The functional plausibility of topologically extended models of RBMs as hippocampal models

The hippocampus has distinctive functional and structural properties. In this research, we utilize Restricted Boltzmann Machines (RBMs) based models inspired by distinctive structures found in hippocampus; neurogenesis in the dentate gyrus (DG) and recurrent connections in CA3. We review two types of topologically extended models of RBMs inspired by hippocampus. In one type of models, units are dynamically added during the training phase, and in the other type, connections are partly recursive. We analyzed these models both as separate models and combined model. The two types of the proposed models implement functions that the hippocampus has but the classical RBMs don't. Furthermore, by combining the two proposed models, memorization of chronologically ordered data and memory reconstruction tasks' performance improved significantly.