This article describes the Dual Route Cascaded (DRC) model, a computational model of visual word recognition and reading aloud. The DRC is a computational realization of the dual-route theory of reading, and is the only computational model of reading that can perform the 2 tasks most commonly used to study reading: lexical decision and reading aloud. For both tasks, the authors show that a wide variety of variables that influence human latencies influence the DRC model's latencies in exactly the same way. The DRC model simulates a number of such effects that other computational models of reading do not, but there appear to be no effects that any other current computational model of reading can simulate but that the DRC model cannot. The authors conclude that the DRC model is the most successful of the existing computational models of reading.

Much research suggests that words comprising more than one morpheme are represented in a "decomposed" manner in the visual word recognition system. In the research presented here, we investigate what information is used to segment a word into its morphemic constituents and, in particular, whether semantic information plays a role in that segmentation. Participants made visual lexical decisions to stem targets preceded by masked primes sharing (1) a semantically transparent morphological relationship with the target (e.g., cleaner-CLEAN), (2) an apparent morphological relationship but no semantic relationship with the target (e.g., corner-CORN), and (3) a nonmorphological form relationship with the target (e.g., brothel-BROTH). Results showed significant and equivalent masked priming effects in cases in which primes and targets appeared to be morphologically related, and priming in these conditions could be distinguished from nonmorphological form priming. We argue that these findings suggest a level of representation at which apparently complex words are decomposed on the basis of their morpho-orthographic properties. Implications of these findings for computational models of reading are discussed.

There is intense public interest in questions surrounding how children learn to read and how they can best be taught. Research in psychological science has provided answers to many of these questions but, somewhat surprisingly, this research has been slow to make inroads into educational policy and practice. Instead, the field has been plagued by decades of "reading wars." Even now, there remains a wide gap between the state of research knowledge about learning to read and the state of public understanding. The aim of this article is to fill this gap. We present a comprehensive tutorial review of the science of learning to read, spanning from children's earliest alphabetic skills through to the fluent word recognition and skilled text comprehension characteristic of expert readers. We explain why phonics instruction is so central to learning in a writing system such as English. But we also move beyond phonics, reviewing research on what else children need to learn to become expert readers and considering how this might be translated into effective classroom practice. We call for an end to the reading wars and recommend an agenda for instruction and research in reading acquisition that is balanced, developmentally informed, and based on a deep understanding of how language and writing systems work.

Some theories of visual word recognition postulate that there is a level of processing or representation at which morphemes are treated differently from whole words. Support for these theories has been derived from priming experiments in which the recognition of a target word is facilitated by the prior presentation of a morphologicallyrelated prime (departure-DEPART). In English, such facilitation could be due to morphological relatedness, or to some combination of the orthographic and semantic relatedness characteristic of derivationally related words. We report two sets of visual priming experiments in which the morphological, semantic, and orthographic relationships between primes and targets are varied in three SOA conditions (43 ms, 72 ms, and 230 ms). Results showed that morphological structure plays a signi cant role in the early visual recognition of English words that is independent of both semantic and orthographic relatedness. Findings are discussed in terms of current approaches to morphological processing.Requests for reprints should be addressed to Kathleen Rastle,

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Reading in many alphabetic writing systems depends on both item-specific knowledge used to read irregular words (sew, yacht) and generative spelling-sound knowledge used to read pseudowords (tew, yash). Research into the neural basis of these abilities has been directed largely by cognitive accounts proposed by the dual-route cascaded and triangle models of reading. We develop a framework that enables predictions for neural activity to be derived from cognitive models of reading using 2 principles: (a) the extent to which a model component or brain region is engaged by a stimulus and (b) how much effort is exerted in processing that stimulus. To evaluate the derived predictions, we conducted a meta-analysis of 36 neuroimaging studies of reading using the quantitative activation likelihood estimation technique. Reliable clusters of activity are localized during word versus pseudoword and irregular versus regular word reading and demonstrate a great deal of convergence between the functional organization of the reading system put forward by cognitive models and the neural systems activated during reading tasks. Specifically, left-hemisphere activation clusters are revealed reflecting orthographic analysis (occipitotemporal cortex), lexical and/or semantic processing (anterior fusiform, middle temporal gyrus), spelling-sound conversion (inferior parietal cortex), and phonological output resolution (inferior frontal gyrus). Our framework and results establish that cognitive models of reading are relevant for interpreting neuroimaging studies and that neuroscientific studies can provide data relevant for advancing cognitive models. This article thus provides a firm empirical foundation from which to improve integration between cognitive and neural accounts of the reading process.

The authors examined the regularity effect on reading aloud as a function of left-to-right phonemic position of irregularity in low-frequency exception words. Ss named 96 low-frequency exception words categorized into 5 conditions on the basis of the position (1st through 5th) of their 1st irregular grapheme-to-phoneme correspondence (GPC). Latencies and error rates for these words were compared with the rates for 96 matched GPC regular controls. Results showed that the cost of irregularity decreased monotonically over the 5 positions of irregularity. This result is offered as evidence for dual-route models of reading and against parallel distributed processing models of reading.

We present a new database of lexical decision times for English words and nonwords, for which two groups of British participants each responded to 14,365 monosyllabic and disyllabic words and the same number of nonwords for a total duration of 16 h (divided over multiple sessions). This database, called the British Lexicon Project (BLP), fills an important gap between the Dutch Lexicon Project (DLP; Keuleers, Diependaele, & Brysbaert, Frontiers in Language Sciences. Psychology, 1, 174, 2010) and the English Lexicon Project (ELP; Balota et al., 2007), because it applies the repeated measures design of the DLP to the English language. The high correlation between the BLP and ELP data indicates that a high percentage of variance in lexical decision data sets is systematic variance, rather than noise, and that the results of megastudies are rather robust with respect to the selection and presentation of the stimuli. Because of its design, the BLP makes the same analyses possible as the DLP, offering researchers with a new interesting data set of word-processing times for mixed effects analyses and mathematical modeling. The BLP data are available at http://crr.ugent.be/blp and as Electronic Supplementary Materials.Electronic supplementary materialThe online version of this article (doi:10.3758/s13428-011-0118-4) contains supplementary material, which is available to authorized users.