Hierarchical Models in the Brain
Figure 4
Example of Factor Analysis using a hierarchical model, in which the causes have deterministic and stochastic components.
Parameters and causes were sampled from the unit normal density to generate a response, which was then used for their estimation. The aim was to recover the causes without knowing the parameters, which is effected with reasonable accuracy (upper). The conditional estimates of the causes and parameters are shown in lower panels, along with the increase in free-energy or log-evidence, with the number of DEM iterations (lower left). Note that there is an arbitrary affine mapping between the conditional means of the causes and their true values, which we estimated, post hoc to show the correspondence in the upper panel.
