August 2014
Volume 14, Issue 10
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Visuomotor adaptation to random rotation transformations in a continuous tracking paradigm
Author Affiliations
  • Katherine Snyder
    Center for Perceptual Systems, The University of Texas at Austin
  • Lawrence Cormack
    Center for Perceptual Systems, The University of Texas at Austin
  • Mary Hayhoe
    Center for Perceptual Systems, The University of Texas at Austin
Journal of Vision August 2014, Vol.14, 662. doi:10.1167/14.10.662
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      Katherine Snyder, Lawrence Cormack, Mary Hayhoe; Visuomotor adaptation to random rotation transformations in a continuous tracking paradigm. Journal of Vision 2014;14(10):662. doi: 10.1167/14.10.662.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Stability of visuomotor mapping influences the rate of visuomotor adaptation, with lower stability yielding faster learning and forgetting (e.g. Braun et al, 2009) and the flexibility gained from such quick learning and forgetting can make participants more adversely affected by unexpected perturbations (Seidler et al, 2004). In our studies, participants continuously tracked a randomly moving target on screen with a computer mouse while cursor position was transformed through multiple rotation angles, yielding a rich data set of target and response time series. In study 1, participants experienced blocks where cursor rotation varied sinusoidally with time at a frequency of 0.125, 0.25, 0.5 or 1 Hz. In other blocks the transformation varied in a square wave, or as a weighted sum of sine and square wave. The square wave function resulted in higher distance error after the perturbation from minimum to maximum angle than did the sine wave at the same phase, indicating that increases in perturbation size increase error. Additionally, after the perturbation, peak distance from cursor to target decreased with increasing transformation function frequency. In contrast, distance error increased with increasing transformation function frequency for the 300 ms before the perturbation. Thus, fixed transformations decrease post-adaptation error but increase susceptibility to perturbations. In study 2, rotation angle was disassociated from its rate of change by using a random walk instead of a periodic function. Participants tracked a target through a randomly rotating transformation within three different ranges of angles. Preliminary spike-triggered average analysis suggests that both angle and its derivative contribute to distance error. Additionally, we observed minimum cursor heading errors near the mean angle of each block, indicating participants adapt to the mean angle. Together, these results (and this technique more generally) provide insight about the dynamics of visuomotor adaptation in a naturalistic dynamic tracking task.

Meeting abstract presented at VSS 2014

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