Steven Saunders

Assessing the basic components of reading: A revision of the Castles and Coltheart test with new norms

We present administration details and normative data for a new version of the word and nonword reading test originally developed by Castles and Coltheart. The new test contains an expanded set of items, with 40 each of regular words, irregular words and nonwords, rather than the original 30 items of each type. The new items extend the upper-end of the difficulty range of the test, making it less susceptible to ceiling effects than the original version. The test also incorporates a stopping-rule, which makes administration of the test less time-consuming and removes the stress on children who can only read a few items. The test is free of charge and is available to teachers, professionals and researchers in both pencil-and-paper and computer-based formats from the Macquarie On-line Test Interface (MOTIF: http://www.maccs.mq.edu.au/research/resources).

Computational Modeling of Reading in Semantic Dementia: Comment on Woollams, Lambon Ralph, Plaut, and Patterson (2007)

Woollams, Lambon Ralph, Plaut, and Patterson reported detailed data on reading in 51 cases of semantic dementia. They simulated some aspects of these data using a connectionist parallel distributed processing (PDP) triangle model of reading. We argue here that a different model of reading, the dual route cascaded (DRC) model of Coltheart, Rastle, Perry, Langdon, and Ziegler (2001), not only provides a more accurate simulation of these aspects of reading in semantic dementia than does the PDP model but also provides highly accurate simulations of other aspects of reading in this disorder that the PDP approach has not simulated. We conclude that our findings add to evidence both from simulations of normal skilled reading and from simulations of other kinds of acquired dyslexia that the nonconnectionist DRC model of reading offers a better account of normal and disordered reading than the connectionist PDP models of reading.

Can the dual-route cascaded computational model of reading offer a valid account of the masked onset priming effect?

The masked onset priming effect (MOPE) refers to the empirical finding that target naming is faster when the target (SIB) is preceded by a briefly presented masked prime that starts with the same letter/phoneme (suf) than when it does not (mof; Kinoshita, 2000, Experiment 1). The dual-route cascaded (DRC) computational model of reading (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) has offered an explanation for how the MOPE might occur in humans. However, there has been some empirical discrepancy regarding whether for nonword items the effect is limited to the first-letter/phoneme overlap between primes and targets or whether orthographic/phonological priming effects occur beyond the first letter/phoneme. Experiment 1 tested these two possibilities. The human results, which were successfully simulated by the DRC model, showed priming beyond the first letter/phoneme. Nevertheless, two recent versions of the DRC model made different predictions regarding the nature of these priming effects. Experiment 2 examined whether it is facilitatory, inhibitory, or both, in order to adjudicate between the two versions of the model. The human results showed that primes exert both facilitatory and inhibitory effects.

Is the orthographic/phonological onset a single unit in reading aloud?

Two main theories of visual word recognition have been developed regarding the way orthographic units in printed words map onto phonological units in spoken words. One theory suggests that a string of single letters or letter clusters corresponds to a string of phonemes (Coltheart, 1978; Venezky, 1970), while the other suggests that a string of single letters or letter clusters corresponds to coarser phonological units, for example, onsets and rimes (Treiman & Chafetz, 1987). These theoretical assumptions were critical for the development of coding schemes in prominent computational models of word recognition and reading aloud. In a reading-aloud study, we tested whether the human reading system represents the orthographic/phonological onset of printed words and nonwords as single units or as separate letters/phonemes. Our results, which favored a letter and not an onset-coding scheme, were successfully simulated by the dual-route cascaded (DRC) model (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001). A separate experiment was carried out to further adjudicate between 2 versions of the DRC model.

Computational modelling of the masked onset priming effect in reading aloud

The masked onset priming effect (MOPE) was first defined by Forster and Davis (1991) as the finding that human naming latencies are faster when a target word (e.g., BREAK) is preceded by a briefly presented masked prime word that shares its initial sound with the target (e.g., belly) compared to when it does not (e.g., merry) or when it rhymes with it (e.g., stake). The present paper presents a review of empirical findings on the MOPE in the English language and their simulations by the DRC computational model of reading (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001), which offers an explicit account of how the effect might occur in humans. A new version of DRC, called DRC 1.2, which differs from the previous downloadable DRC version mainly in the way its nonlexical route operates, has been recently developed. The performance of DRC 1.2 on simulating the MOPE is evaluated in this paper.

Computational modelling of the effects of semantic dementia on visual word recognition

Rogers, Lambon Ralph, Hodges, and Patterson (2004) studied two-alternative forced-choice visual lexical decision performance in patients with semantic dementia. With item pairs where the target word was more “typical” (i.e., higher in bigram and trigram frequency) than the foil (all foils were pseudohomophones), lexical decision performance was good and was unaffected by word frequency. With item pairs where the target word was less “typical” (i.e., lower in bigram and trigram frequency) than the foil, lexical decision performance was worse and was affected by word frequency, being particularly inaccurate when the word targets were low in frequency. We show (using as materials all the monosyllabic items used by Rogers and colleagues) that the same pattern of results occurs in the lexical decision performance of the DRC (dual-route cascaded) computational model of reading when the model is lesioned by probabilistic deletion of low-frequency words from its orthographic lexicon. We consider that the PDP (parallel distributed processing) computational model of reading used by Woollams, Plaut, Lambon Ralph, and Patterson (2007) to simulate reading in semantic dementia is not capable of simulating this lexical decision result. We take this, in conjunction with previous work on computational modelling of reading aloud in surface dyslexia, phonological dyslexia, and semantic dementia using the DRC and PDP reading models, to indicate that the DRC model does a better job than the PDP model in accounting for what is known about the various forms of acquired dyslexia.

Reading aloud: The cumulative lexical interference effect

Picture naming shows a cumulative semantic interference effect: Latency for naming a target picture increases as a function of the number of pictures semantically similar to the target that have previously been named (Howard, Nickels, Coltheart, & Cole-Virtue, Cognition 100:464–482, 2006). Howard and colleagues, and also Oppenheim, Dell, and Schwartz (Cognition 114:227–252, 2010), argued that this occurs because of the joint presence in the picture-naming system of three critical properties: shared activation, priming, and competition. They also discussed the possibility that whenever any cognitive system possesses these three properties, a cumulative similarity-based interference effect from repeated use of that cognitive system will occur. We investigated this possibility by looking for a cumulative lexical interference effect when the task is reading aloud: Will the latency of reading a target word aloud increase as a function of the number of words orthographically/phonologically similar to the target that have previously been read aloud? We found that this was so. This supports the general idea that cumulative similarity-based interference effects will arise whenever any cognitive system that possesses the three key properties of shared activation, priming, and competition is repeatedly used.

Phonotactic Constraints: Implications for Models of Oral Reading in Russian.

The present article investigates how phonotactic rules constrain oral reading in the Russian language. The pronunciation of letters in Russian is regular and consistent, but it is subject to substantial phonotactic influence: the position of a phoneme and its phonological context within a word can alter its pronunciation. In Part 1 of the article, we analyze the orthography-to-phonology and phonology-to-phonology (i.e., phonotactic) relationships in Russian monosyllabic words. In Part 2 of the article, we report empirical data from an oral word reading task that show an effect of phonotactic dependencies on skilled reading in Russian: humans are slower when reading words where letter-phoneme correspondences are highly constrained by phonotactic rules compared with those where there are few or no such constraints present. A further question of interest in this article is how computational models of oral reading deal with the phonotactics of the Russian language. To answer this question, in Part 3, we report simulations from the Russian dual-route cascaded model (DRC) and the Russian connectionist dual-process model (CDP++) and assess the performance of the 2 models by testing them against human data.

Effects of homophony on reading aloud : implications for models of speech production

In this paper we investigate whether homophones have shared (e.g., Dell, 1990; Levelt, Roelofs, & Meyer, 1999) or independent (e.g., Caramazza, Costa, Miozzo, & Bi, 2001) phonological representations. We carried out a homophone reading aloud task with low frequency irregular homophones and matched low frequency irregular non-homophonic controls. The ‘Shared Representation’ view predicted a homophone advantage: homophones should be read faster than their matched controls because the low frequency homophone inherits the frequency of its high frequency partner. The ‘Independent Representation’ view predicted neither an advantage nor a disadvantage: performance should be governed by the homophones specific-word frequency. Results showed that low frequency homophones were read aloud slower than non-homophonic controls. Results were confirmed with an independent database of reading latencies (Balota, Cortese, Hutchison, Neely, Nelson, Simpson, & Treiman, 2002). Additionally, attempts to simulate the homophone disadvantage effect using current computational models of reading aloud were all unsuccessful. The homophone disadvantage effect constitutes, therefore, a new challenge for all computational reading models to date.

Lexical and sublexical effects on visual word recognition in Greek: comparing human behavior to the dual route cascaded model

ABSTRACT We evaluated the dual route cascaded (DRC) model of visual word recognition using Greek behavioural data on word and nonword naming and lexical decision, focusing on the effects of syllable and bigram frequency. DRC was modified to process polysyllabic Greek words and nonwords. The Greek DRC and native speakers of Greek were presented with the same sets of word and nonword stimuli, spanning a wide range on several psycholinguistic variables, and the sensitivity of the model to lexical and sublexical variables was compared to the effects of these factors on the behavioural data. DRC pronounced correctly all the stimuli and successfully simulated the effects of frequency in words, and of length and bigram frequency in nonwords. However, unlike native speakers of Greek, DRC failed to demonstrate sensitivity to word length and syllabic frequency. We discuss the significance of these findings in constraining models of visual word recognition.