Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis
Fig 8
Model selection accuracy and execution time for likelihood-based RSA, PCM, and encoding analysis with regularization.
(A-C) Model-selection accuracy was inferentially compared between the three techniques on the basis of N = 3,000 simulations, using a likelihood-ratio test of counts of correct model decisions [51]. The signal-strength parameter for the simulation was set to s = 0.3 for Exp. 1, s = 0.15 for Exp. 2, and s = 0.5 for Exp. 3. All resulting significant differences (two-tailed, p<0.01, uncorrected) are indicated by a horizontal line above the bars. (D-F) Execution times for the evaluation of a single data set under a single model. For encoding, the time is split into the time required to estimate regression coefficients (dark blue) and the time to determine the regularization constant (light blue).