Unlearning Increases the Storage Capacity of Content Addressable Memories

The storage and retrieval of information in networks of biological neurons can be modeled by content addressable memories (CAMs). We show that the amount of information that can be stored in a CAM is substantially increased by an unlearning algorithm. The mechanisms for this increase are illustrated in terms of an energy function that describes the covergence properties of the network.