Following Whitney's and Grainger's proposal that the highest pre-lexical orthographic encoding on the lexical (ventral) route is comprised of non-contiguous bigrams (dubbed open-bigrams by Grainger), Dehaene and company got into the act with their Local Combination Detector (LCD) model. While the model is somewhat vague, they do make two specific claims:
- Open-bigram representations do not provide sufficient accuracy in encoding letter order. Therefore, the highest level of the LCD model includes quadrigram detectors to provide a more precise encoding of letter order.
- Open-bigram-like representations occur as a result of retinotopic bigram detectors operating over noisy retinotopic representations of individual letters.
Claim (1) has some problematic aspects:
- The model does not include a location-invariant encoding, as the quadigram detectors are retinotopic.
- Quadrigrams do not provide a realistic similarity metric. For example, LAME and LIME would activate different quadrigrams, making them completely different from each other at the lexical level.
- The authors only considered on/off open-bigrams with no encoding of edges. The addition of graded activations and edge bigrams, as in the SERIOL model, allows more accurate encoding of order information.
- However, there is evidence that letter-order encoding on the ventral route is indeed somewhat imprecise, whereas the encoding is more accurate on the dorsal phonological route. Occipito-parietal lesions lead to a selective deficit in encoding letter order (Friedmann & Gvion, 2001; Shalev, Mevorach & Humphryes, in press) . See also Frankish & Turner (2007) . So experimental results indicate that open-bigrams do not need to be "fixed" with quadrigrams.
In contrast, claim (2) above offers a reasonable account of how open-bigrams could be activated within a parallel framework. Grainger et al. (2006) incorporated this suggestion into their Overlap Open-Bigram (OOB) model. Within the abstract open-bigram layer, the OOB model is quite similar to the SERIOL model, in that it employs open-bigrams with graded activation levels. The only difference is that the OOB model includes activation of transpositions (e.g., BIRD would activate bigram RI to a low level). Of course, the two models radically differ on how the open-bigrams become activated, as the SERIOL model proposes that open-bigrams are activated serially. This serial mechanism explains perceptual patterns for consonant strings, while parallel accounts do not. For a detailed comparison of serial versus parallel activation of open-bigrams, see Whitney & Cornelissen (2008).