Movement Endpoint Research Articles

A switching cost for motor planning.

Movement planning consists of choosing the intended endpoint of the movement and selecting the motor program that will bring the effector on the endpoint. It is widely accepted that movement endpoint is updated on a trial-by-trial basis with respect to the observed errors and that the motor program for a given movement follows the rules of optimal feedback control. In this article, we show clear limitations of these theories. First, participants in the current study could not tune their motor program appropriately for each individual trial. This was true even when the participants selected the width of the target that they reached toward or when they had learned the appropriate motor program previously. These data are compatible with the existence of a switching cost for motor planning, which relates to the drop in performance due to an imposed switch of motor programs. This cost of switching shares many features of costs reported in cognitive task switching experiments and, when tested in the same participants, was correlated with it. Second, we found that randomly changing the width of a target over the course of a reaching experiment prevents the motor system from updating the endpoint of movements on the basis of the performance on the previous trial if the width of the target has changed. These results provide new insights into the process of motor planning and how it relates to optimal control theory and to an action selection based on the reward consequences of the motor program rather than that based on the observed error.

Upper Limb Obstacle Avoidance Behavior in Individuals With Stroke

Background. Upper limb (UL) poststroke hemiparesis commonly leads to chronic disability. Despite moderate-to-good clinical recovery, many patients with UL hemiparesis still do not fully use their arm in daily tasks. Decreased arm use may be related to deficits in performance of more complex movement than what is usually assessed clinically. Objective. To identify differences between poststroke and nondisabled control subjects in making complex corrective movements to avoid an obstacle in the reaching path. Methods. Subjects rapidly reached for a juice bottle on a refrigerator shelf with their hemiparetic or dominant (controls) arm viewed in a large-screen projected 3D virtual environment. In random trials, a sliding door partially obstructed the reaching path. A successful trial was one in which subjects touched the bottle without their arm or hand hitting the door. Results. Fewer participants with stroke (12%) were successful at a 65% success rate in avoiding the door compared to controls (42%). Subjects with stroke also initiated corrections later (further) in the reaching path (100.7 ± 77.6 mm) compared to controls (51.6 ± 31.0 mm) resulting in a reduced margin of error. While both groups used similar endpoint movement strategies for obstructed reaching, subjects with stroke used less elbow and more trunk movement. Participants who reported being more confident using their hemiparetic arm had higher success rates. Conclusion. Arm movement deficits can be identified when complex tasks are evaluated. Deficits in higher-order motor function such as obstacle avoidance behavior may decrease actual arm use in individuals with mild-to-moderate hemiparesis and should be evaluated in routine clinical practice.

Extending Energy Optimization in Goal-Directed Aiming from Movement Kinematics to Joint Angles

ABSTRACTEnergy optimization in goal-directed aiming has been demonstrated as an undershoot bias in primary movement endpoint locations, especially in conditions where corrections to target overshoots must be made against gravity. Two-component models of upper limb movement have not yet considered how joint angles are organized to deal with the energy constraints associated with moving the upper limb in goal-directed aiming tasks. To address this limitation, participants performed aiming movements to targets in the up and down directions with the index finger and two types of rod extensions attached to the index finger. The rod extensions were expected to invoke different energy optimizing strategies in the up and down directions by allowing the distal joints the opportunity to contribute to end effector displacement. Primary movements undershot the farthest target to a greater extent in the downward direction compared to the upward direction, showing that movement kinematics optimize energy expenditure in consideration of the effects of gravity. As rod length increased, shoulder elevation was optimized in movements to the far-up target and elbow flexion was optimally minimized in movements to the far-down target. The results suggest energy optimization in the control of joint angles independent of the force of gravity.

Control of Redundant Kinematic Degrees of Freedom in a Closed-Loop Brain-Machine Interface.

Brain-machine interface (BMI) systems use signals acquired from the brain to directly control the movement of an actuator, such as a computer cursor or a robotic arm, with the goal of restoring motor function lost due to injury or disease of the nervous system. In BMIs with kinematically redundant actuators, the combination of the task goals and the system under neural control can allow for many equally optimal task solutions. The extent to which kinematically redundant degrees of freedom (DOFs) in a BMI system may be under direct neural control is unknown. To address this question, a Kalman filter was used to decode single- and multi-unit cortical neural activity of two macaque monkeys into the joint velocities of a virtual four-link kinematic chain. Subjects completed movements of the chain's endpoint to instructed target locations within a two-dimensional plane. This system was kinematically redundant for an endpoint movement task, as four DOFs were used to manipulate the 2-D endpoint position. Both subjects successfully performed the task and improved with practice by producing faster endpoint velocity control signals. Kinematic redundancy allowed null movements whereby the individual links of the chain could move in a way that cancels out and does not result in endpoint movement. As the subjects became more proficient at controlling the chain, the amount of null movement also increased. Task performance suffered when the links of the kinematic chain were hidden and only the endpoint was visible. Furthermore, all four DOFs of the joint-velocity control space exhibited task-relevant modulation. The relative usage of each DOF depended on the configuration of the chain, and trials in which the less-prominent DOFs were utilized also had better task performance. Overall, these results indicate that the subjects incorporated the redundant components of the control space into their control strategy. Future BMI systems with kinematic redundancy, such as exoskeletal systems or anthropomorphic robotic arms, may benefit from allowing neural control over redundant configuration dimensions as well as the end-effector.

A Synergetic Brain-Machine Interfacing Paradigm for Multi-DOF Robot Control

This paper proposes a novel brain-machine interfacing (BMI) paradigm for control of a multijoint redundant robot system. Here, the user would determine the direction of end-point movement of a 3-degrees of freedom (DOF) robot arm using motor imagery electroencephalography signal with co-adaptive decoder (adaptivity between the user and the decoder) while a synergetic motor learning algorithm manages a peripheral redundancy in multi-DOF joints toward energy optimality through tacit learning. As in human motor control, torque control paradigm is employed for a robot to be adaptive to the given physical environment. The dynamic condition of the robot arm is taken into consideration by the learning algorithm. Thus, the user needs to only think about the end-point movement of the robot arm, which allows simultaneous multijoints control by BMI. The support vector machine-based decoder designed in this paper is adaptive to the changing mental state of the user. Online experiments reveals that the users successfully reach their targets with an average decoder accuracy of over 75% in different end-point load conditions.

Cerebellar Modulation of Cortically Evoked Complex Movements in Rats.

Intracortical microstimulation (ICMS) delivered to the motor cortex (M1) via long- or short-train duration (long- or short-duration ICMS) can evoke coordinated complex movements or muscle twitches, respectively. The role of subcortical cerebellar input in M1 output, in terms of long- and short-duration ICMS-evoked movement and motor skill performance, was evaluated in rats with bilateral lesion of the deep cerebellar nuclei. After the lesion, distal forelimb movements were seldom observed, and almost 30% of proximal forelimb movements failed to match criteria defining the movement class observed under control conditions. The classifiable movements could be evoked in different cortical regions with respect to control and many kinematic variables were strongly affected. Furthermore, movement endpoints within the rat's workspace shrunk closer to the body, while performance in the reaching/grasping task worsened. Surprisingly, neither the threshold current values for evoking movements nor the overall size of forelimb movement representation changed with respect to controls in either long- or short-duration ICMS. We therefore conclude that cerebellar input via the motor thalamus is crucial for expressing the basic functional features of the motor cortex.

Математична модель оптимального керування рухом електрорухомого складу на підставі вирішення рівнянь Гамільтона-Якобі-Беллмана

Optimal control is a powerful tool, which allows you to solve complex management tasks, including motion control of electric rolling stock on railways. The optimization problem is a common concern of management theory. It consideres the current factor as an abstract object, which seeks to maximize the expected benefits (or minimize losses) at some future period of time. A mathematical model of electric rolling stock control systems, based on the solution of Hamilton-Jacobi-Bellman equation using the method of dynamic programming and solution of the problem relating to the time coordinate has been developed in this paper. To reduce the volume of calculations it has been proposed to determine the optimal expert system in the direction relating to the movement time of electric rolling stock - reverse Bellman approach. It is assumed that the end point of electric rolling stock movement is known - the ultimate coordinate of movement and given time of movement, and the final velocity at this point is zero - which corresponds to the arrival of the train to the destination.

An Eye in the Palm of Your Hand: Alterations in Visual Processing Near the Hand, a Mini-Review.

Feedback within the oculomotor system improves visual processing at eye movement end points, also termed a visual grasp. We do not just view the world around us however, we also reach out and grab things with our hands. A growing body of literature suggests that visual processing in near-hand space is altered. The control systems for moving either the eyes or the hands rely on parallel networks of fronto-parietal regions, which have feedback connections to visual areas. Since the oculomotor system effects on visual processing occur through feedback, both through the motor plan and the motor efference copy, a parallel system where reaching and/or grasping motor-related activity also affects visual processing is likely. Areas in the posterior parietal cortex, for example, receive proprioceptive and visual information used to guide actions, as well as motor efference signals. This trio of information channels is all that would be necessary to produce spatial allocation of reach-related visual attention. We review evidence from behavioral and neurophysiological studies that support the hypothesis that feedback from the reaching and/or grasping motor control networks affects visual processing while noting ways in which it differs from that seen within the oculomotor system. We also suggest that object affordances may represent the neural mechanism through which certain object features are selected for preferential processing when stimuli are near the hand. Finally, we summarize the two effector-based feedback systems and discuss how having separate but parallel effector systems allows for efficient decoupling of eye and hand movements.

A Sensorimotor Model for Computing Intended Reach Trajectories.

The presumed role of the primate sensorimotor system is to transform reach targets from retinotopic to joint coordinates for producing motor output. However, the interpretation of neurophysiological data within this framework is ambiguous, and has led to the view that the underlying neural computation may lack a well-defined structure. Here, I consider a model of sensorimotor computation in which temporal as well as spatial transformations generate representations of desired limb trajectories, in visual coordinates. This computation is suggested by behavioral experiments, and its modular implementation makes predictions that are consistent with those observed in monkey posterior parietal cortex (PPC). In particular, the model provides a simple explanation for why PPC encodes reach targets in reference frames intermediate between the eye and hand, and further explains why these reference frames shift during movement. Representations in PPC are thus consistent with the orderly processing of information, provided we adopt the view that sensorimotor computation manipulates desired movement trajectories, and not desired movement endpoints.

Review of upper limb kinematics after cervical spinal cord injury: Implications for rehabilitation

The aim of this literature review is to provide a clear understanding of motor control and kinematic changes during open-chain upper limb (UL) movements after tetraplegia. Using data from MEDLINE between 1966 and August 2014, we investigated kinematic UL studies after tetraplegia. We included fourteen control case and three series case studies with a total of 161 SCI participants and 126 healthy control participants. SCI participants efficiently perform a broad range of tasks with their UL This is achieved by effective scapulothoracic and glenohumeral compensation which provide a dynamic mechanical coupling between the shoulder and elbow joints thus palliating elbow extension despite triceps brachii paralysis. The mechanism is incomplete, however, since C5-C6 SCI individuals are forced to reduce overhead workspace to keep the elbow extended and to maintain the mechanical dynamic interaction between the shoulder and elbow. Furthermore, motion slowing is a clear kinematic characteristic, caused by: – decreased strength; – triceps brachii paralysis disrupting normal agonist-antagonist co-contraction; – accuracy requirements at movement endpoint; – grasping. Grasping requires a prolonged deceleration phase during transport to ensure hand placement with respect to the to-be-grasped object then wrist extension during grasping to elicit either whole hand or lateral grip. Contrary to the normal pattern, where grasping is prepared during the transport phase, SCI individuals transport the wrist in flexion leading to passive finger opening that did not attest a grip preparation particularly if object size is greater than maximal grip aperture. The pattern (wrist flexed then extended) indicates that reaching and grasping are performed consecutively suggesting that these two phases are independent. Elbow extension restoration causes increased elbow stiffness resulting in increased movement velocity, reduced need for glenohumeral compensation, and overall improved motor control. Rehabilitation and surgical restoration should take these kinematic characteristics into account to reinforce proximal and distal compensations allowing elbow extension and grasp using tenodesis and consequently favoring greater autonomy of individuals after SCI.

Temporal and spatial constraints of action effect on sensory binding.

Previous studies have shown that asynchrony in perceived changes in the visual attributes of an object is attenuated when the object is the target of a manual reaching action (e.g. Corveleyn et al. in J Vis, 2012. doi: 10.1167/12.11.20 ). In the present study, we examined the temporal and spatial constraints associated with the effect of action on sensory binding. Participants performed a temporal order judgment task which required them to judge which changed first, the position or the colour of a visual stimulus, either while performing a concurrent motor task (manual acquisition of a visual target) or not (perceptual task). In Experiment 1, the fixed-attribute change (colour or position) occurred 0, 250, 500 or 1000ms following the end of the motor action or the presentation of an auditory cue, while the variable-attribute change (position or colour) occurred randomly within an interval of ±200ms from the fixed-attribute change. In Experiment 2, the visual stimulus was presented at a distance of 0, 2, 4 or 8cm from a central fixation cross which was the target in the motor task. The fixed attribute (colour or position) changed 700ms after an auditory cue (perceptual task) or when the hand reached the visual target (motor task). The variable-attribute change (position or colour) again occurred within an interval of ±200ms from the fixed-attribute change. Statistical analysis of the point of subjective simultaneity revealed that performing a motor action reduced the perceived temporal asynchrony in the perceptual task, but only when the visual changes occurred less than 500ms (for the fixed attribute) following movement execution (Exp. 1) and at a distance of less than 4cm from the movement endpoint (Exp. 2). These results indicate that action-induced sensory binding requires temporal contiguity and spatial congruency between the endpoint of the action and its visual consequences.

Velocity neurons improve performance more than goal or position neurons do in a simulated closed-loop BCI arm-reaching task.

Brain-Computer Interfaces (BCIs) that convert brain-recorded neural signals into intended movement commands could eventually be combined with Functional Electrical Stimulation to allow individuals with Spinal Cord Injury to regain effective and intuitive control of their paralyzed limbs. To accelerate the development of such an approach, we developed a model of closed-loop BCI control of arm movements that (1) generates realistic arm movements (based on experimentally measured, visually-guided movements with real-time error correction), (2) simulates cortical neurons with firing properties consistent with literature reports, and (3) decodes intended movements from the noisy neural ensemble. With this model we explored (1) the relative utility of neurons tuned for different movement parameters (position, velocity, and goal) and (2) the utility of recording from larger numbers of neurons—critical issues for technology development and for determining appropriate brain areas for recording. We simulated arm movements that could be practically restored to individuals with severe paralysis, i.e., movements from an armrest to a volume in front of the person. Performance was evaluated by calculating the smallest movement endpoint target radius within which the decoded cursor position could dwell for 1 s. Our results show that goal, position, and velocity neurons all contribute to improve performance. However, velocity neurons enabled smaller targets to be reached in shorter amounts of time than goal or position neurons. Increasing the number of neurons also improved performance, although performance saturated at 30–50 neurons for most neuron types. Overall, our work presents a closed-loop BCI simulator that models error corrections and the firing properties of various movement-related neurons that can be easily modified to incorporate different neural properties. We anticipate that this kind of tool will be important for development of future BCIs.

Mapping shape to visuomotor mapping: learning and generalisation of sensorimotor behaviour based on contextual information.

Humans can learn and store multiple visuomotor mappings (dual-adaptation) when feedback for each is provided alternately. Moreover, learned context cues associated with each mapping can be used to switch between the stored mappings. However, little is known about the associative learning between cue and required visuomotor mapping, and how learning generalises to novel but similar conditions. To investigate these questions, participants performed a rapid target-pointing task while we manipulated the offset between visual feedback and movement end-points. The visual feedback was presented with horizontal offsets of different amounts, dependent on the targets shape. Participants thus needed to use different visuomotor mappings between target location and required motor response depending on the target shape in order to “hit” it. The target shapes were taken from a continuous set of shapes, morphed between spiky and circular shapes. After training we tested participants performance, without feedback, on different target shapes that had not been learned previously. We compared two hypotheses. First, we hypothesised that participants could (explicitly) extract the linear relationship between target shape and visuomotor mapping and generalise accordingly. Second, using previous findings of visuomotor learning, we developed a (implicit) Bayesian learning model that predicts generalisation that is more consistent with categorisation (i.e. use one mapping or the other). The experimental results show that, although learning the associations requires explicit awareness of the cues’ role, participants apply the mapping corresponding to the trained shape that is most similar to the current one, consistent with the Bayesian learning model. Furthermore, the Bayesian learning model predicts that learning should slow down with increased numbers of training pairs, which was confirmed by the present results. In short, we found a good correspondence between the Bayesian learning model and the empirical results indicating that this model poses a possible mechanism for simultaneously learning multiple visuomotor mappings.

Sensor positioning and experimental constraints influence estimates of local dynamic stability during repetitive spine movements

Application of non-linear dynamics analyses to study human movement has increased recently, which necessitates an understanding of how dependent measures may be influenced by experimental design and setup. Quantifying local dynamic stability for a multi-articulated structure such as the spine presents the possibility for estimates to be influenced by positioning of kinematic sensors used to measure spine angular kinematics. Oftentimes researchers will also choose to constrain the spine׳s movement by physically restraining the pelvis and/or using targets to control movement endpoints. Ten healthy participants were recruited, and asked to perform separate trials of 35 consecutive cycles of spine flexion under both constrained and unconstrained conditions. Electromagnetic sensors that measure three-dimensional angular orientations were positioned over the pelvis and the spinous processes of L3, L1, and T11. Using the pelvic sensor as a reference, each sensor location on the spine was used to obtain a different representation of the three-dimensional spine angular kinematics. Local dynamic stability of each kinematic time-series was determined by calculating the maximum finite-time Lyapunov exponent (λmax). Estimates for λmax were significantly lower (i.e. dynamically more stable) for spine kinematic data obtained from the L3 sensor than those obtained from kinematic data using either the L1 or T11 sensors. Likewise, λmax was lower when the movement was constrained. These results emphasize the importance of proper placement of instrumentation for quantifying local dynamic stability of spine kinematics and are especially relevant for repeated measures designs where data are obtained from the same individual on multiple days.

Upper limb kinematics after cervical spinal cord injury: a review.

Although a number of upper limb kinematic studies have been conducted, no review actually addresses the key-features of open-chain upper limb movements after cervical spinal cord injury (SCI). The aim of this literature review is to provide a clear understanding of motor control and kinematic changes during open-chain upper limb reaching, reach-to-grasp, overhead movements, and fast elbow flexion movements after tetraplegia. Using data from MEDLINE between 1966 and December 2014, we examined temporal and spatial kinematic measures and when available electromyographic recordings. We included fifteen control case and three series case studies with a total of 164 SCI participants and 131 healthy control participants. SCI participants efficiently performed a broad range of tasks with their upper limb and movements were planned and executed with strong kinematic invariants like movement endpoint accuracy and minimal cost. Our review revealed that elbow extension without triceps brachii relies on increased scapulothoracic and glenohumeral movements providing a dynamic coupling between shoulder and elbow. Furthermore, contrary to normal grasping patterns where grasping is prepared during the transport phase, reaching and grasping are performed successively after SCI. The prolonged transport phase ensures correct hand placement while the grasping relies on wrist extension eliciting either whole hand or lateral grip. One of the main kinematic characteristics observed after tetraplegia is motor slowing attested by increased movement time. This could be caused by (i) decreased strength, (ii) triceps brachii paralysis which disrupts normal agonist–antagonist co-contractions, (iii) accuracy preservation at movement endpoint, and/or (iv) grasping relying on tenodesis. Another feature is a reduction of maximal superior reaching during overhead movements which could be caused by i) strength deficit in agonist muscles like pectoralis major, ii) strength deficit in proximal synergic muscles responsible for scapulothoracic and glenohumeral joint stability, iii) strength deficit in distal synergic muscles preventing the maintenance of elbow extension by shoulder elbow dynamic coupling, iv) shoulder joint ankyloses, and/or v) shoulder pain. Further studies on open chain movements are needed to identify the contribution of each of these factors in order to tailor upper limb rehabilitation programs for SCI individuals.

Equilibrium-based movement endpoints elicited from primary motor cortex using repetitive microstimulation.

High-frequency, long-duration intracortical microstimulation (HFLD-ICMS) is increasingly being used to deduce how the brain encodes coordinated muscle activity and movement. However, the full movement repertoire that can be elicited from the forelimb representation of primary motor cortex (M1) using this method has not been systematically determined. Our goal was to acquire a comprehensive M1 forelimb representational map of movement endpoints elicited with HFLD-ICMS, using stimulus parameters optimal for evoking stable forelimb spatial endpoints. The data reveal a 3D forelimb movement endpoint workspace that is represented in a patchwork fashion on the 2D M1 cortical surface. Although cortical maps of movement endpoints appear quite disorderly with respect to movement space, we show that the endpoint locations in the workspace evoked with HFLD-ICMS of two adjacent cortical points are closer together than would be expected if the organization were random. Although there were few obvious consistencies in the endpoint maps across the two monkeys tested, one notable exception was endpoints bringing the hand to the mouth, which was located at the boundary between the hand and face representation. Endpoints at the extremes of the monkey's workspace and locations above the head were largely absent. Our movement endpoints are best explained as resulting from coactivation of agonist and antagonist muscles driving the joints toward equilibrium positions determined by the length-tension relationships of the muscles.

Estimating feedforward vs. feedback control of speech production through kinematic analyses of unperturbed articulatory movements.

To estimate the contributions of feedforward vs. feedback control systems in speech articulation, we analyzed the correspondence between initial and final kinematics in unperturbed tongue and jaw movements for consonant-vowel (CV) and vowel-consonant (VC) syllables. If movement extents and endpoints are highly predictable from early kinematic information, then the movements were most likely completed without substantial online corrections (feedforward control); if the correspondence between early kinematics and final amplitude or position is low, online adjustments may have altered the planned trajectory (feedback control) (Messier and Kalaska, 1999). Five adult speakers produced CV and VC syllables with high, mid, or low vowels while movements of the tongue and jaw were tracked electromagnetically. The correspondence between the kinematic parameters peak acceleration or peak velocity and movement extent as well as between the articulators' spatial coordinates at those kinematic landmarks and movement endpoint was examined both for movements across different target distances (i.e., across vowel height) and within target distances (i.e., within vowel height). Taken together, results suggest that jaw and tongue movements for these CV and VC syllables are mostly under feedforward control but with feedback-based contributions. One type of feedback-driven compensatory adjustment appears to regulate movement duration based on variation in peak acceleration. Results from a statistical model based on multiple regression are presented to illustrate how the relative strength of these feedback contributions can be estimated.

Motor contagion: the contribution of trajectory and end-points.

Increased involuntary arm movement deviation when observing an incongruent human arm movement has been interpreted as a strong indicator of motor contagion. Here, we examined the contribution of trajectory and end-point information on motor contagion by altering congruence between the stimulus and arm movement. Participants performed cyclical horizontal arm movements whilst simultaneously observing a stimulus representing human arm movement. The stimuli comprised congruent horizontal movements or vertical movements featuring incongruent trajectory and end-points. A novel, third, stimulus comprised curvilinear movements featuring congruent end-points, but an incongruent trajectory. In Experiment 1, our dependent variables indicated increased motor contagion when observing the vertical compared to horizontal movement stimulus. There was even greater motor contagion in the curvilinear stimulus condition indicating an additive effect of an incongruent trajectory comprising congruent end-points. In Experiment 2, this additive effect was also present when facing perpendicular to the display, and thus with end-points represented as a product of the movement rather than an external spatial reference. Together, these findings support the theory of event coding (Hommel et al., Behav Brain Sci 24:849-878, 2001), and the prediction that increased motor contagion takes place when observed and executed actions share common features (i.e., movement end-points).

Aging and limb alter the neuromuscular control of goal-directed movements

The purpose of this study was to determine whether the neuromuscular control of goal-directed movements is different for young and older adults with the upper and lower limbs. Twenty young (25.1 ± 3.9 years) and twenty older adults (71.5 ± 4.8 years) attempted to accurately match the displacement of their limb to a spatiotemporal target during ankle dorsiflexion or elbow flexion movements. We quantified neuromuscular control by examining the movement endpoint accuracy and variability, and the antagonistic muscle activity using surface electromyography (EMG). Our results indicate that older adults exhibit impaired endpoint accuracy with both limbs due to greater time variability. In addition, older adults exhibit greater EMG burst and lower EMG burst variability as well as lower coactivation of the antagonistic muscles. The impaired accuracy of older adults during upper limb movements was related to lower coactivation of the antagonistic muscles, whereas their impaired accuracy during lower limb movements was related to the amplified EMG bursts. The upper limb exhibited greater movement control than the lower limb, and different neuromuscular parameters were related to the accuracy and consistency for each limb. Greater endpoint error during upper limb movements was related to lower coactivation of the antagonistic muscles, whereas greater endpoint error during lower limb movements was related to the amplified EMG bursts. These findings indicate that the age-associated impairments in movement control are associated with altered activation of the involved antagonistic muscles. In addition, independent of age, the neuromuscular control of goal-directed movements is different for the upper and lower limbs.

Interference and Shaping in Sensorimotor Adaptations with Rewards

When a perturbation is applied in a sensorimotor transformation task, subjects can adapt and maintain performance by either relying on sensory feedback, or, in the absence of such feedback, on information provided by rewards. For example, in a classical rotation task where movement endpoints must be rotated to reach a fixed target, human subjects can successfully adapt their reaching movements solely on the basis of binary rewards, although this proves much more difficult than with visual feedback. Here, we investigate such a reward-driven sensorimotor adaptation process in a minimal computational model of the task. The key assumption of the model is that synaptic plasticity is gated by the reward. We study how the learning dynamics depend on the target size, the movement variability, the rotation angle and the number of targets. We show that when the movement is perturbed for multiple targets, the adaptation process for the different targets can interfere destructively or constructively depending on the similarities between the sensory stimuli (the targets) and the overlap in their neuronal representations. Destructive interferences can result in a drastic slowdown of the adaptation. As a result of interference, the time to adapt varies non-linearly with the number of targets. Our analysis shows that these interferences are weaker if the reward varies smoothly with the subject's performance instead of being binary. We demonstrate how shaping the reward or shaping the task can accelerate the adaptation dramatically by reducing the destructive interferences. We argue that experimentally investigating the dynamics of reward-driven sensorimotor adaptation for more than one sensory stimulus can shed light on the underlying learning rules.