Description and results of simulation 1.

A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main text for details. C: Classifier accuracy scores for model-generated data from both levels of the context dimension. The y-axis represents accuracy scores, the x-axis represents level of measurement noise (in units of standard deviation), the dotted line represents chance performance. D: Proportion of positive tests of each type. The y-axis represents proportion of positives, the x-axis represents measurement noise, the dotted line represents the accepted false discovery rate of 5%. Panels E-F show the proportion of each type of conclusion in Table 1 (specificity/sensitivity in red, invariance/tolerance in blue, and no conclusion in green) reached from jointly testing against specificity and invariance. In both cases, the cross-classification test is used against specificity. E: Conclusions reached by using the classification accuracy invariance test against invariance. F: Conclusions reached by using the decoding separability test against invariance. This figure includes public domain clipart and all other parts are original: https://freesvg.org/binary-file-vector-graphics.