Individual Differences in Reading Speed are Linked to Variability in the Processing of Lexical and Contextual Information: Evidence from Single-trial Event-related Brain Potentials

Abstract

In the current paper, we examined the effects of lexical (e.g. word frequency, orthographic neighborhood density) and contextual (e.g. word predictability in the form of cloze probability) features on single-trial event-related brain potentials in a self-paced reading paradigm. Critically, we examined whether individual differences in reading speed modulated single-trial effects on the N400, an ERP component linked to semantic memory access. Consistent with past work, we found that word frequency effects on the N400 were attenuated with increasing predictability. However, effects of orthographic neighborhood density were robust across all levels of predictability. Importantly, individual differences in reading speed moderated the influence of both frequency and predictability (but not orthographic neighborhood density) on the N400, such that slower readers showed reduced effects compared to faster readers. These data show that different lexical factors influence word processing through dissociable mechanisms. Our findings support a dynamic semantic-memory access model of the N400, in which information at multiple levels (lexical, sentential, individual) simultaneously contributes to the unfolding neural dynamics of comprehension.

Keywords:

• Lexical processing
• reading
• event-related brain potential
• EEG
• semantics

Notes

1 Follow-up analyses were conducted to test the sensitivity of our effects to specification of electrode site in the model, including electrode as a fixed effect, picking of a single a priori representative electrode for analysis (Cz), and aggregating mean amplitudes across all 8 electrodes. Importantly, our results were robust to differences in the specification of electrode.

2 There is a sizeable correlation between word length and orthographic neighborhood that is driven by the fact that words that are quite long tend to have a sparse orthographic neighborhood space. Given the high degree of correlation between word length and ON, there is concern about collinearity influencing model parameters. Given that length effects are not theorized to directly impact N400 amplitudes, these effects were not included in the current models. We did conduct a follow-up analysis including both length and ON; however, SEs of the fixed effects of the lexical features were considerably inflated in this model suggesting problems with high multicollinearity. Nevertheless, we conducted an additional analysis aimed at examining the effects of ON in a model without longer words (that necessarily contain fewer neighbors; see also Payne et al. 2015). This analysis was conducted on a restricted dataset excluding words longer than eight characters. Importantly, we still observed reliable relationships between ON and N400 amplitude in the restricted dataset.

Additional information

Funding

This work was supported by National Institute on Aging (US): [Grant Number AG026308].