Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning
Neural Computation
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Applying bounded weight-independent temporal plasticity rule to synapses from independent Poisson firing presynaptic neurons onto a conductance-based integrate-and-fire neuron leads to a bimodal distribution of synaptic strength (Song et al., 2000). We extend this model to investigate the effects of spreading the synapses over the dendritic tree. The results suggest that distal synapses tend to lose out to proximal ones in the competition for synaptic strength. Against expectations, versions of the plasticity rule with a smoother transition between potentiation and depression make little difference to the distribution or lead to all synapses losing.