 We use a general probabilistic framework that relies on the principle of maximizing the likelihood for the network to reproduce some temporal dynamics.
<meaning-changed>  We use a general probabilistic framework that relies on the principle of maximizing the likelihood for the network to reproduce some temporal dynamics.
 In this paper, we derive a learning rule, local to the synapse, from a simple mathematical principle, the maximization of the likelihood for the network to reproduce some temporal dynamics.