OB1-reader: A model of word recognition and eye movements in text reading

Decades of reading research have led to sophisticated accounts of single-word recognition and, in parallel, accounts of eye-movement control in text reading. Although these two endeavors have strongly advanced the field, their relative independence has precluded an integrated account of the reading process. To bridge the gap, we here present a computational model of reading, OB1-reader, which integrates insights from both literatures. Key features of OB1 are as follows: (1) parallel processing of multiple words, modulated by an attentional window of adaptable size; (2) coding of input through a layer of open bigram nodes that represent pairs of letters and their relative position; (3) activation of word representations based on constituent bigram activity, competition with other word representations and contextual predictability; (4) mapping of activated words onto a spatiotopic sentence-level representation to keep track of word order; and (5) saccade planning, with the saccade goal being dependent on the length and activation of surrounding word units, and the saccade onset being influenced by word recognition. A comparison of simulation results with experimental data shows that the model provides a fruitful and parsimonious theoretical framework for understanding reading behavior.