Using stimulus statistics to predict behavioral discrimination.

<p>Covariance along the Orthogonal dimension in each experiment (as measured by the second Eigenvalue of the covariance matrix of tested stimuli, λ₂) is along the abscissa, and effect size (Cohen’s <i>d</i>, calculated as the difference in mean discriminability between Consistent and Orthogonal stimuli, each averaged across experimental blocks) is along the ordinate. Positive values along the ordinate indicate Consistent stimuli were better discriminated than Orthogonal stimuli, while negative values indicate Orthogonal stimuli were better discriminated. Results from the present report are plotted as squares with each experiment labeled individually. Results from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161001#pone.0161001.ref024" target="_blank">24</a>] are plotted as triangles, and results from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161001#pone.0161001.ref026" target="_blank">26</a>] are plotted as circles. Experiment 1 from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161001#pone.0161001.ref026" target="_blank">26</a>], which is included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161001#pone.0161001.g002" target="_blank">Fig 2A</a> as a point of reference, is the upper-leftmost circle, which is also labeled. The solid line is the linear regression fit. Increasing covariance along the Orthogonal dimension clearly results in those stimuli being better-discriminated, but results from Experiment 5 are an outlier such that rare, extreme deviations from stimulus statistics are discriminated far better than predicted by covariance alone.