A method for creating and maintaining short-term memory using short-term plasticity, includes changing a gain of a synapse based on pre synaptic spike activity without regard to postsynaptic spike activity. The method also includes calculating the gain based on a continuously updated synaptic state variable associated with the short-term plasticity.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for creating and maintaining short-term memory using short-term plasticity in an artificial neural network, comprising: storing state information in a synapse of the artificial neural network based at least in part on a maintenance signal transmitted before or at a time when a gain of the synapse returns to a baseline value; and retrieving the state information as postsynaptic activity of a neuron receiving a postsynaptic transmission from the synapse. 2. The method of claim 1, further comprising adjusting the state information based at least in part on the maintenance signal. 3. The method of claim 2, in which the method further comprises: periodically receiving the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and periodically receiving additional maintenance signals, at the synapse, to increase the specific gain of the synapse. 4. The method of claim 2, in which the method further comprises: periodically receiving the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and periodically receiving fewer maintenance signals, at the synapse, to decrease the specific gain of the synapse. 5. The method of claim 1, in which a gain of the postsynaptic transmission comprises information corresponding to the state information. 6. An artificial neural network configured to create and maintain short-term memory using short-term plasticity, the artificial neural network comprising: a memory unit; and at least one processor coupled to the memory unit; the at least one processor being configured: to store state information in a synapse of the artificial neural network based at least in part on a maintenance signal transmitted before or at a time when a gain of the synapse returns to a baseline value; and to retrieve the state information as postsynaptic activity of a neuron receiving a postsynaptic transmission from the synapse. 7. The artificial neural network of claim 6, in which the at least one processor is further configured to adjust the state information based at least in part on the maintenance signal. 8. The artificial neural network of claim 7, in which the at least one processor is further configured: to periodically receive the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and to periodically receive additional maintenance signals, at the synapse, to increase the specific gain of the synapse. 9. The artificial neural network of claim 7, in which the at least one processor is further configured: to periodically receive the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and to periodically receive fewer maintenance signals, at the synapse, to decrease the specific gain of the synapse. 10. The artificial neural network of claim 6, in which a gain of the postsynaptic transmission comprises information corresponding to the state information. 11. An apparatus for creating and maintaining short-term memory using short-term plasticity in an artificial neural network, comprising: means for storing state information in a synapse of the artificial neural network based at least in part on a maintenance signal transmitted before or at a time when a gain of the synapse returns to a baseline value; and means for retrieving the state information as postsynaptic activity of a neuron receiving a postsynaptic transmission from the synapse. 12. The apparatus of claim 11, further comprising means for adjusting the state information based at least in part on the maintenance signal. 13. The apparatus of claim 12, further comprising: means for periodically receiving the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and means for periodically receiving additional maintenance signals, at the synapse, to increase the specific gain of the synapse. 14. The apparatus of claim 12, further comprising: means for periodically receiving the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and means for periodically receiving fewer maintenance signals, at the synapse, to decrease the specific gain of the synapse. 15. The apparatus of claim 11, in which a gain of the postsynaptic transmission comprises information corresponding to the state information. 16. A non-transitory computer-readable medium having program code recorded thereon for creating and maintaining short-term memory using short-term plasticity in an artificial neural network, the program code comprising: program code to store state information in a synapse based at least in part on a maintenance signal transmitted before or at a time when a gain of the synapse returns to a baseline value; and program code to retrieve the state information as postsynaptic activity of a neuron receiving a postsynaptic transmission from the synapse. 17. The non-transitory computer-readable medium of claim 16, in which the program code further comprises program code to adjust the state information based at least in part on the maintenance signal. 18. The non-transitory computer-readable medium of claim 17, in which the program code further comprises: program code to periodically receive the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and program code to periodically receive additional maintenance signals, at the synapse, to increase the specific gain of the synapse. 19. The non-transitory computer-readable medium of claim 17, in which the program code further comprises: program code to periodically receive the maintenance signal, at the synapse, to maintain a specific gain of the synapse; and program code to periodically receive fewer maintenance signals, at the synapse, to decrease the specific gain of the synapse. 20. The non-transitory computer-readable medium of claim 16, in which a gain of the postsynaptic transmission comprises information corresponding to the state information.