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

Overcoming the Weight Transport Problem via Spike-Timing-Dependent Weight Inference