Aymar de Rugy

Different mechanisms contributing to savings and anterograde interference are impaired in Parkinson's disease.

Reinforcement and use-dependent plasticity mechanisms have been proposed to be involved in both savings and anterograde interference in adaptation to a visuomotor rotation (cf. Huang et al., 2011). In Parkinsons disease (PD), dopamine dysfunction is known to impair reinforcement mechanisms, and could also affect use-dependent plasticity. Here, we assessed savings and anterograde interference in PD with an A1-B-A2 paradigm in which movement repetition was (1) favored by the use of a single-target, and (2) manipulated through the amount of initial training. PD patients and controls completed either limited or extended training in A1 where they adapted movement to a 30° counter-clockwise rotation of visual feedback of the movement trajectory, and then adapted to a 30° clockwise rotation in B. After subsequent washout, participants readapted to the first 30° counter-clockwise rotation in A2. Controls showed significant anterograde interference from A1 to B only after extended training, and significant A1-B-A2 savings after both limited and extended training. However, despite similar A1 adaptation to controls, PD patients showed neither anterograde interference nor savings. That extended training was necessary in controls to elicit anterograde interference but not savings suggests that savings and anterograde interference do not result from equal contributions of the same underlying mechanism(s). It is suggested that use-dependent plasticity mechanisms contributes to anterograde interference but not to savings, while reinforcement mechanisms contribute to both. As both savings and anterograde interference were impaired in PD, dopamine dysfunction in PD might impair both reinforcement and use-dependent plasticity mechanisms during adaptation to a visuomotor rotation.

Muscle Coordination Is Habitual Rather than Optimal

When sharing load among multiple muscles, humans appear to select an optimal pattern of activation that minimizes costs such as the effort or variability of movement. How the nervous system achieves this behavior, however, is unknown. Here we show that contrary to predictions from optimal control theory, habitual muscle activation patterns are surprisingly robust to changes in limb biomechanics. We first developed a method to simulate joint forces in real time from electromyographic recordings of the wrist muscles. When the model was altered to simulate the effects of paralyzing a muscle, the subjects simply increased the recruitment of all muscles to accomplish the task, rather than recruiting only the useful muscles. When the model was altered to make the force output of one muscle unusually noisy, the subjects again persisted in recruiting all muscles rather than eliminating the noisy one. Such habitual coordination patterns were also unaffected by real modifications of biomechanics produced by selectively damaging a muscle without affecting sensory feedback. Subjects naturally use different patterns of muscle contraction to produce the same forces in different pronation–supination postures, but when the simulation was based on a posture different from the actual posture, the recruitment patterns tended to agree with the actual rather than the simulated posture. The results appear inconsistent with computation of motor programs by an optimal controller in the brain. Rather, the brain may learn and recall command programs that result in muscle coordination patterns generated by lower sensorimotor circuitry that are functionally “good-enough.”

Are muscle synergies useful for neural control

The observation that the activity of multiple muscles can be well approximated by a few linear synergies is viewed by some as a sign that such low-dimensional modules constitute a key component of the neural control system. Here, we argue that the usefulness of muscle synergies as a control principle should be evaluated in terms of errors produced not only in muscle space, but also in task space. We used data from a force-aiming task in two dimensions at the wrist, using an electromyograms (EMG)-driven virtual biomechanics technique that overcomes typical errors in predicting force from recorded EMG, to illustrate through simulation how synergy decomposition inevitably introduces substantial task space errors. Then, we computed the optimal pattern of muscle activation that minimizes summed-squared muscle activities, and demonstrated that synergy decomposition produced similar results on real and simulated data. We further assessed the influence of synergy decomposition on aiming errors (AEs) in a more redundant system, using the optimal muscle pattern computed for the elbow-joint complex (i.e., 13 muscles acting in two dimensions). Because EMG records are typically not available from all contributing muscles, we also explored reconstructions from incomplete sets of muscles. The redundancy of a given set of muscles had opposite effects on the goodness of muscle reconstruction and on task achievement; higher redundancy is associated with better EMG approximation (lower residuals), but with higher AEs. Finally, we showed that the number of synergies required to approximate the optimal muscle pattern for an arbitrary biomechanical system increases with task-space dimensionality, which indicates that the capacity of synergy decomposition to explain behavior depends critically on the scope of the original database. These results have implications regarding the viability of muscle synergy as a putative neural control mechanism, and also as a control algorithm to restore movements.

Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion–extension, forearm pronation–supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60° visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.

Interaction between discrete and rhythmic movements: reaction time and phase of discrete movement initiation during oscillatory movements

This study investigates a task in which discrete and rhythmic movements are combined in a single-joint elbow rotation. Previous studies reported a tendency for the EMG burst associated with the discrete movement to occur around the expected burst associated with the rhythmic movement (e.g., [Exp. Brain Res. 99 (1994) 325; J. Neurol. Neurosurg. Psychiatry 40 (1977) 1129; Hum. Mov. Sci. 19 (2000) 627]). We document this interaction between discrete and rhythmic movements in different task variations and suggest a model consisting of rhythmic and discrete pattern generators that reproduces the major results. In the experiment, subjects performed single-joint elbow oscillatory movements (2 Hz). Upon a signal, they initiated a movement that consisted of a shift in the midpoint of the oscillation (MID), a shift in the amplitude of the oscillation (AMP), or a combination of both (MID + AMP). These shifting movements were performed either in a reaction time or in a self-paced fashion. The tendency for the EMG bursts associated with the discrete and rhythmic movements to synchronize was found similarly in all three tasks and instruction conditions, but the synchronization was most pronounced in the self-initiated discrete movement. Reaction time was increased for the combined task (MID + AMP), indicating higher control demands due to a combination of discrete and rhythmic components. This EMG burst synchronization was reproduced in a model based on a half-center oscillator with activation signals that produce either rhythmic or discrete activity. This activity was interpreted as torques driving a simple limb model. Summation of discrete and rhythmic activation signals of the pattern generators was sufficient to simulate the EMG burst synchronization. Further, simulation data reproduced the modulation of the reaction time as a function of the phase of the discrete movement.

Corticospinal modulation induced by sounds depends on action preparedness

•  Unexpected loud auditory stimuli can trigger the involuntary release of motor actions during preparation to move. •  Because acoustic stimulation can suppress motor cortex excitability during action, this early release could be independent of the motor cortex, and interpreted as pre‐planned action stored and triggered from subcortical areas. •  In contrast, we show that corticospinal excitability in response to the loud auditory stimuli was increased when people were highly prepared to move, and reduced otherwise. •  Our results also indicate that auditory stimuli can affect intracortical excitability by increasing intracortical facilitation and reducing short‐interval intracortical inhibition. •  Together, our findings demonstrate that the early release of motor responses by auditory stimuli involves the motor cortex.

The learning of goal-directed locomotion: A perception-action perspective

This study was designed to better understand the process underlying the learning of goal-directed locomotion. Subjects walked on a treadmill in a virtual reality setting and were asked to cross pairs of oscillating doors. The subjects behaviour was examined at the beginning of the learning process (pretest), after 350 trials (intermediate test), and after 700 trials (posttest). The data were analysed at three different levels, each representing a specific aspect of the global response: performance outcome, displacement kinematics, and current arrival condition. While some aspects of performance outcome suggested the presence of a ceiling effect in the intermediate test, both displacement kinematics and current arrival condition clearly highlighted continuous transformations of the control mechanism involved. The learning process is best described as (1) the establishing of a relationship between specific information and a movement parameter and (2) the optimization of this relationship. The optimization process is characterized by the further exploration of the available behavioural repertoire and by the refinement of the dialogue between information and movement.

Neural prediction of complex accelerations for object interception

To intercept or avoid moving objects successfully, we must compensate for the sensorimotor delays associated with visual processing and motor movement. Although straightforward in the case of constant velocity motion, it is unclear how humans compensate for accelerations, as our visual system is relatively poor at detecting changes in velocity. Work on free-falling objects suggests that we are able to predict the effects of gravity, but this represents the most simple, limiting case in which acceleration is constant and motion linear. Here, we show that an internal model also predicts the effects of complex, varying accelerations when they result from lawful interactions with the environment. Participants timed their responses with the arrival of a ball rolling within a tube of various shapes. The pattern of errors indicates that participants were able to compensate for most of the effects of the ball acceleration (∼85%) within a relatively short practice (∼300 trials). Errors on catch trials in which the ball velocity was unexpectedly maintained constant further confirmed that participants were expecting the effect of acceleration induced by the shape of the tube. A similar effect was obtained when the visual scene was projected upside down, indicating that the mechanism of this prediction is flexible and not confined to ecologically valid interactions. These findings demonstrate that the brain is able to predict motion on the basis of prior experience of complex interactions between an object and its environment.

The Synergistic Organization of Muscle Recruitment Constrains Visuomotor Adaptation

Reaching to visual targets engages the nervous system in a series of transformations between sensory information and motor commands. That which remains to be determined is the extent to which the processes that mediate sensorimotor adaptation to novel environments engage neural circuits that represent the required movement in joint-based or muscle-based coordinate systems. We sought to establish the contribution of these alternative representations to the process of visuomotor adaptation. To do so we applied a visuomotor rotation during a center-out isometric torque production task that involved flexion/extension and supination/pronation at the elbow-joint complex. In separate sessions, distinct half-quadrant rotations (i.e., 45 degrees ) were applied such that adaptation could be achieved either by only rescaling the individual joint torques (i.e., the visual target and torque target remained in the same quadrant) or by additionally requiring torque reversal at a contributing joint (i.e., the visual target and torque target were in different quadrants). Analysis of the time course of directional errors revealed that the degree of adaptation was lower (by approximately 20%) when reversals in the direction of joint torques were required. It has been established previously that in this task space, a transition between supination and pronation requires the engagement of a different set of muscle synergists, whereas in a transition between flexion and extension no such change is required. The additional observation that the initial level of adaptation was lower and the subsequent aftereffects were smaller, for trials that involved a pronation-supination transition than for those that involved a flexion-extension transition, supports the conclusion that the process of adaptation engaged, at least in part, neural circuits that represent the required motor output in a muscle-based coordinate system.

Spatially constrained locomotion under informational conflict

This study investigates the informational based that supports intentional adaptation of locomotion to spatial environmental constraints. A virtual reality setup was used to present subjects with targets providing normal as well as abnormal optical expansion during locomotor pointing (i.e. positioning of a foot on a visible target on the floor during walking). The manipulation dissociated two variables providing temporal information about time-to-passage (TTP): TTP(beta alpha) which encompasses target expansion, and TTP(alpha) which is independent of target expansion. While a previous study showed TTP(alpha) to be sufficient, the present results reveal that TTP(beta alpha) may be used when it is available. This finding indicates that both variables play a role that varies according to the circumstances. Furthermore, the present results provide evidence of the operation of a security principle for action in conflicting situations.