Transfer of Motor Learning across Arm Configurations

Abstract

It has been suggested that the learning of new dynamics occurs in intrinsic coordinates. However, it has also been suggested that elements that encode hand velocity, and hence act in an extrinsic frame of reference, play a role in the acquisition of dynamics. To reconcile claims regarding the coordinate system involved in the representation of dynamics, we have used a procedure involving the transfer of force-field learning between two workspace locations. Subjects made point-to-point movements while holding a two-link manipulandum. Subjects were first trained to make movements in a single direction at the left of the workspace. They were then tested for transfer of learning at the right of the workspace. Two groups of subjects were defined. For the subjects in group j, movements at the left and right workspace locations were matched in terms of joint displacements. For the subjects in group h, movements in the two locations had the same hand displacements. Workspace locations were chosen such that for group j, the paths (for training and testing) that were identical in joint space were orthogonal in hand space. The subjects in group j showed good transfer between workspace locations, whereas the subjects in group h showed poor transfer. These results are in agreement with the idea that new dynamics are encoded in intrinsic coordinates and that this learning has a limited range of generalization across joint velocities.

Observed effector-independent motor learning by observing

“…Work on motor learning shows that novel dynamics are represented in intrinsic, muscle-based coordinate frames (Malfait et al 2002;Shadmehr 2004). Another well-documented feature of dynamics learning is that generalization (for example, to other movement directions) is rather limited Gandolfo et al 1996;Mattar and Ostry 2007;Thoroughman and Shadmehr 2000;Tremblay et al 2008).…”

“…Performance on each of the 96 reaching movement trials was assessed on a trial by trial basis using custom software written in MATLAB (The Mathworks). Performance on each trial was based on hand trajectory curvature, which was characterized by calculating the maximum perpendicular deviation of the hand path from a straight-line segment linking the start and end positions of movement (Brashers-Krug et al 1996;Malfait et al 2002;Thoroughman and Shadmehr 1999). Scores for each movement were averaged across bins of eight movements.…”

“…In contrast, studies of motor learning show that information about novel forces is represented in an intrinsic, muscle-based coordinate system (Malfait et al 2002;Shadmehr 2004), and that generalization of dynamics learning to adjacent movement directions is limited Gandolfo et al 1996;Mattar and Ostry 2007;Thoroughman and Shadmehr 2000;Tremblay et al 2008). While some instances of interlimb transfer have been reported (Criscimagna-Hemminger et al 2003;Sainburg and Wang 2002), once cognitive influences are removed, no interlimb transfer is observed for dynamics learning (Malfait and Ostry 2004).…”

The role of kinematic redundancy in adaptation of reaching

“…Motor adaptation is a similar phenomenon that has received much recent attention but has, to our knowledge, never been addressed from this perspective Buch et al 2003;Malfait et al 2005Malfait et al ,2002Shadmehr and Mussa-Ivaldi 1994;Wang and Sainburg 2004a,b). A common experimental paradigm used to study motor adaptation has been reaching in unusual force fields Shadmehr et al 1995;Shadmehr and Mussa-Ivaldi 1994).…”

Dissociable effects of the implicit and explicit memory systems on learning control of reaching

“…For example, when people practice reaching in a force field, it appears that the brain associates the limb state in which forces were experienced to the motor command that are necessary to negate the forces (Conditt et al, 1997). The coordinate system in which limb state is represented in this computation is joint-like rather than Cartesian, resulting in generalization patterns that are in the intrinsic coordinates of the arm (Shadmehr and Moussavi, 2000;Malfait et al, 2002). This pattern of generalization is consistent with the hypothesis that the brain relies primarily on proprioception to represent limb state for the purpose of transforming a movement plan into motor commands.…”