How well does the NEF capture neuronal heterogeneity? From what I understand of the Neurogical Engineering Framework (NEF), groups of neurons are used to compute functions. However, I'm not clear if these calculations take into account neurons of different shapes/sizes and their attributes/uses in the brain. How well does the NEF capture heterogeneity and how is it used?
To review how neurons encode information, please check out these class notes review encoding.

In those notes, you'll notice the intercept $J_{bias}$ and the maximum firing rate $\alpha$ are randomly selected when encoding functions in large populations of neurons. These variations can account for heterogeneity in attributes of neurons.