  A population of firing neurons is expected to carry information not only by
mean firing rate but also by fluctuation and synchrony among neurons. In order
to examine this possibility, we have studied responses of neuronal ensembles to
three kinds of inputs: mean-, fluctuation- and synchrony-driven inputs. The
generalized rate-code model including additive and multiplicative noise (H.
Hasegawa, Phys. Rev. E {\bf 75} (2007) 051904) has been studied by direct
simulations (DSs) and the augmented moment method (AMM) in which equations of
motion for mean firing rate, fluctuation and synchrony are derived. Results
calculated by the AMM are in good agreement with those by DSs. The independent
component analysis (ICA) of our results has shown that mean firing rate,
fluctuation (or variability) and synchrony may carry independent information in
the population rate-code model. The input-output relation of mean firing rates
is shown to have higher sensitivity for larger multiplicative noise, as
recently observed in prefrontal cortex. A comparison is made between results
obtained by the integrate-and-fire (IF) model and our rate-code model.
