In this paper we introduce a novel approach for building 4D coupled statistical mod-els of conversational facial expression interactions. To build these coupled models we use 3D AAMs for feature extraction, 4D polynomial fitting for sequence representation, and concatenated feature vectors of frontchannel-backchannel interactions (with offset values) for the coupled model. Using a coupled model of conversation smile interactions, we predicted each se-quence’s backchannel signal. In a subsequent experiment, human observers rated pre-dicted sequences as highly similar to the originals. Our results demonstrate the usefulness of coupled models as powerful tools to analyse and synthesise key aspects of conversa-tional interactions, including conversation timings, backchannel responses to frontchan-nel signals, and the spatial and temporal dynamics of conversational facial expression interactions. 1