According to several computational models, novel items can create a learning mode with dynamics favorable to new learning, and not to memory retrieval. In line with that idea, a new item in a recognition test has been found to create a bias toward calling subsequent items new as well. Here, we tested whether this bias, which we termed the afterglow effect, is indeed caused by a general learning mode, or is caused by perceptual overlap between preceding and current items. In two experiments, we show that a preceding recognition judgment biases the current one, but only if the preceding and current items are of the same perceptual category. In contrast, we did not find strong bias effects from perceptually novel fractal images, as would be predicted if novel items induce a learning mode that then biases recognition judgments. We conclude that the afterglow effect is more likely to reflect perceptual phenomena than a learning mode. We suggest how this can be reconciled with what is known about familiarity at the neural level.