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- Bayesian estimation (1)
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During reading, saccadic landing positions within words show a pronounced peak close to the word center, with an additional systematic error that is modulated by the distance from the launch site and the length of the target word. Here we show that the systematic variation of fixation positions within words, the saccadic range error, can be derived from Bayesian decision theory. We present the first mathematical model for the saccadic range error; this model makes explicit assumptions regarding underlying visual and oculomotor processes. Analyzing a corpus of eye movement recordings, we obtained results that are consistent with the view that readers use Bayesian estimation for saccade planning. Furthermore, we show that alternative models fail to reproduce the experimental data.
It is generally accepted that low-level features (e.g., inter-word spaces) are responsible for saccade-target selection in eye-movement control during reading. In two experiments using Uighur script known for its rich suffixes, we demonstrate that, in addition to word length and launch site, the number of suffixes influences initial landing positions. We also demonstrate an influence of word frequency. These results are difficult to explain purely by low-level guidance of eye movements and indicate that due to properties specific to Uighur script low-level visual information and high-level information such as morphological structure of parafoveal words jointly influence saccade programming. (C) 2014 Elsevier B.V. All rights reserved.