Daragh E. Sibley

Individual Differences in Visual Word Recognition: Insights from the English Lexicon Project

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 among individuals who contributed to the English Lexicon Project (http://elexicon.wustl.edu), an online behavioral database containing nearly 4 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 their utilization of lexical and nonlexical information.

The relationship between phonological and auditory processing and brain organization in beginning readers

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.

Large‐Scale Modeling of Wordform Learning and Representation

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 word-forms. 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.

Responding to Nonwords in the Lexical Decision Task: Insights From the English Lexicon Project

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, because 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 base-word number of syllables, and negatively correlated with Levenshtein orthographic distance and base-word 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., base-word frequency). The present findings provide well-specified and interesting new constraints for informing models of word recognition and lexical decision.

Dissociations in Performance on Novel Versus Irregular Items: Single‐Route Demonstrations With Input Gain in Localist and Distributed Models

Four pairs of connectionist simulations are presented in which quasi-regular mappings are computed using localist and distributed representations. In each simulation, a control parameter termed input gain was modulated over the only level of representation that mapped inputs to outputs. Input gain caused both localist and distributed models to shift between regularity-based and item-based modes of processing. Performance on irregular items was selectively impaired in the regularity-based modes, whereas performance on novel items was selectively impaired in the item-based modes. Thus, the models exhibited double dissociations without separable processing components. These results are discussed in the context of analogous dissociations found in language domains such as word reading and inflectional morphology.

Learning orthographic and phonological representations in models of monosyllabic and bisyllabic naming

Most current models of word naming are restricted to processing monosyllabic words and pseudowords. This limitation stems from difficulties in representing the orthographic and phonological codes for words varying substantially in length. Sibley, Kello, Plaut, and Elman (2008) described an extension of the simple recurrent network architecture, called the sequence encoder, that learned orthographic and phonological representations of variable-length words. The present research explored the use of sequence encoders in models of monosyllabic and bisyllabic word naming. Performance in these models is comparable to other models in terms of word and pseudoword naming accuracy, as well as accounting for naming latency phenomena. Although the models do not address all naming phenomena, the results suggest that sequence encoders can learn orthographic and phonological representations, making it easier to create models that scale up to larger vocabularies, while accounting for behavioural data.

PC-Based Game Features That Influence Instruction and Learner Motivation

PC-based games are currently being used for military training, but the instructional and motivational features of such technology are not well understood. To identify features of training games that influence instruction and motivation, a popular first-person-perspective game with a military theme was analyzed empirically. Twenty-one participants played the “basic training” portion of the game, which included Army background information, virtual marksmanship training, an obstacle course, virtual weapons familiarization, and an urban terrain training mission. The results of this research provide useful information to individuals developing training games, desktop simulations, and interactive multimedia courseware to meet optimal training objectives and strategies.

A computational exploration of double dissociations: modes of processing instead of components of processing

Two connectionist models are reported that simulated the defining features of the double dissociation between phonological and surface dyslexia in word reading. One model was a feed-forward, three-layer perceptron, and the other included recurrent connections. Neither model contained an architectural separation of sublexical and lexical processes, nor of phonological and semantic processes. Analyses showed that the double dissociation was simulated because the control parameter input gain shifted the models between conjunctive and componential modes of processing. The dissociation was not simulated by any kind of damage to separate system components. The simulations are discussed in the context of current accounts of surface and phonological dyslexia.

Impact of dialect use on a basic component of learning to read

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.