Sequence learning with hidden units in spiking neural networks

NeurIPS 2011 Johanni BreaWalter SennJean-Pascal Pfister

We consider a statistical framework in which recurrent networks of spiking neurons learn to generate spatio-temporal spike patterns. Given biologically realistic stochastic neuronal dynamics we derive a tractable learning rule for the synaptic weights towards hidden and visible neurons that leads to optimal recall of the training sequences... (read more)

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