Slow readers capitalize on predictive processing

Working memory constraints have been shown to be pervasive in human sentence comprehension. Working memory-based theories of sentence comprehension predict the locality effect: when the distance between two linguistically related words (e.g., a subject and a verb) increases, the processing difficulty increases. While the locality effect has been consistently observed in English, there is no sufficient evidence for locality in verb-final languages such as Hindi and German. The absence of locality in verb-final languages is attributed to robust prediction of the verb, which may override certain working memory demands. We take an individual differences approach to study how working memory and prediction interact. In four self-paced reading experiments in Hindi, we consistently find an anti-locality effect: Speedup at the verb when the argument-verb distance is increased. However, individuals differ in their extent of locality effect. Why do certain individuals in a language population show stronger anti-locality effects than others? We test two competing hypotheses: (i) Varying prediction-strength hypothesis: Individuals with stronger predictability of the verb would show larger anti-locality effects and faster reader times, on average; (b) Varying lexical-access hypothesis: Individuals with poorer lexical accessibility are, on average, slower in reading and may capitalize more on predictability, showing larger anti-locality effects. The two hypotheses make opposite predictions about the correlation between the individual-level locality effect and reading speed. We find strong evidence that slow readers exhibit stronger anti-locality effects. The results support the varying lexical access hypothesis, implying that individuals with slowed lexical access compensate with predictive processing.