Abstract
Accurate performance of reaching movements depends on adaptable neural
circuitry that learns to predict forces and compensate for limb dynamics.
In earlier experiments, we quantified generalization from training
at one arm position to another position. The generalization patterns
suggested that neural elements learning to predict forces coded a
limb's state in an intrinsic, muscle-like coordinate system. Here,
we test the sensitivity of these elements to the other arm by quantifying
inter-arm generalization. We considered two possible coordinate systems:
an intrinsic (joint) representation should generalize with mirror
symmetry reflecting the joint's symmetry and an extrinsic representation
should preserve the task's structure in extrinsic coordinates. Both
coordinate systems of generalization were compared with a naive control
group. We tested transfer in right-handed subjects both from dominant
to nondominant arm (D-->ND) and vice versa (ND-->D). This led to
a 2 x 3 experimental design matrix: transfer direction (D-->ND/ND-->D)
by coordinate system (extrinsic, intrinsic, control). Generalization
occurred only from dominant to nondominant arm and only in extrinsic
coordinates. To assess the dependence of generalization on callosal
inter-hemispheric communication, we tested commissurotomy patient
JW. JW showed generalization from dominant to nondominant arm in
extrinsic coordinates. The results suggest that when the dominant
right arm is used in learning dynamics, the information could be
represented in the left hemisphere with neural elements tuned to
both the right arm and the left arm. In contrast, learning with the
nondominant arm seems to rely on the elements in the nondominant
hemisphere tuned only to movements of that arm.
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