John de Grosbois

Amending Ongoing Upper-Limb Reaches: Visual and Proprioceptive Contributions?

In order to maximize the precise completion of voluntary actions, humans can theoretically utilize both visual and proprioceptive information to plan and amend ongoing limb trajectories. Although vision has been thought to be a more dominant sensory modality, research has shown that sensory feedback may be processed as a function of its relevance and reliability. As well, theoretical models of voluntary action have suggested that both vision and proprioception can be used to prepare online trajectory amendments. However, empirical evidence regarding the use of proprioception for online control has come from indirect manipulations from the sensory feedback (i.e., without directly perturbing the afferent information; e.g., visual-proprioceptive mismatch). In order to directly assess the relative contributions of visual and proprioceptive feedback to the online control of voluntary actions, direct perturbations to both vision (i.e., liquid crystal goggles) and proprioception (i.e., tendon vibration) were implemented in two experiments. The first experiment employed the manipulations while participants simply performed a rapid goal-directed movement (30 cm amplitude). Results from this first experiment yielded no significant evidence that proprioceptive feedback contributed to online control processes. The second experiment employed an imperceptible target jump to elicit online trajectory amendments. Without or with tendon vibration, participants still corrected for the target jumps. The current study provided more evidence of the importance of vision for online control but little support for the importance of proprioception for online limb-target regulation mechanisms.

Eye movements may cause motor contagion effects

When a person executes a movement, the movement is more errorful while observing another person’s actions that are incongruent rather than congruent with the executed action. This effect is known as “motor contagion”. Accounts of this effect are often grounded in simulation mechanisms: increased movement error emerges because the motor codes associated with observed actions compete with motor codes of the goal action. It is also possible, however, that the increased movement error is linked to eye movements that are executed simultaneously with the hand movement because oculomotor and manual-motor systems are highly interconnected. In the present study, participants performed a motor contagion task in which they executed horizontal arm movements while observing a model making either vertical (incongruent) or horizontal (congruent) movements under three conditions: no instruction, maintain central fixation, or track the model’s hand with the eyes. A significant motor contagion-like effect was only found in the ‘track’ condition. Thus, ‘motor contagion’ in the present task may be an artifact of simultaneously executed incongruent eye movements. These data are discussed in the context of stimulation and associative learning theories, and raise eye movements as a critical methodological consideration for future work on motor contagion.

Better together: Contrasting the hypotheses explaining the one-target advantage

Movement times are significantly shorter when moving from a start position to a single target, compared to when one has to continue onto a second target (i.e., the one-target advantage [OTA]). To explain this movement time difference, both the movement integration and the movement constraint hypotheses have been proposed. Although both hypotheses have been found to have explanatory power as to why the OTA exists, the support for each has been somewhat equivocal. The current review evaluated the relative support in the literature for these two hypotheses. Ultimately, preferential support for each theoretical explanation was found to be related to the higher indices of difficulty (IDs: Fitts, 1954) employed. That is, studies that included higher IDs (i.e., 6-8 bits) were more likely to provide more support for the movement constraint hypothesis, whereas studies employing lower IDs (i.e., 1-4 bits) were more likely to provide more support for the movement integration hypothesis. When the IDs employed were relatively intermediate (i.e., 5 bits), both hypotheses were mostly supported. Thus, task difficulty is crucial when determining which hypothesis better explains the planning and control of sequential goal-directed movements. Critically, the OTA most likely always involves integration but may also involve constraining if the accuracy demands are sufficiently high.

Can You Hear That Peak? Utilization of Auditory and Visual Feedback at Peak Limb Velocity

Purpose: At rest, the central nervous system combines and integrates multisensory cues to yield an optimal percept. When engaging in action, the relative weighing of sensory modalities has been shown to be altered. Because the timing of peak velocity is the critical moment in some goal-directed movements (e.g., overarm throwing), the current study sought to test whether visual and auditory cues are optimally integrated at that specific kinematic marker when it is the critical part of the trajectory. Methods: Participants performed an upper-limb movement in which they were required to reach their peak limb velocity when the right index finger intersected a virtual target (i.e., a flinging movement). Brief auditory, visual, or audiovisual feedback (i.e., 20 ms in duration) was provided to participants at peak limb velocity. Performance was assessed primarily through the resultant position of peak limb velocity and the variability of that position. Results: Relative to when no feedback was provided, auditory feedback significantly reduced the resultant endpoint variability of the finger position at peak limb velocity. However, no such reductions were found for the visual or audiovisual feedback conditions. Further, providing both auditory and visual cues concurrently also failed to yield the theoretically predicted improvements in endpoint variability. Conclusions: Overall, the central nervous system can make significant use of an auditory cue but may not optimally integrate a visual and auditory cue at peak limb velocity, when peak velocity is the critical part of the trajectory.