Part of Advances in Neural Information Processing Systems 5 (NIPS 1992)
Daphne Bavelier, Michael Jordan
We describe a model of visual word recognition that accounts for several aspects of the temporal processing of sequences of briefly presented words. The model utilizes a new representation for writ(cid:173) ten words, based on dynamic time warping and multidimensional scaling. The visual input passes through cascaded perceptual, com(cid:173) parison, and detection stages. We describe how these dynamical processes can account for several aspects of word recognition, in(cid:173) cluding repetition priming and repetition blindness.