1. A method for managing synapse plasticity in an artificial neural network, comprising determining whether a number of plastic synapse types defined for the artificial neural network is greater than a hardware limit; and converting at least one of: a first set of synapses from a plastic synapse type to a fixed synapse type when the first set of synapses is designated as unused, a second set of synapses from the fixed synapse type to the plastic synapse type when the second set of synapses is designated as used, or a combination thereof, when the number of defined plastic synapse types is greater than the hardware limit, such that a number of active plastic synapse types is less than or equal to the hardware limit.