  We propose a solution to the weight transport problem, which questions the
biological plausibility of the backpropagation algorithm. We derive our method
based upon a theoretical analysis of the (approximate) dynamics of leaky
integrate-and-fire neurons. We show that the use of spike timing alone
outcompetes existing biologically plausible methods for synaptic weight
inference in spiking neural network models. Furthermore, our proposed method is
more flexible, being applicable to any spiking neuron model, is conservative in
how many parameters are required for implementation and can be deployed in an
online-fashion with minimal computational overhead. These features, together
with its biological plausibility, make it an attractive mechanism underlying
weight inference at single synapses.
