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Dual route models of reading suggest there are 2 pathways for reading words: an orthographic-lexical pathway, used to read familiar regular words and exception words, and a grapheme-to-phoneme-conversion-(GPC)-sublexical pathway, used to read unfamiliar regular words, pseudohomophones (PHs), and nonwords. It is unclear, however, whether PHs activate lexical and semantic representations without intention in the GPC-sublexical pathway to the same extent as words along the orthographic-lexical pathway. The present study explored this by introducing a novel condition, color pseudohomophone associates (CPHAs; e.g., "skigh"), in 3 experiments using the Stroop paradigm. Experiment 1 examined 4 types of stimuli: color words (CWs), color word associates (CWAs), color PHs (CPHs), and color PH associates (CPHAs), in a mixed list context. Significant Stroop effects were found for all 4 types of stimuli. To ensure the robustness of this effect, Experiment 2 was conducted using pure list contexts whereby participants received only word stimuli (e.g., CWs, CWAs) or only PH stimuli (e.g., CPHs, CPHAs). The results replicated those of Experiment 1, suggesting that CPHAs activate lexical and semantic representations without intention in the GPC-sublexical pathway. Experiment 3 added 2 novel conditions: color exception word associates (which can only be pronounced correctly using the orthographic-lexical pathway) to compare the effects obtained with color exception PH associates (which rely on the GPC-sublexical pathway for correct pronunciation). Stroop effects of similar magnitude were found for both types of stimuli, suggesting lexical and semantic representations are accessed without intention in either reading pathway to a similar degree. Implications for models of reading are discussed.

The aim of this work is to combine behavioural and functional magnetic resonance imaging (fMRI) data to advance our knowledge of where the Frequency x Regularity interaction on word naming is located in the cerebral cortex. Participants named high and low frequency, regular and exception words in a behavioural lab (Experiment 1) and during an fMRI study (Experiment 2). We used the Additive Factors Method (AFM) to localize the expected overadditive Frequency x Regularity interaction both temporally, through word naming reaction times (whereby low frequency exceptions produce the longest reaction times), and spatially on the cortex, through hemodynamic response measures from fMRI (whereby low frequency exceptions produce the highest activation intensities). Activation maps revealed significant activation for low frequency exception words in the supplementary motor association cortex (SMA). We interpret the SMA activation as increased articulatory preparation, given previous demonstrations of the SMA's involvement in motor programming. Hemodynamic time courses were extracted from four regions of interest: the middle temporal gyri, SMA, insula and the inferior frontal gyri. Importantly, hemodynamic intensities within the SMA displayed an overadditive interaction pattern parallel to that found with naming reaction times. Thus, we provide an application of the AFM to fMRI intensity measures and evidence that the SMA is a potential cortical source of the Frequency x Regularity interaction during a basic naming paradigm. While the AFM has traditionally been used to localize factors in time we provide evidence that the AFM is useful in understanding how variables influence one another in the brain. (Contains 1 table and 7 figures.)

D. C. Plaut and J. R. Booth presented a parallel distributed processing model that purports to simulate human lexical decision performance. This model (and D. C. Plaut, 1995) offers a single mechanism account of the pattern of factor effects on reaction time (RT) between semantic priming, word frequency, and stimulus quality without requiring a stages-of-processing account of additive effects. Three problems are discussed. First, no evidence is provided that this model can discriminate between words and nonwords with the same orthographic structure and still produce the pattern of factor effects on RT it currently claims to produce. Second, the level of representation used by the model to make a lexical decision is inconsistent with what is known about how skilled readers with damage to their semantic system make word/nonword discriminations. Finally, there are a number of results that are difficult to reconcile with the single mechanism account. The authors' preference is to retain the stages-of-processing account.

Recent research on developmental dyslexia has suggested a phonological core deficit hypothesis (e.g., Manis, Seidenberg, Doi, McBride-Chang, & Peterson, 1996; Stanovich, Siegel, & Gottardo, 1997) whereby pure cases of developmental phonological dyslexia (dysfunctional phonetic decoding processing but normal sight vocabulary processing) can exist, but pure cases of developmental surface dyslexia (dysfunctional sight vocabulary processing but normal phonetic decoding processing) should not. By applying Jacoby's (1991) and Lindsay and Jacoby's (1994) process dissociation procedure to the reading of regular and exception words, we present a method that serves to estimate readers' reliance on sight vocabulary and phonetic decoding during real word recognition. These reliance estimates are then used in Castles and Coltheart's (1993) regression-based approach to identify normal readers and developmental dyslexics. This new method: (1) allows one to explore normal reading acquisition and both the delay and deviance accounts of developmental dyslexia, (2) provides an alternative to matching dyslexics to both chronological-age and reading-age control groups, and (3) uses only real words. We present evidence that pure cases of developmental surface dyslexia can be obtained with both Castles and Coltheart's measure as well as our own, and that developmental surface dyslexia is not simply a delayed reading deficit. The theoretical importance and utility of estimates of reliance on sight vocabulary and phonetic decoding is discussed.

The present research investigated the relationship between Rapid Automatized Naming (RAN) performance, letter-string reading measures of sight vocabulary (SV) and phonetic decoding (PD), and lexical decision. Criterion-based naming rates were obtained from three types of RAN tasks: digits, letters, and letter sounds. Latency measures were obtained from the naming of regular words, exception words, nonwords and pseudohomophones; as well as button press and verbal lexical decision tasks. Regression analyses supported the hypotheses that RAN-Letters latency reflects SV processing in that its variance is uniquely accounted for by exception word naming latency and button press lexical decision latency, and that RAN-Letter Sounds latency best reflects PD processing in that its variance is uniquely accounted for by pseudohomophone and nonword naming latency. Findings are discussed in light of what the RAN tasks are measuring, implications involving visual word recognition models of reading, and the utility of the new RAN-Letter Sounds task with respect to diagnostic and remediation applications.

Previous functional magnetic resonance imaging (fMRI) studies have investigated the role of phonological processing by utilizing nonword rhyming decision tasks (e.g., Pugh et al., 1996). Although such tasks clearly engage phonological components of visual word recognition, it is clear that decision tasks are more cognitively involved than the simple overt naming tasks, which more closely map onto normal reading behavior. Our research aim for this study was to examine the advantages of overt naming tasks for fMRI studies of word recognition processes. Process models are presented to highlight the similarities and differences between two cognitive tasks that are used in the word recognition literature, pseudohomophone naming (e.g., pronounce BRANE) and rhyming decision (e.g., do LEAT and JEAT rhyme?). An fMRI study identified several differences in cortical activation associated with the differences observed in the process models. Specifically, the results show that the overt naming task involved the insular cortex and inferior frontal gyrus, whereas the rhyming decision task engaged the temporal-parietal regions. It is argued that future fMRI research examining the neuroanatomical components of basic visual word recognition utilize overt naming tasks.

D. C. Plaut and J. R. Booth (2000) presented a parallel distributed processing model that purports to simulate human lexical decision performance. This model (and D. C. Plaut, 1995) offers a single mechanism account of the pattern of factor effects on reaction time (RT) between semantic priming, word frequency, and stimulus quality without requiring a stages-of-processing account of additive effects. Three problems are discussed. First, no evidence is provided that this model can discriminate between words and nonwords with the same orthographic structure and still produce the pattern of factor effects on RT it currently claims to produce. Second, the level of representation used by the model to make a lexical decision is inconsistent with what is known about how skilled readers with damage to their semantic system make word/nonword discriminations. Finally, there are a number of results that are difficult to reconcile with the single mechanism account. The authors' preference is to retain the stages-of-processing account. Keywords: stages-of-processing, parallel distributed processing (PDP), lexical--semantic priming, word frequency, stimulus quality

The number and type of connections involving different levels of orthographic and phonological representations differentiate between several models of spoken and visual word recognition. At the sublexical level of processing, Borowsky, Owen, and Fonos (1999) demonstrated evidence for direct processing connections from grapheme representations to phoneme representations (i.e., a sensitivity effect) over and above any bias effects, but not in the reverse direction. Neural network models of visual word recognition implement an orthography to phonology processing route that involves the same connections for processing sublexical and lexical information, and thus a similar pattern of cross-modal effects for lexical stimuli are expected by models that implement this single type of connection (i.e., orthographic lexical processing should directly affect phonological lexical processing, but not in the reverse direction). Furthermore, several models of spoken word perception predict that there should be no direct connections between orthographic representations and phonological representations, regardless of whether the connections are sublexical or lexical. The present experiments examined these predictions by measuring the influence of a cross-modal word context on word target discrimination. The results provide constraints on the types of connections that can exist between orthographic lexical representations and phonological lexical representations.

Phonological lexical access has been investigated by examining both a pseudohomophone (e.g., brane) base-word frequency effect and a pseudohomophone advantage over pronounceable nonwords (e.g., frane) in a single mixed block of naming trials. With a new set of pseudohomophones and nonwords presented in a mixed block, we replicated the standard finding in the naming literature: no reliable base-word frequency effect, and a pseudohomophone advantage. However, for this and two of three other sets of stimuli---those of McCann and Besner (1987), Seidenberg, Petersen, MacDonald, and Plaut (1996), and Herdman, LeFevre, and Greenham (1996), respective--reliable effects of base-word frequency on pseudohomophone naming latency were found when pseudohomophones were presented in pure blocks prior to nonwords. Three of the four stimulus sets tested produced a pseudohomophone naming disadvantage when pseudohomophones were presented prior to nonwords. When nonwords were presented first, these effects were diminished. A strategy-based scaling account of the data is argued to provide a better explanation of the data than is the criterion-homogenization theory (Lupker, Brown, & Colombo, 1997).