According to Bowers, the finding that there are neurons with highly selective responses to familiar stimuli supports theories positing localist representations over approaches positing the type of distributed representations typically found in parallel distributed processing (PDP) models. However, his conclusions derive from an overly narrow view of the range of possible distributed representations and of the role that PDP models can play in exploring their properties. Although it is true that current distributed theories face challenges in accounting for both neural and behavioral data, the proposed localist account--to the extent that it is articulated at all--runs into more fundamental difficulties. Central to these difficulties is the problem of specifying the set of entities a localist unit represents. (Contains 3 footnotes.)