Before revision:  Here, we propose a model where a spiking recurrent network  drives a read-out layer . Plastic synapses follow common Hebbian learning rules. The dynamics of the  recurrent network is constrained to encode time while the read-out neurons encode space.
After revision:  Here, we propose a model where a spiking recurrent network drives a read-out layer : the dynamics of the recurrent network is constrained to encode time while the read-out neurons encode space.