  We generalize a previously proposed approach for nonlinear Granger causality
of time series, based on radial basis function. The proposed model is not
constrained to be additive in variables from the two time series and can
approximate any function of these variables, still being suitable to evaluate
causality. Usefulness of this measure of causality is shown in a physiological
example and in the study of the feed-back loop in a model of excitatory and
inhibitory neurons.
