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Can intention override the “automatic pilot”?

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Abstract

Previous research has suggested that the visuomotor system possesses an “automatic pilot” which allows people to make rapid online movement corrections in response to sudden changes in target position. Importantly, the automatic pilot has been shown to operate in the absence of visual awareness, and even under circumstances in which people are explicitly asked not to correct their ongoing movement. In the current study, we investigated the extent to which the automatic pilot could be “disengaged” by explicitly instructing participants to ignore the target jump (i.e., “NO-GO”), by manipulating the order in which the two tasks were completed (i.e., either “GO” or NO-GO first), and by manipulating the proportion of trials in which the target jumped. The results indicated that participants made fewer corrections in response to the target jump when they were asked not to correct their movement (i.e., NO-GO), and when they completed the NO-GO task prior to the task in which they were asked to correct their movement when the target jumped (i.e., the GO task). However, increasing the proportion of jumping targets had only a minimal influence on performance. Critically, participants still made a significant number of unintended corrections (i.e., errors) in the NO-GO tasks, even under explicit instructions not to correct their movement if the target jumped. Overall these data suggest that, while the automatic pilot can be influenced to some degree by top-down strategies and previous experience, the pre-potent response to correct an ongoing movement cannot be completely disengaged.

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Notes

  1. Previous work by Cressman et al. (2006) and Cameron et al. (2009a) has shown that reach trajectories begin to deviate toward the jumped target as early as 130–150 ms after the target jump.

  2. This temporal window should not be seen as absolute limit, but as a rough guideline. These time limits will undoubtedly be influenced by factors such as movement velocity, reach distance, and individual differences in visuomotor processing speed.

  3. We use the term “highly automatic” instead of “automatic” here because we feel it is a bit naïve to divide processes categorically into automatic or not automatic. Such a simple dichotomy sets the stage for the development of straw-man hypotheses which are easily rejected. Instead, we believe that many automatic processes lie on a continuum of automaticity with highly automatic processes on one end of the continuum and less automatic processes on the other (see MacLeod and Dunbar 1988). In some sense, the goal of the present study was to determine on which end of the continuum of automaticity the automatic pilot for reaching movements lies.

  4. We used a movement time constraint of 300 ms because previous work by Pisella and colleagues (2000) indicated that the largest proportion of “automatic” corrections occurred on trials in which movement times were between 200 and 300 ms.

  5. Previous research by Cressman et al. (2006) and Cameron et al. (2009a) has demonstrated that participants’ reach trajectories may significantly deviate towards the jumped target even when they were able to stop their movement in flight (i.e. the STOP condition). This suggests that the automatic pilot may have still have been ‘captured’ by the target jump even on trials where participants successfully stopped their movement. Given that we were only recording movement endpoint in this study, we were not able to index trials in which corrections initially deviated toward the target jump but ultimately landed at the initial target location (i.e. in the NO-GO condition). Therefore, these data likely represent a conservative estimate of the total number of corrections that occurred in the NO-GO tasks.

  6. One could argue that there is no adequate baseline condition with which to compare jump trials in the NO-GO task because on these trials participants are asked to ignore the target jump and point to the initial target location (which is no longer present on the screen). Presumably this would have increased movement endpoint error and variability in this condition and could lead to jump trials in this condition being incorrectly classified as corrected. To rule out this possibility, we conducted a separate analysis of the movement endpoints for jump trials in the NO-GO tasks that were classified as “not corrected” and compared them to the movement endpoints for the static trials in the same condition. This analysis revealed that the endpoints for the static trials and jump trials classified as not corrected in the NO-GO tasks were identical. This suggests that participants were accurately pointing to the initial target location on trials which were not corrected. Therefore, we can be certain that movements classified as corrected in the NO-GO task were truly corrected and were not misclassified as a consequence of an increase in movement variability. .

  7. Note that this does not pose a problem for how we classified jump trials as corrected in the NO-GO tasks. The classification of jump trials was done at an individual subject level which takes these differences in accuracy for static trials into account.

  8. In a subsequent analysis we examined whether the order in which the different conditions (i.e., 20 vs. 50% jump) were completed within a session had any influence on the percentage of movement corrections. This analysis revealed a significant main effect of task order (GO first vs. NO-GO first; F(1,16) = 5.49, p = 0.032), but no main effect of condition order (i.e., 20% jump first vs. 50% jump first; p = 0.63), and no task order × condition order (p = 0.71) or task x condition order (p = 0.22) interaction. Therefore, the order in which the different conditions were completed within a testing session had no significant influence on the percentage of corrections.

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Acknowledgments

The authors would like to thank Robert McIntosh for helpful comments on an earlier draft of this manuscript. This work was supported by a Heart and Stroke Foundation of Canada Postdoctoral Award to C.L.S. and a Canadian Institutes of Health Research (CIHR) operating grant to M.A.G.

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Correspondence to Melvyn A. Goodale.

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Striemer, C.L., Yukovsky, J. & Goodale, M.A. Can intention override the “automatic pilot”?. Exp Brain Res 202, 623–632 (2010). https://doi.org/10.1007/s00221-010-2169-7

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