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target="_blank" rel="nofollow" href="#ulink_379dd456-964b-5ab0-aaa7-bdd0d489d93e">Table 1.1 Properties and functions of phonology during word identification

Properties Functions
Automatic or Routine Not easily suppressed Helps stabilize word identity Stable identity supports memory and comprehension
Universal or Highly General Observed in all writing systems
Sublexical as well as Lexical Sublexical processes depend on writing system
Rich Content From low level (articulatory features) to supra‐segmental (syllabic stress)

       What have we learned about word reading from neuroimaging?

      We conclude our review of word reading with a few highlights of what neuroimaging research has added to understanding in this area (see Yeatman, this volume, for comprehensive review).

      Two landmark papers in 1988 reported positron emission tomographic (PET) studies in Science (Posner et al., 1988) and Nature (Petersen et al., 1988). From a vantage point years later, the results seem modest. Petersen et al. (1988) concluded the results “favor the idea of separate brain areas…(for) separate visual and auditory coding of words, each with independent access to supramodal articulatory and semantic systems” (p. 585). More interesting for models of word identification was their conclusion that the results argued against “obligatory visual‐to‐auditory recoding.” If we understand “auditory” as phonological, this conclusion was at odds with the behavioral data just starting to emerge around that time.

      Later research with fMRI confirmed the role of visual left posterior areas while modifying the earlier conclusion about phonology. The identification of brain networks that connect visual areas to phonological and meaning areas has been a major achievement of cognitive neuroscience. Studies found that increases in reading skill are associated with increased activation in left‐hemisphere areas in both temporal and frontal brain areas (Turkeltaub et al., 2003) and identified the left posterior (occipital‐temporal) region as the site of orthographic processing or the visual word form area (Cohen et al., 2000; McCandliss et al., 2003). Additional areas in the temporal, parietal, and frontal lobes support meaning, memory, and attentional functions. It is the interconnections among specific areas that comprise the multiple subcircuits that make up the larger reading network, as synthesized by Dehaene (2009).

      An important question is how this reading network develops. A general answer is that the basic areas – the posterior visual areas and the left hemisphere language areas – get connected through experience in reading. Additionally, built‐in potentials may support this development. Saygin et al. (2016) found that the connectivity pattern within left hemisphere visual areas observed in individual children at age 8 could be predicted by connectivity “fingerprints” that were observed, but not functional at age 5, prior to reading instruction.

      Does identifying the brain’s reading network add something to models of word identification and the behavioral data supporting them? Other than required connections between visual and language areas, there is little to constrain the neural implementation of reading processes. Additionally, results from imaging do not automatically align with behavioral results. For example, finding a brain area in an fMRI study that responds more to words than pseudowords reflects the cumulative effects of processing that extends over time intervals that greatly exceed the time course of the processes involved in word identification (though note that MEG can expose these short intervals). However, brain‐behavior model comparisons and theoretical syntheses are helpful, as Taylor et al. (2013) demonstrated. They concluded that both the DRC (Coltheart et al., 2001) and the Triangle PDP model (Plaut et al., 1996) could predict activation patterns during word and pseudoword reading. In fact, all components of the finer‐grain DRC model could be observed in brain data.

       Disruptions in the word‐identification system.

Schematic illustration of the word-identification system of the Reading Systems Framework.

      The link between skilled and disrupted word identification processes is made explicit in dual‐route models, which postulate selective disruption to either the direct (lexical) route or the indirect (sublexical) route to word identity. Castles and Coltheart (1993) established the existence of each type of disruption by testing children’s performance on both irregular, exception words (requiring the lexical route) and pseudowords (requiring the sublexical route). Although a problem with both kinds of words was most common, disassociations between exception word and pseudoword performance appeared for some children. Most showed a phonological dyslexia profile (more difficulty with pseudowords), while others showed a surface dyslexia pattern (more difficulty with exception words). In the Reading Systems Framework, the surface dyslexic is impaired in visual‐orthographic memory, whereas the phonological dyslexic is impaired in the linkage between sublexical orthographic strings and pronunciations.

      These two different manifestations of disruption to the word reading system might, however, arise from a single problem in the phonological system. Difficulty reading exception words might be recast not as surface dyslexia but as due to a developmental delay (Manis et al., 1996) – that is, reading experience that is insufficient to acquire high‐quality word representations of exceptionally spelled words. A connectionist model by Seidenberg and McClelland (1989) showed the plausibility of a key assumption: A serious problem in phonological representations can lead to a “deficit” in reading exception words. Other studies – a review by Rack et al. (1992), a critique of visual deficit hypotheses (Vellutino, 1981), demonstrations of

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