An anatomical perspective on sublexical units: The influence of the split fovea

We discuss the problem of how to represent the internal structure of English words, and consider the solutions adopted in a number of implemented models of visual word recognition and naming. We describe two sets of simulations with the split-fovea model, an implemented connectionist cognitive model of single-word reading, whose architecture is based on the precise vertical splitting of the human fovea. We show that the model can capture critical human data from two effects concerned with the parallel activation of lexical competitors: (a) the transposed letters effect, in which pairs of words like salt and slat, or clam and calm, interact during processing, and (b) the neighbourhood effect, in which large lexical neighbourhoods facilitate naming. We discuss the results in terms of the coarse coding generated by the architecture of the split-fovea model and the naming task. Finally, we consider some of the implications for the processing of different languages and different orthographies, and for language impairment.