Figure 1: This graph shows the kernels implied by the recognition dynamics in (2.9) that accumulate evidence for changes in the conditional estimates of model parameters. These kernels are applied to the history of free-energy gradients to produce changes in the conditional mean (solid line) and its motion (broken line). The kernels are derived from a standard Volterra-series expansion about the true conditional mean, where, in this example, κ=4.