Theoretical analysis of interhemispheric transfer costs in visual word recognition

Abstract

It is becoming increasingly clear that interhemispheric transfer is an important factor in visual word recognition. One of the two computational models of visual word recognition that includes this aspect, the SERIOL model, is tested on the basis of recently obtained behavioural word naming data. Optimal viewing position (OVP) data were collected from participants with left hemisphere language dominance, right hemisphere language dominance, and bilateral language representation (as determined by fMRI). We employ a mathematical model, which is based on some of the underlying assumptions of SERIOL, to investigate the model's ability to predict our results. We show that this mathematical model, which makes use of the original parameters, is able to perfectly predict the differences in the OVP curves observed in the three groups of participants.

Acknowledgements

We would like to thank Carol Whitney and Colin Davis for comments on an earlier draft of this article and for providing us with the basic framework for our calculations.

Notes

¹The authors would like to thank Colin Davis for suggesting this approach (see Stevens & Grainger (2003) for empirical support regarding the mechanisms of the perception cost model).