Most simple and complex cells in the cat striate cortex are both orientation and direction selective. In this article we use single-cell learning rules to develop both orientation and direction selectivity in a natural scene environment. We show that a simple principal component analysis rule is inadequate for developing direction selectivity, but that the BCM rule as well as similar higher-order rules can. We also demonstrate that the convergence of lagged and nonlagged cells depends on the velocity of motion in the environment, and that strobe rearing disrupts this convergence, resulting in a loss of direction selectivity.

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