Post synaptic potential-based learning rule

A method comprising:

• identifying a spike sent from a first artificial neuron in a spiking neural network (SNN) to a second artificial neuron in the SNN, wherein the SNN is implemented using a neuromorphic computing device, and the spike is sent over a particular artificial synapse connecting the first artificial neuron to the second artificial neuron in the SNN;
• comparing the membrane potential of the second artificial neuron at a particular time step, corresponding to sending of the spike, to a threshold potential, wherein the threshold potential is set lower than a firing potential of the second artificial neuron;
• and
• determining a change to synaptic weight of the particular artificial synapse based on the spike, wherein the synaptic weight is to be decreased if the membrane potential of the second artificial neuron is lower than the threshold potential at the particular time step and the synaptic weight is to be increased if the membrane potential of the second artificial neuron is higher than the threshold potential at the particular time step.

An apparatus comprising:

• a neuromorphic computing device to implement an artificial spiking neural network (SNN), wherein the neuromorphic computing device comprises:
• at least one neuromorphic core comprising:
• an interface to receive at least one input;
• and
• a learning core to:
• identify a spike sent from a first artificial neuron in the SNN to a second artificial neuron in the SNN over a particular artificial synapse connecting the first artificial neuron to the second artificial neuron in the SNN, wherein the spike corresponds to the input;
• compare the membrane potential of the second artificial neuron at a particular time step corresponding to the spike to a threshold potential, wherein the threshold potential is set lower than a firing potential of the second artificial neuron;
• and
• determine a change to synaptic weight of the particular artificial synapse based on the spike, wherein a first change to the synaptic weight is to be made if the membrane potential of the second artificial neuron is lower than the threshold potential at the particular time step and a second, different change to the synaptic weight is to be made if the membrane potential of the second artificial neuron is higher than the threshold potential at the particular time step.