A neural network theory of preference reversal is presented. This theory includes a model of why New Coke was preferred to Old Coke on taste tests but was unpopular in the market. The model uses competing drive lod representing "excitement" and "security." Context influences which drive wins the competition, hence, which stimulus attributes are attended to. Our network's design, outlined m stages, is based on Grossberg's gated dipole theory. Three sets of dipoles, representing attributes, categories, and drives, are connected by modifiable associative synapses. The network also includes competition among categories and enhancement oi attention by mismatch of expectation.