Sensorimotor control and linear visuomotor gains.

In everyday life, we often use graphical interfaces where the visual space is mapped to the motor space with a visuomotor gain called the control display gain. One of the key objectives in the field of Human Computer Interaction is to design this control display gain so as to enhance users' performance. Although the control display gain involved in operating systems has been found to improve users' pointing performance, the reasons for this improvement have not yet been fully elucidated, especially because the control display gains on operating systems are both non-constant and non-linear. Here, we tested non-constant but linear velocity-based control display gains to determine which parameters were responsible for pointing performance changes based on analyses of the movement kinematics. Using a Fitts' paradigm, constant gains of 1 and 3 were compared with a linearly increasing gain (i.e., the control display gain increases with the motor velocity) and a decreasing gain (i.e., the control display gain decreases with the motor velocity). Three movements with various indexes of difficulty (ID) were tested (3, 5 and 7 bits). The increasing gain was expected to increase the velocity of the initial impulse phase and decrease that of the correction phase, thus decreasing the movement time (MT), and the contrary in the case of the decreasing gain. Although the decreasing gain increased MT at ID3, the increasing gain was found to be less efficient than the constant gain of 3, probably because a non-constant gain between the motion and its visual consequences disrupted the sensorimotor control. In addition, the kinematic analyses of the movements suggested that the motion profile was planned by the central nervous system based on the visuomotor gain at maximum motor velocity, as common features were observed between the constant gain of 1 and the decreasing gain, and between the constant gain of 3 and the increasing gain. By contrast, the amplitude of the velocity profile seemed to be specific to each particular visuomotor mapping process.

Adaptive use of interaction torque during arm reaching movement from the optimal control viewpoint.

The study aimed at investigating the extent to which the brain adaptively exploits or compensates interaction torque (IT) during movement control in various velocity and load conditions. Participants performed arm pointing movements toward a horizontal plane without a prescribed reach endpoint at slow, neutral and rapid speeds and with/without load attached to the forearm. Experimental results indicated that IT overall contributed to net torque (NT) to assist the movement, and that such contribution increased with limb inertia and instructed speed and led to hand trajectory variations. We interpreted these results within the (inverse) optimal control framework, assuming that the empirical arm trajectories derive from the minimization of a certain, possibly composite, cost function. Results indicated that mixing kinematic, energetic and dynamic costs was necessary to replicate the participants' adaptive behavior at both kinematic and dynamic levels. Furthermore, the larger contribution of IT to NT was associated with an overall decrease of the kinematic cost contribution and an increase of its dynamic/energetic counterparts. Altogether, these results suggest that the adaptive use of IT might be tightly linked to the optimization of a composite cost which implicitly favors more the kinematic or kinetic aspects of movement depending on load and speed.

On the nature of motor planning variables during arm pointing movement: Compositeness and speed dependence.

The purpose of this study was to investigate the nature of the variables and rules underlying the planning of unrestrained 3D arm reaching. To identify whether the brain uses kinematic, dynamic and energetic values in an isolated manner or combines them in a flexible way, we examined the effects of speed variations upon the chosen arm trajectories during free arm movements. Within the optimal control framework, we uncovered which (possibly composite) optimality criterion underlays at best the empirical data. Fifteen participants were asked to perform free-endpoint reaching movements from a specific arm configuration at slow, normal and fast speeds. Experimental results revealed that prominent features of observed motor behaviors were significantly speed-dependent, such as the chosen reach endpoint and the final arm posture. Nevertheless, participants exhibited different arm trajectories and various degrees of speed dependence of their reaching behavior. These inter-individual differences were addressed using a numerical inverse optimal control methodology. Simulation results revealed that a weighted combination of kinematic, energetic and dynamic cost functions was required to account for all the critical features of the participants' behavior. Furthermore, no evidence for the existence of a speed-dependent tuning of these weights was found, thereby suggesting subject-specific but speed-invariant weightings of kinematic, energetic and dynamic variables during the motor planning process of free arm movements. This suggested that the inter-individual difference of arm trajectories and speed dependence was not only due to anthropometric singularities but also to critical differences in the composition of the subjective cost function.