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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?

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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.

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