Page's target article makes a good case for the strength of localist models. This can be characterized as an issue of where new information is integrated with respect to existing knowledge structures. We extend the analysis by discussing the dimension of when this integration takes place, the implications, and how they guide us in the creation of cognitive models.

Shepard has challenged psychologists to identify nonarbitrary principles of mind upon which to build a more explanatory and general cognitive science. I suggest that such nonarbitrary principles may fruitfully be sought not only in the laws of physics and mathematics, but also in the logical entailments of different categories of representation. In the example offered here, conceptualizing mental events as indexical with respect to the events they represent enables one to account parsimoniously for a wide range of empirical psychological phenomena. (...) [Shepard]. (shrink)

We propose a way in which Barsalou could strengthen his position and at the same time make a considerable dent in the category/abstraction problem (that he suggests remains unsolved). There exists a class of connectionist models that solves this problem parsimoniously and provides a mechanistic underpinning for the promising high-level architecture he proposes.

Although Glenberg 's theory benefits from the incorporation of a suppression concept, a more differentiated view of suppression would be even more effective. We propose such a concept, showing how it accounts for phenomena that Glenberg describes and also for phenomena that he ignores.