In this paper, an extension of the unsupervised topology-learning TopoART neural network is presented. Like TopoART, it is capable of stable incremental on-line clustering of real-valued data. However, it incorporates temporal information in such a way that consecutive input vectors with a low distance in the input space are summarised to episode-like clusters. Inspired by natural memory systems, we propose two recall methods enabling the selection and retrieval of these episodes. They are demonstrated at the example of a video stream recorded in a natural environment.