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Multifunctionality is a well observed phenomenological feature of biological neural networks and considered to be of fundamental importance to the survival of certain species over time. These multifunctional neural networks are capable of performing more than one task without changing any network connections. In this paper, we investigate how this neurological idiosyncrasy can be achieved in an artificial setting with a modern machine learning paradigm known as "reservoir computing." A training technique is designed to enable a reservo