Predictive learning of temporal sequences in recurrent neocortical circuits

Rajesh P. N. Rao and Terrence J. Sejnowski
The Salk Institute

(2001 Complexity in biological information processing. Wiley, Chichester (Novartis Foundation Symposium 239), in press, 2001)

When a spike is initiated near the soma of a cortical pyramidal neuron, it may back-propagate up dendrites toward distal synapses, where strong depolarization can trigger spike-timing dependent Hebbian plasticity at recently activated synapses. We show that (a) these mechanisms can implement a temporal-difference algorithm for sequence learning, and (b) a population of recurrently connected neurons with this form of synaptic plasticity can learn to predict spatiotemporal input patterns. Using biophysical simulations, we demonstrate that a network of cortical neurons can develop direction selectivity similar to that observed in complex cells in alert monkey visual cortex as a consequence of learning to predict moving stimuli.