Empirical work and models of visual word recognition have traditionally focused on group-level performance. Despite the emphasis on the prototypical reader, there is clear evidence that variation in reading skill modulates word recognition performance. In the present study, we examined differences between individuals who contributed to the English Lexicon Project (http://elexicon.wustl.edu), an online behavioral database containing nearly four million word recognition (speeded pronunciation and lexical decision) trials from over 1,200 participants. We observed considerable within- and between-session reliability across distinct sets of items, in terms of overall mean response time (RT), RT distributional characteristics, diffusion model parameters (Ratcliff, Gomez, & McKoon, 2004), and sensitivity to underlying lexical dimensions. This indicates reliably detectable individual differences in word recognition performance. In addition, higher vocabulary knowledge was associated with faster, more accurate word recognition performance, attenuated sensitivity to stimuli characteristics, and more efficient accumulation of information. Finally, in contrast to suggestions in the literature, we did not find evidence that individuals were trading-off in their utilization of lexical and nonlexical information.

We employed brain-behavior analyses to explore the relationship between performance on tasks measuring phonological awareness, pseudoword decoding, and rapid auditory processing (all predictors of reading (dis)ability) and brain organization for print and speech in beginning readers. For print-related activation, we observed a shared set of skill-correlated regions, including left hemisphere temporoparietal and occipitotemporal sites, as well as inferior frontal, visual, visual attention, and subcortical components. For speech-related activation, shared variance among reading skill measures was most prominently correlated with activation in left hemisphere inferior frontal gyrus and precuneus. Implications for brain-based models of literacy acquisition are discussed.

Researchers have extensively documented how various statistical properties of words (e.g., word-frequency) influence lexical processing. However, the impact of lexical variables on nonword decision-making performance is less clear. This gap is surprising, since a better specification of the mechanisms driving nonword responses may provide valuable insights into early lexical processes. In the present study, item-level and participant-level analyses were conducted on the trial-level lexical decision data for almost 37,000 nonwords in the English Lexicon Project in order to identify the influence of different psycholinguistic variables on nonword lexical decision performance, and to explore individual differences in how participants respond to nonwords. Item-level regression analyses reveal that nonword response time was positively correlated with number of letters, number of orthographic neighbors, number of affixes, and baseword number of syllables, and negatively correlated with Levenshtein orthographic distance and baseword frequency. Participant-level analyses also point to within- and between-session stability in nonword responses across distinct sets of items, and intriguingly reveal that higher vocabulary knowledge is associated with less sensitivity to some dimensions (e.g., number of letters) but more sensitivity to others (e.g., baseword frequency). The present findings provide well-specified and interesting new constraints for informing models of word recognition and lexical decision.

Can some black-white differences in reading achievement be traced to differences in language background? Many African American children speak a dialect that differs from the mainstream dialect emphasized in school. We examined how use of alternative dialects affects decoding, an important component of early reading and marker of reading development. Behavioral data show that use of the alternative pronunciations of words in different dialects affects reading aloud in developing readers, with larger effects for children who use more African American English (AAE). Mechanisms underlying this effect were explored with a computational model, investigating factors affecting reading acquisition. The results indicate that the achievement gap may be due in part to differences in task complexity: children whose home and school dialects differ are at greater risk for reading difficulties because tasks such as learning to decode are more complex for them.

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the sequence encoder is used to learn nearly 75,000 wordform representations through exposure to strings of stress-marked phonemes or letters. First, the mechanisms and efficacy of the sequence encoder are demonstrated and shown to overcome problems with traditional slot-based codes. Then, two large-scale simulations are reported that learned to represent lexicons of either phonological or orthographic wordforms. In doing so, the models learned the statistics of their lexicons as shown by better processing of well-formed pseudowords as opposed to ill-formed (scrambled) pseudowords, and by accounting for variance in well-formedness ratings. It is discussed how the sequence encoder may be integrated into broader models of lexical processing.