Pointing in 3D Space to Remembered Targets. I. Kinesthetic Versus Visual Target Presentation

Abstract

This study investigated the influence of different modalities of target information (visual, kinesthetic) on the accuracy, kinematics, and interjoint coordination of pointing movements to remembered targets. The targets were presented by a robot arm in five locations in three-dimensional (3D) space, either as a point of light in a dark room ("visual" condition), or kinesthetically. Relative pointing accuracy in the visual compared with kinesthetic conditions was influenced by the target location: pointing errors were the largest for the visual targets most eccentric relative to the subject's head. In addition, for the two most lateral targets, the final arm positions were, on average, closer to the center than the targets in the visual condition and farther from the center than the targets in the kinesthetic conditions. This result suggests that the pattern of errors in the visual condition described elsewhere ("range effect") may derive from visual processing rather than motor planning and implementation. Two modes of kinesthetic target presentation were utilized. During "passive" kinesthetic presentation of the target, the experimenter moved the subject's relaxed arm. Alternately, in "active" kinesthetic presentation of the target, the subject actively (with minimal help from the experimenter) moved his arm. No visual feedback was allowed in either kinesthetic condition. The variability in the final fingertip position was significantly smaller in the active condition than in the passive condition. In contrast, variability in the final values of arm orientation angles did not differ significantly in the active and passive conditions. This apparent contradiction may be resolved by the fact that, for the given target location, the influence of the deviation of these angles in the given trial from their average values on the position of the fingertip tended to be mutually compensated, and this tendency was stronger in the active condition. Our analysis of the correlations among the arm orientation angles and of the relationship between the initial and final arm configurations suggests that the kinesthetic conditions enabled the implementation of a mixture of strategies for achieving accuracy. The first strategy is to use a specific memory of an adequate arm configuration (that assumed during target presentation), such that accuracy is achieved by using this memory as a template. The second strategy is to use synergistically coordinating joint angles, such that accuracy is achieved by focusing on a specific endpoint that can be reached by a range of equivalent arm positions. The latter strategy was better utilized in the active condition. In conclusion, our results indicate that human subjects can use diverse sensory information to achieve comparable final accuracy, but that the details of the strategies employed differ with the kind of information available.

Predictive Modeling by the Cerebellum Improves Proprioception

“…Controls demonstrated better precision of proprioception in the active-simple task (Task 2) compared with the passive task (Fig. 2, t ϭ 3.67, p Ͻ 0.005), as expected (Adamovich et al, 1998;Fuentes and Bastian, 2010). However, their performance was not improved in the active-complex task (Task 3)-it was no different from the passive task (Fig.…”

“…Cerebellar patients have the same precision as controls in passive proprioception, but whereas controls improve with active movement (Adamovich et al, 1998;Zia et al, 2000;Laufer et al, 2001;Fuentes and Bastian, 2010), patients do not. Importantly, we show that not all self-generated movement improves proprioception; when control subjects encounter unpredictable forces during movement, their active proprioceptive precision worsens to passive levels.…”

“…Efference-copy-based predictions of body position could augment peripheral proprioceptive signals after self-generated movements (Adamovich et al, 1998). This contribution would be distinct from ␣-gamma motor neuron modulation of muscle spindles (Paillard and Brouchon, 1974;Jones et al, 2001).…”

“…Normally, proprioception after active movements is more precise (i.e., less variable) than after similar passive movements (Paillard and Brouchon, 1974;Adamovich et al, 1998;Fuentes and Bastian, 2010). Efference-copy-based predictions of body position could augment peripheral proprioceptive signals after self-generated movements (Adamovich et al, 1998).…”

Differences in curvature between constrained and unconstrained goal-directed movements to haptic targets

“…Although it is known that endpoint accuracy is better when moving towards visual targets than when moving towards haptic targets (van Beers et al 1998), the curvature in movement trajectories hardly differs (Adamovich et al 1998;Haggard and Richardson 1996). Movement times were around 3.5 s in our study, whereas they were around 0.5 s in other studies (Bongers and Zaal 2010;Desmurget et al 1997;Palluel-Germain et al 2004).…”