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A Bayesian hierarchical model of trial-to-trial fluctuations in decision criterion

Fig 4

Recovery of the per-subject parameters of the hMFC model.

A) The covariate weights w show excellent recovery even with low trial numbers (note that the lines for the different weights overlap). The model is able to recover a_i and very well with high trial numbers, but recovery drops with a limited number of data points per subject. Each dot represents the recovery correlation for one dataset. Note that error bars (standard error) are shown but they are very small. B-E) The recovery for a_i (B) and (C) and (D) and covariate weights w_i,0, w_i,1, w_i,2 (E) is shown for an example dataset with 500 trials and 5000 trials per subject. Each dot represents one subject. The line shows the diagonal.

doi: https://doi.org/10.1371/journal.pcbi.1013291.g004