Word predictability effects are linear, not logarithmic: Implications for probabilistic models of sentence comprehension.

During language comprehension, we routinely use information from the prior context to help identify the meaning of individual words. While measures of online processing difficulty, such as reading times, are strongly influenced by contextual predictability, there is disagreement about the mechanisms underlying this lexical predictability effect, with different models predicting different linking functions - linear (Reichle, Rayner & Pollatsek, 2003) or logarithmic (Levy, 2008). To help resolve this debate, we conducted two highly-powered experiments (self-paced reading, N = 216; cross-modal picture naming, N = 36), and a meta-analysis of prior eye-tracking while reading studies (total N = 218). We observed a robust linear relationship between lexical predictability and word processing times across all three studies. Beyond their methodological implications, these findings also place important constraints on predictive processing models of language comprehension. In particular, these results directly contradict the empirical predictions of surprisal theory, while supporting a proportional pre-activation account of lexical prediction effects in comprehension.