  A dynamical mean-field approximation (DMA) previously proposed by the present
author [H. Hasegawa, Phys. Rev E {\bf 67}, 041903 (2003)] has been extended to
ensembles described by a general noisy spiking neuron model. Ensembles of
$N$-unit neurons, each of which is expressed by coupled $K$-dimensional
differential equations (DEs), are assumed to be subject to spatially correlated
white noises. The original $KN$-dimensional {\it stochastic} DEs have been
replaced by $K(K+2)$-dimensional {\it deterministic} DEs expressed in terms of
means and the second-order moments of {\it local} and {\it global} variables:
the fourth-order contributions are taken into account by the Gaussian
decoupling approximation. Our DMA has been applied to an ensemble of
Hodgkin-Huxley (HH) neurons (K=4), for which effects of the noise, the coupling
strength and the ensemble size on the response to a single-spike input have
been investigated. Results calculated by DMA theory are in good agreement with
those obtained by direct simulations.
