the wse has proven to be an important finding for word recognition models, and specifically is supported by rumelhart and mcclelland's interactive-activation model of word recognition. according to this model, when a reader is presented with a word, each letter in parallel will either stimulate or inhibit different feature detectors (e.g. a curved shape for "c", horizontal and vertical bars for "h", etc.). those feature detectors will then stimulate or inhibit different letter detectors, which will finally stimulate or inhibit different word detectors. each activated connection would carry a different weight, and thus the word "work" in the example would be activated more than any other word (and therefore recognized by a reader).