Are there distinct neural representations of object and limb dynamics?
In recent studies of human motor learning, subjects learned to move the arm while grasping a robotic device that applied novel patterns of forces to the hand. Here, we examined the generality of force field learning. We tested the idea that contextual cues associated with grasping a novel object promote the acquisition and use of a distinct internal model, associated with that object. Subjects learned to produce point-to-point arm movements to targets in a horizontal plane while grasping a robotic linkage that applied either a velocity-dependent counter-clockwise or clockwise force field to the hand. Following adaptation, subjects let go of the robot and were asked to generate the same movements in free space. Small but reliable after-effects were observed during the first eight movements in free space, however, these after-effects were significantly smaller than those observed for control subjects who moved the robot in a null field. No reduction in retention was observed when subjects subsequently returned to the force field after moving in free space. In contrast, controls who reached with the robot in a NF showed much poorer retention when returning to a force field. These findings are consistent with the idea that contextual cues associated with grasping a novel object may promote the acquisition of a distinct internal model of the dynamics of the object, separate from internal models used to control limb dynamics alone.
Cothros
N
N
Department of Psychology, The University of Western Ontario, Social Science Bldg, N6A 5C2, London, ON, Canada.
Wong
J D
JD
Gribble
P L
PL
D000293:Adolescent; D000328:Adult; D001132:Arm / Q000294:innervation; D005260:Female; D007839:Functional Laterality; D018737:Hand Strength; D006801:Humans; D007858:Learning / Q000502:physiology*; D007866:Leg / Q000294:innervation; D008297:Male; D009043:Motor Activity / Q000502:physiology*; D009068:Movement / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D012371:Robotics