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. 2013 May 23;9(5):e1003080. doi: 10.1371/journal.pcbi.1003080

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© 2013 Zhang et al

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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A. End points of one subject in the training task. Blue dots denote end points. The grey filled circle denotes the target. Yellow diamond marks the centroid of the target. The distribution of the errors is bivariate Gaussian, elongated in the vertical direction. B. Q-Q plots for the end points of the subject. The quantiles of the horizontal and vertical positions of the end points are plotted against the standard normal quantiles. The linear relationship in both directions implies that the distribution of the end points is bivariate Gaussian. C. The standard deviations of the end points in the horizontal () and vertical () directions. Each point is for one subject. All subjects had a larger than . That is, their distributions were vertically elongated. The median -to- ratio across subjects was 1.44.

Inline graphic — A. End points of one subject in the training task. Blue dots denote end points. The grey filled circle denotes the target. Yellow diamond marks the centroid of the target. The distribution of the errors is bivariate Gaussian, elongated in the vertical direction. B. Q-Q plots for the end points of the subject. The quantiles of the horizontal and vertical positions of the end points are plotted against the standard normal quantiles. The linear relationship in both directions implies that the distribution of the end points is bivariate Gaussian. C. The standard deviations of the end points in the horizontal () and vertical () directions. Each point is for one subject. All subjects had a larger than . That is, their distributions were vertically elongated. The median -to- ratio across subjects was 1.44.