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Heather Neyedli, Timothy Welsh; Hit me with your best shot: Optimal movement planning with constantly changing decision parameters.. Journal of Vision 2012;12(9):424. doi: https://doi.org/10.1167/12.9.424.
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© ARVO (1962-2015); The Authors (2016-present)
Humans are able to rapidly select movements that will achieve the individual’s goal while avoiding negative outcomes. Trommerhäuser et al. (2003) showed that, in a rapid aiming task, people concentrated their movements around an ‘optimal movement endpoint’ that was modeled based on the participants’ endpoint variability and the cost associated with a penalty circle that partially overlapped the target circle. Participants adjusted their endpoint when the penalty circle cost or distance between the two circles changed; however, penalty value only changed between blocks of trials. In typical daily interactions, the values associated with our movement goal vary. The purpose of the present study was to determine whether participants can adjust their endpoint when the distance between the target and penalty circles and the value of the penalty circle changed trial-to-trial. Participants aimed to a target circle in the presence of an overlapping penalty circle and received 100 points for contact with the target alone, and lost points for contact with the penalty region. In one block, the penalty circle for a given trial was either orange or red indicating that the cost was -100 or -600 points, respectively. In the other block, the penalty circle either overlapped the target circle by 9 or 13.5mm.There was a significant difference in endpoint between the two values within each distance and penalty block. However, when compared to the optimal endpoint calculated from the model, participants showed a significantly smaller shift in endpoint between the two penalty values, but an optimal shift in the distance block. We suggest participants are more optimal with a random changing of distance because the distance between the two circles is an intrinsic property of the visual stimuli, whereas the color associated with each the penalty value requires additional cognitive resources to interpret and predict the potential costs.
Meeting abstract presented at VSS 2012
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