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. 2007 Apr;178(4):565-70.
doi: 10.1007/s00221-007-0936-x. Epub 2007 Mar 23.

The dominant and nondominant arms are specialized for stabilizing different features of task performance

Jinsung Wang  1 , Robert L Sainburg
Affiliations

The dominant and nondominant arms are specialized for stabilizing different features of task performance

Jinsung Wang et al. Exp Brain Res. 2007 Apr.

Abstract

We have previously proposed a model of motor lateralization, in which the two arms are differentially specialized for complementary control processes. During aimed movements, the dominant arm shows advantages for coordinating intersegmental dynamics as required for specifying trajectory speed and direction, while the nondominant arm shows advantages in controlling limb impedance, as required for accurate final position control. We now directly test this model of lateralization by comparing performance of the two arms under two different tasks: one in which reaching movement is made from one fixed starting position to three different _target positions; and the other in which reaching is made from three different starting positions to one fixed _target position. For the dominant arm, performance was most accurate when reaching from one fixed starting position to multiple _targets. In contrast, nondominant arm performance was most accurate when reaching toward a single _target from multiple start locations. These findings contradict the idea that motor lateralization reflects a global advantage of one "dominant" hemisphere/limb system. Instead, each hemisphere/limb system appears specialized for stabilizing different aspects of task performance.

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Figures

Fig. 1
Fig. 1
a Side view: subjects were seated in a chair with the arm supported by an air jet system that removed the effects of friction on arm movement. _targets and the cursor representing hand position were projected on a screen placed above the arm. b Top view: the positions of the start and _target circles, and the Flock of Birds sensors are shown. c Locations of the start and _target circles. The distance between every two _targets under each condition is 5 cm. The distance between the start circle and the closest _target is 15 cm. All these start and _target circles are linearly aligned on the midline relative to the subject’s body
Fig. 2
Fig. 2
a Changes in final accuracy performance across blocks. Thick lines represent mean data averaged across subects; thin lines represent SE. b Mean performance measures of constant error (mean ± SE). *A significant difference at P < 0.05. c Scatter plots representing the distribution of data for each condition. Small circles, triangles and squares represent data from the movements made to the near, middle and far _targets, respectively
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