Motor planning: effect of directional uncertainty with discrete spatial cues

Abstract

We investigated the effect of spatial uncertainty on motor planning by using the cueing method in a reaching task (experiment 1). Discrete spatial cues indicated the different locations in which the target could be presented. The number of cues as well as their direction changed from trial to trial. We tested the adequacy of two models of motor planning to account for the data. The switching model assumes that only one motor response can be planned at a time, whereas the capacity-sharing model assumes that multiple motor responses can be planned in parallel. Both models predict the same relation between average reaction time (RT) and number of cues, but they differ in their prediction of the shape of the distribution of the reaction time. The results showed that RT increased with the number of cues independently from their spatial dispersion. This relation was well described by the function predicted by both models, whereas it was poorly described by the Hick-Hyman law. In addition, the distribution of RT conformed to the prediction of the capacity-sharing model and not to that of the switching model. We investigated the role that the requirement of a spatially directed motor response might have had on this pattern of results by testing subjects in a simple RT task (experiment 2) with the same cueing presentation as in experiment 1. The results contrasted with those in experiment 1 and showed that RT was dependent on the spatial dispersion of the cues and not on their number. The results of the two experiments suggest that the mode of processing of potential targets is dependent on the spatial constraints of the task. The processing resources can be either divided relative to the spatial distribution of possible targets or across multiple independent discrete representations of these targets.

Beta-Band Activity during Motor Planning Reflects Response Uncertainty

“…The analyses indicated that RT was significantly affected by number of cues (F (2,4) ϭ 24.730; p ϭ 0.006), whereas MT was not (F (2,4) ϭ 0.186; p ϭ 0.837). As expected, these results show that increasing the number of possible target locations increased RT, which is consistent with the results obtained previously with a similar experimental paradigm (Pellizzer and Hedges, 2003;Pellizzer et al, 2006).…”

“…For example, it is known that the latency of motor responses increases progressively with the number of possible movement directions, which indicates that the level of motor preparation covaries with the degree of directional uncertainty (Bock and Arnold, 1992;Basso and Wurtz, 1998;Dorris and Munoz, 1998;Pellizzer and Hedges, 2003;Kveraga et al, 2006;Pellizzer et al, 2006;Churchland et al, 2008). Consequently, if both response latency and beta-band ERD reflect the complexity of motor preparation, we expect beta-band ERD to be modulated by directional uncertainty as well.…”

Linking Perception, Cognition, and Action: Psychophysical Observations and Neural Network Modelling

“…The Area, Decision Changes, Number of Submovements and Maximum Velocity (Fig. 4B) evidently varied in accordance with MT’s changes, as has been reported in other studies [25], [26]. This pattern can be due to subjects beginning their movement before they reach a decision (shorter RT) and deciding while they move (longer MT) as long as targets are close to each other, since in this case a slight trajectory modification would be enough to reach the desired target.…”

Competitive interactions in sensorimotor cortex: oscillations express separation between alternative movement targets

“…A few previous studies have also used a delay between target exposition and response signal. Similar to the present study, Pellizzer and Hedges (2003) found, for their two-target condition, no effect of target separation. Praamstra et al (2009) reported extremely small (Ͻ10 ms) effects.…”