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Set for variability (SfV) is an oral language task that requires an individual to disambiguate the mismatch between the decoded form of an irregular word and its actual lexical pronunciation. For example, in the task, the word wasp is pronounced to rhyme with clasp (i.e. /waesp/), and the individual must recognize the actual pronunciation of the word to be /w[alpha]sp/. SfV has been shown to be a significant predictor of both item-specific and general word reading variance above and beyond that associated with phonemic awareness skill, letter-sound knowledge, and vocabulary skill. However, very little is known about the child characteristics and word features that affect SfV item performance. In this study, we explored whether word features and child characteristics that involve phonology only are adequate to explain item-level variance in SfV performance or whether including predictors that involve the connection between phonology and orthography explains additional variance. To accomplish this, we administered the SfV task (N = 75 items) to a sample of grade 2-5 children (N = 489), along with a battery of reading, reading related, and language measures. Results suggest that variance in SfV performance is uniquely accounted for by measures tapping phonological skill along with those capturing knowledge of phonology to orthography associations, but more so in children with better decoding skill. Additionally, word reading skill was found to moderate the influence of other predictors suggesting that how the task is approached may be impacted by word reading and decoding ability.

Statistical views of reading highlight the link between proficient literacy and the assimilation of various regularities embedded in writing systems, including those in the mapping between print and meaning. Still, orthographic-semantic (O-S) regularities remain relatively understudied, with open questions regarding 3 issues: (a) how O-S regularities should be quantified, (b) how they impact the behavior of proficient readers, and (c) whether individual differences in sensitivity to these regularities predict reading skills. The goal of the current article is to address these questions. We start by reviewing previous studies estimating print-meaning regularities, where orthography-to-semantics consistency (OSC) is defined as the mean semantic similarity between a word and its orthographic neighbors. While we adopt this general strategy, we identify a potential confound in previous operational definitions. We therefore offer a modified measure, which we use to examine group-level OSC effects in available data sets of single word recognition and reading for comprehension. Our findings validate the existence of OSC effects but reveal variation across tasks, with OSC effects emerging more strongly in tasks involving a direct mapping of print to meaning. Next, we present a reanalysis of word naming data from 399 second through fifth graders, where we examine individual differences in reliance on O-S regularities and their relation to participants' reading skills. We show that early readers whose naming accuracy is more influenced by OSC (i.e., those who rely more on O-S) have better passage comprehension abilities. We conclude by discussing the role of O-S regularities in proficient reading and literacy acquisition.

There is now considerable evidence regarding the types of interventions that are effective at remediating reading disabilities on average. It is generally unclear, however, what predicts the magnitude of individual-level change following a given intervention. We examine new predictors of intervention gains that are theoretically grounded in computational models of reading and focus on individual differences in the functional organization of the reading system. Specifically, we estimate the extent to which children with reading disabilities (n = 118 3rd-4th graders) rely on two sources of information during an oral word reading task-print-speech correspondences and semantic imageability--before and after a phonologically-weighted intervention. We show that children who relied more on print-speech regularities and less on imageability preintervention had better intervention gains. In parallel, children who over the course of the intervention exhibited greater increases in their reliance on print-speech correspondences and greater decreases in their reliance on imageability, had better intervention outcomes. Importantly, these two factors were differentially related to specific reading task outcomes, with greater reliance on print-speech correspondences associated with pseudoword naming, while (lesser) reliance on imageability related to word reading and comprehension. We discuss the implications of these findings for theoretical models of reading acquisition and educational practice.

We modeled word reading growth in typically developing (n = 118) and children with dyslexia (n = 20), Grades 2-5, across multiple exposures to 30 words. We explored the facilitative versus inhibitory effects of exposures to differential mixes of words that support high- versus low-frequency vowel pronunciations. One training corpus contained a ratio of 80%-20% high- to low-frequency pronunciations (e.g., for "ea"; 80% "ea" pronounced as /i/ as in "bead" and 20% "ea" pronounced /[epsilon]/ as in "dead"), whereas the other consisted of a ratio of 20%-80%. We also modeled accuracy at the final exposure for a subset of 12 shared words across conditions using item-level crossed-random effects models with reading skill (i.e., typically developing vs. dyslexic), condition, word frequency, and vowel pronunciation (i.e., high- vs. low-frequency vowel pronunciation) as predictors in the model. We were particularly interested in the interaction between condition and vowel pronunciation across reading groups. Results suggest typically developing children were influenced by the interaction between condition and vowel pronunciation, suggesting both facilitation and inhibition, whereas children with dyslexia were influenced by condition and vowel pronunciation without an interaction. Results are interpreted within the overfitting model of dyslexia.

Visual word recognition is facilitated by the presence of "orthographic neighbors" that mismatch the target word by a single letter substitution. However, researchers typically do not consider "where" neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of "enemies" at each letter position (how many neighbors mismatch the target word at that position). Analyses of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over-time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions.

To investigate the neural basis of a common statistical learning mechanism involved in motor sequence learning and decoding, we recorded brain activation from participants during a serial reaction time (SRT) task and a word reading task using functional magnetic resonance imaging. In the SRT task, a manual response was made depending on the location of a visual cue, and the order of the locations was either fixed or random. In the word reading task, visual words were passively presented. In the inferior frontal gyrus pars triangularis (IFGpTr) and the insula, differences in activation between the ordered and random condition in the SRT task and activation to printed words in the word reading task were correlated with the participants' decoding ability. We speculate that extraction of statistically predictable patterns in the IFGpTr and insula contributes to both motor sequence learning and orthographic learning, and therefore predicts individual differences in decoding skill.

The strategy underlying most computational models of word reading is to specify the organization of the reading system--its architecture and the processes and representations it employs--and to demonstrate that this organization would give rise to the behavior observed in word reading tasks. This approach fails to adequately address the variation in reading behavior observed across and within linguistic communities. Only computational models that incorporate learning can fully account for variation in organization. However, even extant learning models (e.g., the triangle model) must be extended if they are to fully account for variation in organization. The challenges associated with extending theories in this way are discussed.

Previous studies haves shown that under masked priming conditions, CORNER primes CORN as strongly as TEACHER primes TEACH and more strongly than BROTHEL primes BROTH. This result has been taken as evidence of a purely structural level of representation at which words are decomposed into morphological constituents in a manner that is independent of semantics. The research reported here investigated the influence of semantic transparency on long-term morphological priming. Two experiments demonstrated that while lexical decisions were facilitated by semantically transparent primes like TEACHER, semantically opaque words like CORNER had no effect. Although differences in the nonword foils used in each experiIment gave rise to somewhat different patterns of results, this difference in the effects of transparent and opaque primes was found in both experiments. The implications of this finding for accounts of morphological effects on visual word identification are discussed. (Contains 2 tables and 3 footnotes.)

We propose and test a theoretical perspective in which a universal hallmark of successful literacy acquisition is the convergence of the speech and orthographic processing systems onto a common network of neural structures, regardless of how spoken words are represented orthographically in a writing system. During functional MRI, skilled adult readers of four distinct and highly contrasting languages, Spanish, English, Hebrew, and Chinese, performed an identical semantic categorization task to spoken and written words. Results from three complementary analytic approaches demonstrate limited language variation, with speech-print convergence emerging as a common brain signature of reading proficiency across the wide spectrum of selected languages, whether their writing system is alphabetic or logographic, whether it is opaque or transparent, and regardless of the phonological and morphological structure it represents.

Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). Analyses of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over-time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions. [ABSTRACT FROM AUTHOR]

It is generally well accepted that proficient reading requires the assimilation of myriad statistical regularities present in the writing system, including in particular the correspondences between words' orthographic and phonological forms. There is considerably less agreement, however, as to how to quantify these regularities. Here we present a comprehensive approach for this quantification using tools from Information Theory. We start by providing a glossary of the relevant information-theoretic metrics, with simplified examples showing their potential in assessing orthographic-phonological regularities. We specifically highlight the flexibility of our approach in quantifying information under different contexts (i.e., context-independent and dependent readings) and in different types of mappings (e.g., orthography-to-phonology and phonology-to-orthography). Then, we use these information-theoretic measures to assess real-world orthographic-phonological regularities of 10,093 mono-syllabic English words and examine whether these measures predict inter-item variability in accuracy and response times using available large-scale datasets of naming and lexical decision tasks. Together, the analyses demonstrate how information-theoretical measures can be used to quantify orthographical-phonological correspondences, and show that they capture variance in reading performance that is not accounted for by existing measures. We discuss the similarities and differences between the current framework and previous approaches as well as future directions towards understanding how the statistical regularities embedded in a writing system impact reading and reading acquisition. [ABSTRACT FROM AUTHOR]

Previous studies haves shown that under masked priming conditions, CORNER primes CORN as strongly as TEACHER primes TEACH and more strongly than BROTHEL primes BROTH. This result has been taken as evidence of a purely structural level of representation at which words are decomposed into morphological constituents in a manner that is independent of semantics. The research reported here investigated the influence of semantic transparency on long-term morphological priming. Two experiments demonstrated that while lexical decisions were facilitated by semantically transparent primes like TEACHER, semantically opaque words like CORNER had no effect. Although differences in the nonword foils used in each experiment gave rise to somewhat different patterns of results, this difference in the effects of transparent and opaque primes was found in both experiments. The implications of this finding for accounts of morphological effects on visual word identification are discussed. [ABSTRACT FROM AUTHOR]

This article provides an overview of a dynamical systems approach to visual word recognition. In this approach, the dynamics of word recognition are characterized in terms of a connectionist network model. According to this model, seeing a word results in changes in the pattern of activation over the nodes in the lexical network such that, over time, the network moves into an attractor state representing the orthographic, phonological, and semantic properties of that word. At a slower timescale, a learning process modifies the strengths of the connections among the nodes in a way that attunes the network to the statistical regularities in its environment. This view of word identification accommodates a wide body of empirical results, a representative sampling of which is discussed here. Finally, the article closes with a discussion of some of the theoretical issues that should be addressed as the dynamical approach continues to develop. [ABSTRACT FROM AUTHOR]

Set for variability (SfV) is an oral language task that requires an individual to disambiguate the mismatch between the decoded form of an irregular word and its actual lexical pronunciation. For example, in the task, the word wasp is pronounced to rhyme with clasp (i.e. /wæsp/), and the individual must recognize the actual pronunciation of the word to be /wɒsp/. SfV has been shown to be a significant predictor of both item-specific and general word reading variance above and beyond that associated with phonemic awareness skill, letter-sound knowledge, and vocabulary skill. However, very little is known about the child characteristics and word features that affect SfV item performance. In this study, we explored whether word features and child characteristics that involve phonology only are adequate to explain item-level variance in SfV performance or whether including predictors that involve the connection between phonology and orthography explains additional variance. To accomplish this, we administered the SfV task (N = 75 items) to a sample of grade 2–5 children (N = 489), along with a battery of reading, reading related, and language measures. Results suggest that variance in SfV performance is uniquely accounted for by measures tapping phonological skill along with those capturing knowledge of phonology to orthography associations, but more so in children with better decoding skill. Additionally, word reading skill was found to moderate the influence of other predictors suggesting that how the task is approached may be impacted by word reading and decoding ability. Educational Impact and Implications Statement: Set for variability (SfV) is a powerful predictor of word recognition skill in developing readers. The measure taps children's ability to go from the decoded form of a word (e.g., /wʌz/for was) to the correct form (e.g., /wɒz/ for was), which is considered an important second step in word decoding. In the current study, we worked to determine what factors lead to variability in children's ability to perform the task. We found that performance on the SfV task was highly correlated with children's phonemic awareness skill and also related to their reading and decoding skill. This suggests that children with advanced reading and decoding skill may be using both phonological and spelling skills to go from the decoded form of a word to the correct pronunciation. The findings suggest that further studies evaluating the causal influence of SfV on reading development are warranted. [ABSTRACT FROM AUTHOR]