Most neural network models till date have assumed all neurons to be identical, or at least that all neurons within a population are identical. In reality, no two neurons are completely the same.
Is this due to unavoidable "biological noise" that the nervous system has to cope with, or can it be a useful feature included by design?
The guest co-wrote the recent paper"How heterogeneity shapes dynamics and computation in the brain" addressing this question.
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