Spike time windowing for implementing spike-timing dependent plasticity (stdp)
AssigneeQUALCOMM Incorporated
InventorsDavid Jonathan JULIAN, Jeffrey Alexander LEVIN, Kristopher PETERSON, Ravindra Manohar PATWARDHAN
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Abstract
Methods and apparatus are provided for implementing spike-timing dependent plasticity (STDP) using windowing of spikes. One example method for operating an artificial nervous system generally includes recording spike times for a first artificial neuron, recording spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, processing spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron, and updating a parameter (e.g., a weight or a delay) of the synapse based on the processing.
Claims55
A method for operating an artificial nervous system, comprising:
- recording spike times for a first artificial neuron;
- recording spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein recording the spike times for the second artificial neuron comprises keeping the spike times for the second artificial neuron that occur within an amount of time;
- processing spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- updating a parameter of the synapse based on the processing.
A method for operating an artificial nervous system, comprising:
- recording spike times for a first artificial neuron;
- recording spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein recording the spike times for the second artificial neuron comprises keeping up to a predetermined number of the spike times for the second artificial neuron
- processing spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- updating a parameter of the synapse based on the processing.
An apparatus for operating an artificial nervous system, comprising:
- a processing system configured to:
- record spike times for a first artificial neuron;
- record spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein recording the spike times for the second artificial neuron comprises keeping the spike times for the second artificial neuron that occur within an amount of time;
- process spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- update a parameter of the synapse based on the processing;
- and
- a memory coupled to the processing system.
An apparatus for operating an artificial nervous system, comprising:
- a processing system configured to:
- record spike times for a first artificial neuron;
- record spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein recording the spike times for the second artificial neuron comprises keeping up to a predetermined number of the spike times for the second artificial neuron;
- process spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- update a parameter of the synapse based on the processing;
- and
- a memory coupled to the processing system.
An apparatus for operating an artificial nervous system, comprising:
- means for recording spike times for a first artificial neuron;
- means for recording spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein the means for recording the spike times for the second artificial neuron is configured to keep the spike times for the second artificial neuron that occur within an amount of time;
- means for processing spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- means for updating a parameter of the synapse based on the processing.
An apparatus for operating an artificial nervous system, comprising:
- means for recording spike times for a first artificial neuron;
- means for recording spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein the means for recording the spike times for the second artificial neuron is configured to keep up to a predetermined number of the spike times for the second artificial neuron;
- means for processing spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- means for updating a parameter of the synapse based on the processing.
A computer program product for operating an artificial nervous system, comprising a computer-readable medium having instructions executable to:
- record spike times for a first artificial neuron;
- record spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein recording the spike times for the second artificial neuron comprises keeping the spike times for the second artificial neuron that occur within an amount of time;
- process spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- update a parameter of the synapse based on the processing.
A computer program product for operating an artificial nervous system, comprising a computer-readable medium having instructions executable to:
- record spike times for a first artificial neuron;
- record spike times for a second artificial neuron coupled to the first artificial neuron via a synapse, wherein recording the spike times for the second artificial neuron comprises keeping up to a predetermined number of the spike times for the second artificial neuron;
- process spikes for the second artificial neuron according to a window based at least in part on the spike times for the first artificial neuron;
- and
- update a parameter of the synapse based on the processing.
Dependencies are inferred from the claim text.