Embodiments of the invention relate to a time-division multiplexed neurosynaptic module with implicit memory addressing for implementing a neural network. One embodiment comprises maintaining neuron attributes for multiple neurons and maintaining incoming firing events for different time steps. For each time step, incoming firing events for said time step are integrated in a time-division multiplexing manner. Incoming firing events are integrated based on the neuron attributes maintained. For each time step, the neuron attributes maintained are updated in parallel based on the integrated incoming firing events for said time step.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, comprising: maintaining multiple synaptic weights for multiple neurons in a transposable memory array, wherein each synaptic weight of the multiple synaptic weights corresponds to a neuron of the multiple neurons; for at least one synaptic weight of the multiple synaptic weights, updating the synaptic weight based on at least one of a learning rule and neuronal firing activity of a corresponding neuron; and controlling transposable access to the memory array for enhanced learning operation. 2. The method of claim 1, wherein one or more synaptic weights of the multiple synaptic weights is readable from, and writable to, the memory array, in two different directions. 3. The method of claim 2, wherein the two different directions comprise a horizontal direction and a vertical direction. 4. The method of claim 1, further comprising: for at least one neuron of the multiple neurons, selectively integrating one or more incoming firing events targeting the neuron into a membrane potential variable of the neuron based on one or more synaptic weights corresponding to the neuron. 5. The method of claim 4, further comprising: for at least one neuron of the multiple neurons, generating an outgoing firing event when a membrane potential variable of the neuron exceeds a threshold parameter of the neuron. 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 multiple synaptic weights for multiple neurons in a transposable memory array, wherein each synaptic weight of the multiple synaptic weights corresponds to a neuron of the multiple neurons; for at least one synaptic weight of the multiple synaptic weights, updating the synaptic weight based on at least one of a learning rule and neuronal firing activity of a corresponding neuron; and controlling transposable access to the memory array for enhanced learning operation. 7. The system of claim 6, wherein one or more synaptic weights of the multiple synaptic weights is readable from, and writable to, the memory array, in two different directions. 8. The system of claim 7, wherein the two different directions comprise a horizontal direction and a vertical direction. 9. The system of claim 6, the method further comprising: for at least one neuron of the multiple neurons, selectively integrating one or more incoming firing events targeting the neuron into a membrane potential variable of the neuron based on one or more synaptic weights corresponding to the neuron. 10. The system of claim 9, the method further comprising: for at least one neuron of the multiple neurons, generating an outgoing firing event when a membrane potential variable of the neuron exceeds a threshold parameter of the neuron. 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 multiple synaptic weights for multiple neurons in a transposable memory array, wherein each synaptic weight of the multiple synaptic weights corresponds to a neuron of the multiple neurons; for at least one synaptic weight of the multiple synaptic weights, updating the synaptic weight based on at least one of a learning rule and neuronal firing activity of a corresponding neuron; and controlling transposable access to the memory array for enhanced learning operation. 12. The computer program product of claim 11, wherein one or more synaptic weights of the multiple synaptic weights is readable from, and writable to, the memory array, in two different directions. 13. The computer program product of claim 12, wherein the two different directions comprise a horizontal direction and a vertical direction. 14. The computer program product of claim 11, the method further comprising: for at least one neuron of the multiple neurons, selectively integrating one or more incoming firing events targeting the neuron into a membrane potential variable of the neuron based on one or more synaptic weights corresponding to the neuron. 15. The computer program product of claim 14, the method further comprising: for at least one neuron of the multiple neurons, generating an outgoing firing event when a membrane potential variable of the neuron exceeds a threshold parameter of the neuron.