For example, in Cessac 1995 "Increase in complexity in random neural networks" he proved that in the mean-field approximation the transition to chaos is very sharp, while in the real network it develops through the emergence of a limit cycle and a torus. Do you know other examples? I would like to know if there are cases when the mean-field approximation completely neglects important dynamical phenomena.Thanks in advance for any help you may provide.

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