One focus so far has largely been on data-driven, or bottum up, processing. That is, we have discussed how the incoming information triggers a respons by feature detectors, which in turn triggers a response by letter detectors. But object recognition also involves, concept-driven, or topdown, processing - processing that is driven by a broad pattern of knowledge and expectations, including knowledge that cannot easily be understood as an echo of frequent or recent experiences. Most contemporary models of object recognition involve both top-down and bottom-up components and so are said to be interactive models.
Concept driven priming relies on knowledge that is seperate from one's knowledge about letters, word and letter combinations. The evidence is telling us that we cannot view object recognition as a self-contained process. Knowledge that is external to object recognition is imported into and clearly influences the proces. This sort of priming depends on what is in memory and on how that knowledge is accessed and used.