Bottom Up And Top Down Processes In Reading

In reading, word frequency is commonly regarded as the major bottom-up determinant for the speed of lexical access. Moreover, language processing depends on top-down information, such as the predictability of a word from a previous context. Yet, however, the exact role of top-down predictions in visual word recognition is poorly understood: They may rapidly affect lexical processes, or alternatively, influence only late post-lexical stages. To add evidence about the nature of top-down processes and their relation to bottom-up information in the timeline of word recognition, we examined influences of frequency and predictability on event-related potentials (ERPs) in several sentence reading studies. The results were related to eye movements from natural reading as well as to models of word recognition. As a first and major finding, interactions of frequency and predictability on ERP amplitudes consistently revealed top-down influences on lexical levels of word processing (Chapters 2 and 4). Second, frequency and predictability mediated relations between N400 amplitudes and fixation durations, pointing to their sensitivity to a common stage of word recognition; further, larger N400 amplitudes entailed longer fixation durations on the next word, a result providing evidence for ongoing processing beyond a fixation (Chapter 3). Third, influences of presentation rate on ERP frequency and predictability effects demonstrated that the time available for word processing critically co-determines the course of bottom-up and top-down influences (Chapter 4). Fourth, at a near-normal reading speed, an early predictability effect suggested the rapid comparison of top-down hypotheses with the actual visual input (Chapter 5). The present results are compatible with interactive models of word recognition assuming that early lexical processes depend on the concerted impact of bottom-up and top-down information. We offered a framework that reconciles the findings on a timeline of word recognition taking into account influences of frequency, predictability, and presentation rate (Chapter 4).

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