In a previous model , a spectral timing neural network  was used to account for the role of the Hs in the acquisition of classical conditioning. The ability to estimate the timing between separate events was then used to learn and predict transitions between places in the environment. We propose a neural architecture based on this work and explaining the out-of-field activities in the Hs along with their temporal prediction capabilities. The model uses the hippocampo-cortical pathway as a means to spread reward signals to entorhinal neurons. Secondary predictions of the reward signal are then learned, based on transition learning, by pyramidal neurons of the CA region.