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Title: Prediction revision in language processing

Abstract:

Language unfolds in real time, requiring comprehenders to continuously integrate new input and construct coherent mental representations. A key mechanism facilitating this process is prediction, where comprehenders anticipate upcoming language based on contextual cues. Research shows that when new linguistic information contradicts initial predictions, comprehenders can rapidly revise their expectations. In this talk, I will explore three key questions: (1) Do prediction violations impose a cognitive cost on subsequent processing? (2) Does the presence of a local competitor interfere with prediction revision? (3) What role do bottom-up associative priming and top-down pre-activation play in prediction revision? To address these questions, I will present findings from visual-world eye-tracking and ERP studies, using Mandarin Chinese as a test case. This research offers deeper insight into how comprehenders generate and dynamically adjust predictions during real-time language comprehension.

Bio:

Kayla Keyue Chen (https://keyue-c.github.io/) is a final-year PhD student in the Department of Linguistics, Division of Psychology and Language Sciences at University College London. Her research explores predictive mechanisms in language processing.