward, right, and left directions and postural sway during quiet stance. At each load level, the quiet stance task was tested with and without vision. The 1% of body weight load significantly shortened reach distance in the forward direction. It also increased postural sway. Interestingly, additional weight did not result in further deficits. The results support high sensitivity of postural stability to COM elevation that increases the challenge for neural control of posture and that can potentially be used for early detection of declines in postural stability.

Optimality criteria underlying organization of arm movements are often validated by testing their ability to adequately predict hand trajectories. However, kinematic redundancy of the arm allows production of the same hand trajectory through different joint coordination patterns. We therefore consider movement optimality at the level of joint coordination patterns. A review of studies of multi-joint movement control suggests that a ‘trailing’ pattern of joint control is consistently observed during which a single (‘leading’) joint is rotated actively and interaction torque produced by this joint is the primary contributor to the motion of the other (‘trailing’) joints. A tendency to use the trailing pattern whenever the kinematic redundancy is sufficient and increased utilization of this pattern during skillful movements suggests optimality of the trailing pattern. The goal of this study is to determine the cost function minimization of which predicts the trailing pattern. We show that extensive experimental testing of many known cost functions cannot successfully explain optimality of the trailing pattern. We therefore propose a novel cost function that represents neural effort for joint coordination. That effort is quantified as the cost of neural information processing required for joint coordination. We show that a tendency to reduce this ‘neurocomputational’ cost predicts the trailing pattern and that the theoretically developed predictions fully agree with the experimental findings on control of multi-joint movements. Implications for future research of the suggested interpretation of the trailing joint control pattern and the theory of joint coordination underlying it are discussed.