Methods and apparatus are provided for inferring and accounting for missing post-synaptic events (e.g., a post-synaptic spike that is not associated with any pre-synaptic spikes) at an artificial neuron and adjusting spike-timing dependent plasticity (STDP) accordingly. One example method generally includes receiving, at an artificial neuron, a plurality of pre-synaptic spikes associated with a synapse, tracking a plurality of post-synaptic spikes output by the artificial neuron, and determining at least one of the post-synaptic spikes is associated with none of the plurality of pre-synaptic spikes. According to certain aspects, determining inferring missing post-synaptic events may be accomplished by using a flag, counter, or other variable that is updated on post-synaptic firings. If this post-ghost variable changes between pre-synaptic-triggered adjustments, then the artificial nervous system can determine there was a missing post-synaptic pairing.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for artificial nervous system operations, comprising: receiving, at an artificial neuron, a plurality of pre-synaptic spikes associated with a synapse; tracking a plurality of post-synaptic spikes output by the artificial neuron; and determining at least one of the post-synaptic spikes is associated with none of the pre-synaptic spikes. 2. The method of claim 1, wherein the determining comprises: updating a first variable each time the artificial neuron outputs one of the post-synaptic spikes; and updating a second variable each time the artificial neuron receives one of the pre-synaptic spikes. 3. The method of claim 2, wherein receiving the plurality of pre-synaptic spikes comprises: receiving a first pre-synaptic spike associated with the synapse; and receiving a second pre-synaptic spike associated with the synapse after reception of the first pre-synaptic spike. 4. The method of claim 3, wherein tracking the plurality of post-synaptic spikes comprises: determining a first number of the post-synaptic spikes in a first window associated with the first pre-synaptic spike; and determining a second number of the post-synaptic spikes in a second window associated with the second pre-synaptic spike. 5. The method of claim 4, wherein determining the association of the at least one of the post-synaptic spikes further comprises calculating a number of non-associated post-synaptic spikes between the first window and the second window based at least in part on the first variable corresponding to a last post-synaptic spike in the second window, on the second variable corresponding to the first window, and on the second number of the post-synaptic spikes in the second window. 6. The method of claim 5, further comprising adjusting a weight of the synapse based at least in part on the number of non-associated post-synaptic spikes. 7. The method of claim 6, wherein the adjusting comprises adjusting the weight of the synapse by a product of the number of non-associated post-synaptic spikes and an amount comprising one of: a sum of a first asymptotic value associated with a long-term potentiation (LTP) portion of a spike-timing-dependent plasticity (STDP) curve added to a second asymptotic value associated with a long-term depression (LTD) portion of the STDP curve; a difference between the first asymptotic value and the second asymptotic value; a difference between the second asymptotic value and the first asymptotic value; a larger magnitude between the first asymptotic value and the second asymptotic value; a smaller magnitude between the first asymptotic value and the second asymptotic value; an average of the first asymptotic value and the second asymptotic value; or a predetermined value. 8. The method of claim 2, wherein the first variable comprises at least one of a counter, a modulo counter, a flag, a random variable, a pseudo-random variable, or a time-dependent variable. 9. The method of claim 2, wherein the second variable is based at least in part on a prior value of the first variable. 10. The method of claim 2, wherein the second variable is at least one of read or written with a weight of the synapse. 11. The method of claim 1, further comprising adjusting a weight of the synapse based at least in part on the at least one of the post-synaptic spikes. 12. An apparatus for artificial nervous system operations, comprising: a processing system configured to: receive, at an artificial neuron, a plurality of pre-synaptic spikes associated with a synapse; track a plurality of post-synaptic spikes output by the artificial neuron; and determine at least one of the post-synaptic spikes is associated with none of the pre-synaptic spikes; and a memory coupled to the processing system. 13. The apparatus of claim 12, wherein the processing system is configured to determine the association of the at least one of the post-synaptic spikes by: updating a first variable each time the artificial neuron outputs one of the post-synaptic spikes; and updating a second variable each time the artificial neuron receives one of the pre-synaptic spikes. 14. The apparatus of claim 13, wherein the processing system is configured to receive the plurality of pre-synaptic spikes by: receiving a first pre-synaptic spike associated with the synapse; and receiving a second pre-synaptic spike associated with the synapse after reception of the first pre-synaptic spike. 15. The apparatus of claim 14, wherein the processing system is configured to track the plurality of post-synaptic spikes by: determining a first number of the post-synaptic spikes in a first window associated with the first pre-synaptic spike; and determining a second number of the post-synaptic spikes in a second window associated with the second pre-synaptic spike. 16. The apparatus of claim 15, wherein the processing system is further configured to determine the association of the at least one of the post-synaptic spikes by calculating a number of non-associated post-synaptic spikes between the first window and the second window based at least in part on the first variable corresponding to a last post-synaptic spike in the second window, on the second variable corresponding to the first window, and on the second number of the post-synaptic spikes in the second window. 17. The apparatus of claim 16, wherein the processing system is further configured to adjust a weight of the synapse based at least in part on the number of non-associated post-synaptic spikes. 18. The apparatus of claim 17, wherein the processing system is configured to adjust the weight of the synapse by a product of the number of non-associated post-synaptic spikes and an amount comprising one of: a sum of a first asymptotic value associated with a long-term potentiation (LTP) portion of a spike-timing-dependent plasticity (STDP) curve added to a second asymptotic value associated with a long-term depression (LTD) portion of the STDP curve; a difference between the first asymptotic value and the second asymptotic value; a difference between the second asymptotic value and the first asymptotic value; a larger magnitude between the first asymptotic value and the second asymptotic value; a smaller magnitude between the first asymptotic value and the second asymptotic value; an average of the first asymptotic value and the second asymptotic value; or a predetermined value. 19. The apparatus of claim 13, wherein the first variable comprises at least one of a counter, a modulo counter, a flag, a random variable, a pseudo-random variable, or a time-dependent variable. 20. The apparatus of claim 13, wherein the second variable is based at least in part on a prior value of the first variable. 21. The apparatus of claim 13, wherein the second variable is at least one of read or written with a weight of the synapse. 22. The apparatus of claim 12, wherein the processing system is further configured to adjust a weight of the synapse based at least in part on the at least one of the post-synaptic spikes. 23. An apparatus for artificial nervous system operations, comprising: means for receiving, at an artificial neuron, a plurality of pre-synaptic spikes associated with a synapse; means for tracking a plurality of post-synaptic spikes output by the artificial neuron; and means for determining at least one of the post-synaptic spikes is not associated with any of the pre-synaptic spikes. 24. A computer program product for artificial nervous system operations, comprising a non-transitory computer-readable medium having instructions executable to: receive, at an artificial neuron, a plurality of pre-synaptic spikes associated with a synapse; track a plurality of post-synaptic spikes output by the artificial neuron; and determine at least one of the post-synaptic spikes is not associated with any of the pre-synaptic spikes.