Previous work has revealed that social cues, such as gaze and pointed fingers, can lead to a shift in the focus of another person’s attention. Research investigating the mechanisms of these shifts of attention has typically employed detection or localization button-pressing tasks. Because in-depth analyses of the spatiotemporal characteristics of aiming movements can provide additional insights into the dynamics of the processing of stimuli, in the present study we used a reaching paradigm to further explore the processing of social cues. In Experiments 1 and 2, participants aimed to a left or right location after a nonpredictive eye gaze cue toward one of these target locations. Seven stimulus onset asynchronies (SOAs), from 100 to 2,400 ms, were used. Both the temporal (reaction time, RT) and spatial (initial movement angle, IMA) characteristics of the movements were analyzed. RTs were shorter for cued (gazed-at) than for uncued targets across most SOAs. There were, however, no statistical differences in IMAs between movements to cued and uncued targets, suggesting that action planning was not affected by the gaze cue. In Experiment 3, the social cue was a finger pointing to one of the two target locations. Finger-pointing cues generated significant cueing effects in both RTs and IMAs. Overall, these results indicate that eye gaze and finger-pointing social cues are processed differently. Perception–action coupling (i.e., a tight link between the response and the social cue that is presented) might play roles in both the generation of action and the deviation of trajectories toward cued and uncued targets.
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Although the entire movement trajectory was recorded, we chose to analyze movement angle at only one point, 20% of MT (for discussions of techniques that may be used to analyze the whole trajectory, see Gallivan & Chapman, 2014; Lins & Schöner, 2019). This time point of 20% of the MT (which falls approximately at the peak acceleration) was chosen because we believe this point (and similar points early in the trajectory) provides an accurate characterization of the movement planning activated by the stimuli at movement initiation. Because the movements in the present study were executed in full vision, time points later in the trajectories might be contaminated by any online correction processes as the movements converged on the target endpoint as the movement unfolded. Hence, the chosen time point is likely to best represent the simultaneous activation of competing response codes, without contamination from online corrections to movement. Although we report only the analysis of this one point, we conducted a subsequent analysis of additional time points (40%, 60%, and 80% of MT) for each experiment. The results of the analyses of variance when all these time points were included were consistent with the analysis of IMAs at only 20% of MT that is reported in the present article.
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This research was supported by grants and scholarships from the Natural Sciences and Engineering Research Council of Canada. The authors thank Joëlle Hajj and Saba Taravati for their help with data collection.
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Yoxon, E., Constable, M.D. & Welsh, T.N. Probing the time course of facilitation and inhibition in gaze cueing of attention in an upper-limb reaching task. Atten Percept Psychophys 81, 2410–2423 (2019). https://doi.org/10.3758/s13414-019-01821-5
- Eye movements
- Visual attention
- Goal-directed movements