The hippocampus is a central structure of the vertebrate brain, and plays a key role in the formation and processing of memories. Comprised of several highly interconnected sub-regions, it is characterized by a complex network architecture involving both feed-forward and feedback loops. In the past, various computational models of the hippocampus have been proposed. However, these were either lacking in physiological details, or required significant computational resources. With this work, we propose a novel human hippocampal model, which is both solidly grounded in physiological details, and has low computational requirements, allowing for the investigation of various physiological or pathological conditions. Here, we describe the model in detail, and demonstrate how its architecture supports firing rates typical of a resting hippocampus, and the spontaneous generation of characteristic hippocampal theta oscillations.