Embodiments of the invention relate to a time-division multiplexed neurosynaptic module with implicit memory addressing for implementing a universal substrate of adaptation. One embodiment comprises a neurosynaptic device including a memory device that maintains neuron attributes for multiple neurons. The module further includes multiple bit maps that maintain incoming firing events for different periods of delay and a multi-way processor. The processor includes a memory array that maintains a plurality of synaptic weights. The processor integrates incoming firing events in a time-division multiplexing manner. Incoming firing events are integrated based on the neuron attributes and the synaptic weights maintained.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, comprising: maintaining neuron information for multiple neurons of a neural network; maintaining incoming firing events for different periods of delay; and based on the neuron information, integrating incoming firing events in a time-division multiplexing manner using multiple processors of the neural network; wherein the total number of neurons in the neural network is based on the number of processors in the neural network and the number of times each processor is time-multiplexed. 2. The method of claim 1, wherein: for each neuron, the neuron information includes a membrane potential variable of the neuron and a threshold parameter for the neuron. 3. The method of claim 2, further comprising: for each neuron, generating an outgoing firing event in response to a membrane potential variable of the neuron exceeding a threshold parameter for the neuron. 4. The method of claim 1, further comprising: updating the neuron information based on the integrated incoming firing events. 5. The method of claim 1, further comprising: maintaining routing information for the multiple neurons. 6. A system comprising a computer processor, a computer-readable hardware storage medium, and program code embodied with the computer-readable hardware storage medium for execution by the computer processor to implement a method comprising: maintaining neuron information for multiple neurons of a neural network; maintaining incoming firing events for different periods of delay; and based on the neuron information, integrating incoming firing events in a time-division multiplexing manner using multiple processors of the neural network; wherein the total number of neurons in the neural network is based on the number of processors in the neural network and the number of times each processor is time-multiplexed. 7. The system of claim 6, wherein: for each neuron, the neuron information includes a membrane potential variable of the neuron and a threshold parameter for the neuron. 8. The system of claim 7, the method further comprising: for each neuron, generating an outgoing firing event in response to a membrane potential variable of the neuron exceeding a threshold parameter for the neuron. 9. The system of claim 6, the method further comprising: updating the neuron information based on the integrated incoming firing events. 10. The system of claim 6, the method further comprising: maintaining routing information for the multiple neurons. 11. A computer program product comprising a computer-readable hardware storage medium having program code embodied therewith, the program code being executable by a computer to implement a method comprising: maintaining neuron information for multiple neurons of a neural network; maintaining incoming firing events for different periods of delay; and based on the neuron information, integrating incoming firing events in a time-division multiplexing manner using multiple processors of the neural network; wherein the total number of neurons in the neural network is based on the number of processors in the neural network and the number of times each processor is time-multiplexed. 12. The computer program product of claim 11, wherein: for each neuron, the neuron information includes a membrane potential variable of the neuron and a threshold parameter for the neuron. 13. The computer program product of claim 12, the method further comprising: for each neuron, generating an outgoing firing event in response to a membrane potential variable of the neuron exceeding a threshold parameter for the neuron. 14. The computer program product of claim 11, the method further comprising: updating the neuron information based on the integrated incoming firing events. 15. The computer program product of claim 11, the method further comprising: maintaining routing information for the multiple neurons.