Neocortical circuits are dominated by massive excitatory feedback: more than eighty percent of the synapses made by excitatory cortical neurons are onto other excitatory cortical neurons. Why is there such massive re(cid:173) current excitation in the neocortex and what is its role in cortical compu(cid:173) tation? Recent neurophysiological experiments have shown that the plas(cid:173) ticity of recurrent neocortical synapses is governed by a temporally asym(cid:173) metric Hebbian learning rule. We describe how such a rule may allow the cortex to modify recurrent synapses for prediction of input sequences. The goal is to predict the next cortical input from the recent past based on previous experience of similar input sequences.