Certain aspects of the present disclosure support assigning neurons and/or synapses to group tags where group tags have an associated set of parameters. By using group tags, neurons or synapses in a population can be assigned a group tag. Then, by changing a parameter associated with the group tag, all synapses or neurons in the group may have that parameter changed.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for operating an artificial nervous system, comprising: assigning at least one of a first population of synapses or a first population of artificial neurons of the artificial nervous system to a first group tag, wherein the first group tag is associated with a first set of parameters and at least one of a first synapse type or a first neuron type; assigning at least one of a second population of synapses or a second population of artificial neurons of the artificial nervous system to a second group tag, wherein the second group tag is associated with a second set of parameters and at least one of a second synapse type or a second neuron type; and changing one or more parameters in at least one of the first set of parameters or the second set of parameters causing changing the one or more parameters for at least one of: one or more synapses in at least one of the first population or the second population, or one or more artificial neurons in at least one of the first population or the second population. 2. The method of claim 1, further comprising tagging at least one of: one or more of the artificial neurons or one or more of the synapses with both the first and second group tags. 3. The method of claim 1, further comprising: changing parameters associated with the first and second synapse types causing changing these parameters for all synapses in the first and second populations; and changing other parameters associated with the first and second neuron types causing changing these other parameters for all artificial neurons in the first and second populations. 4. The method of claim 1, wherein the first and second sets of parameters comprise at least one of a flag to enable plasticity, a flag to disable plasticity, a flag for post-synaptic potential (PSP) transfer, a flag for dopamine, a homeostasis enable flag, a homeostasis disable flag, a plasticity enable flag or a plasticity disable flag. 5. The method of claim 4, further comprising: controlling simultaneously the flag to enable plasticity, the flag to disable plasticity, the flag for post-synaptic potential (PSP) transfer, and the flag for dopamine. 6. The method of claim 1, wherein parameters associated with the first and second synapse types comprise at least one of a spike-timing-dependent plasticity (STDP) table, a resource model, or plasticity parameters. 7. The method of claim 1, further comprising: controlling simultaneously parameters in the first and second sets. 8. The method of claim 1, wherein: the first synapse type is same as the second synapse type, and the first neuron type is same as the second neuron type, and the method further comprising changing parameters in the first and second sets at different time instants, and a value of a parameter in the first set differs from a value of that parameter in the second set. 9. The method of claim 1, wherein: the first and second populations of synapses are subsets of a set of synapses of at least one of same layer or same type, and the first and second populations of artificial neurons are subsets of a set of artificial neurons of at least one of same layer or same type. 10. The method of claim 1, wherein parameters in the first and second sets are disjoint from parameters associated with the first and second synapse types. 11. The method of claim 1, wherein at least one parameter in the first and second sets is common with at least one parameter associated with the first and second synapse types, and the method further comprising overriding, based on the at least one parameter in the first and second sets, the at least one parameter associated with the first and second synapse types. 12. The method of 1, wherein at least one of the first group tag or the second group tag is assigned dynamically. 13. The method of claim 12, wherein dynamically assigning the at least one of first group tag or second group tag is associated with synapses of at least one of the first population of synapses or the second population of synapses with weights below a threshold. 14. The method of claim 12, wherein dynamically assigning the at least one of first group tag or second group tag further comprises: flagging underutilized synapses of at least one of the first or second populations of synapses and underutilized artificial neurons of at least one of the first or second populations of artificial neurons for at least one of reallocation or structural plasticity. 15. The method of claim 1, wherein changing the one or more parameters comprises enabling and disabling plasticity, and the method further comprising: enabling plasticity based on a certain artificial neuron of the first population of artificial neurons or of the second population of artificial neurons spiking; and disabling plasticity based on a different certain artificial neuron of the first population of artificial neurons or of the second population of artificial neurons spiking. 16. The method of claim 1, wherein changing the one or more parameters comprises enabling and disabling plasticity, and the method further comprising: enabling plasticity based on a set of artificial neurons of at least one of the first population of artificial neurons or the second population of artificial neurons spiking. 17. The method of claim 1, wherein changing the one or more parameters comprises enabling and disabling plasticity, and the method further comprising: enabling plasticity based on a set of artificial neurons of at least one of the first population of artificial neurons or the second population of artificial neurons having a defined activity rate. 18. The method of claim 1, wherein changing the one or more parameters comprises enabling and disabling plasticity, and the method further comprising: enabling plasticity based on a function of synaptic weights associated with at least one of the first population of synapses or the second population of synapses reaching a metric. 19. An apparatus for operating an artificial nervous system, comprising: a processing system configured to: assign at least one of a first population of synapses or a first population of artificial neurons of the artificial nervous system to a first group tag, wherein the first group tag is associated with a first set of parameters and at least one of a first synapse type or a first neuron type; assign at least one of a second population of synapses or a second population of artificial neurons of the artificial nervous system to a second group tag, wherein the second group tag is associated with a second set of parameters and at least one of a second synapse type or a second neuron type; and change one or more parameters in at least one of the first set of parameters or the second set of parameters causing changing the one or more parameters for at least one of: one or more synapses in at least one of the first population or the second population, or one or more artificial neurons in at least one of the first population or the second population; and a memory coupled to the processing system. 20. An apparatus for operating an artificial nervous system, comprising: means for assigning at least one of a first population of synapses or a first population of artificial neurons of the artificial nervous system to a first group tag, wherein the first group tag is associated with a first set of parameters and at least one of a first synapse type or a first neuron type; means for assigning at least one of a second population of synapses or a second population of artificial neurons of the artificial nervous system to a second group tag, wherein the second group tag is associated with a second set of parameters and at least one of a second synapse type or a second neuron type; and means for changing one or more parameters in at least one of the first set of parameters or the second set of parameters causing changing the one or more parameters for at least one of: one means for or more synapses in at least one of the first population or the second population, or one or more artificial neurons in at least one of the first population or the second population. 21. A computer program product for operating an artificial nervous system, comprising a computer-readable medium having instructions executable to: assign at least one of a first population of synapses or a first population of artificial neurons of the artificial nervous system to a first group tag, wherein the first group tag is associated with a first set of parameters and at least one of a first synapse type or a first neuron type; assign at least one of a second population of synapses or a second population of artificial neurons of the artificial nervous system to a second group tag, wherein the second group tag is associated with a second set of parameters and at least one of a second synapse type or a second neuron type; and change one or more parameters in at least one of the first set of parameters or the second set of parameters causing changing the one or more parameters for at least one of: one or more synapses in at least one of the first population or the second population, or one or more artificial neurons in at least one of the first population or the second population. 22. A method for operating an artificial nervous system, comprising: assigning a group of artificial neurons and synapses of the artificial nervous system to a group tag with an associated set of parameters; and sending a single message changing values of the parameters in the set causing simultaneous switch of the parameters for all artificial neurons and synapses in the group. 23. The method of claim 22, wherein the parameters in the set comprise parameters applying only to artificial neurons in the group, parameters applying only to synapses in the group, and parameters applying to both artificial neurons and synapses in the group. 24. The method of claim 23, wherein the parameters applying only to artificial neurons in the group comprise a homeostasis enable flag and a homeostasis disable flag. 25. The method of claim 23, wherein the parameters applying only to synapses in the group comprise a post-synaptic potential (PSP) transfer enable flag and a PSP transfer disable flag. 26. The method of claim 23, wherein the parameters applying to both artificial neurons and synapses in the group comprise a plasticity enable flag and a plasticity disable flag. 27. An apparatus for operating an artificial nervous system, comprising: a processing system configured to: assign a group of artificial neurons and synapses of the artificial nervous system to a group tag with an associated set of parameters; and send a single message changing values of the parameters in the set causing simultaneous switch of the parameters for all artificial neurons and synapses in the group; and a memory coupled to the processing system. 28. An apparatus for operating an artificial nervous system, comprising: means for assigning a group of artificial neurons and synapses of the artificial nervous system to a group tag with an associated set of parameters; and means for sending a single message changing values of the parameters in the set causing simultaneous switch of the parameters for all artificial neurons and synapses in the group. 29. A computer program product for operating an artificial nervous system, comprising a computer-readable medium having instructions executable to: assign a group of artificial neurons and synapses of the artificial nervous system to a group tag with an associated set of parameters; and send a single message changing values of the parameters in the set causing simultaneous switch of the parameters for all artificial neurons and synapses in the group.