# 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?

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.