Overlap model - Gomez, Ratcliff & Perea (in press) in Psychological Review

In this paper, the authors introduce the Overlap Model of letter-position encoding, which is essentially a sloppy slot-based model. For example, an L in the third position would activate an encoding for L in the third position, as well L in the second and fourth positions, to a lesser degree. The authors present a series of experiments to determine parameter settings for the model, which govern the amount of spread for each letter position. In the experiments, a five-letter string was presented for 60ms, followed by a mask and 2AFC. The choices were strings, and the way in which the distractor differed from the target was systematically varied. Note also, that the choices were presented well below where the string occurred, so they did not act as an additional backward mask.

From my point of view, the most interesting aspect of this paper is the finding that the final letter was the least well recognized and localized. In contrast, at longer exposures (>= 100 ms), the usual final-letter advantage can be observed. This contrast is consistent with serial processing and the resulting account of the final-letter advantage, and is difficult to explain otherwise.

However, as a model of letter-position encoding, the Overlap Model faces some difficulties.

1. It is not a full model, as it does not explain how the positions are computed. How is the retinotopic representation transformed into a string-centered positional representation?
2. It cannot explain the finding that, for nine-letter words, the prime 6789 provides facilitation (Grainger et al., 2006 in JEP:HPP). Even with a sloppy position encoding, there would be too much difference between the letter's positions in the prime and target to provide any overlap. Nor could the model be modified to include a position encoding anchored at the final letter; their experiments do not support the existence of such an encoding, as the final letter was the least well anchored/localized (in contrast to the initial letter, which was the best anchored/localized).
   

Burgund & Edwards (2008) in Neuroreport

In this fMRI study of letter priming in the VWFA, the authors compared same-identity and different-identity primes that both had moderate visual similarity to the target. They found no advantage for the same-identity primes, and concluded that the VWFA does not employ abstract letter representations.

However, the task that the subjects performed was based on a visual attribute - whether the letter had an enclosed space. It is perhaps not surprising then that priming was determined by the visual similarity between the prime and the target. It is quite possible that a task based on letter identity would show a different pattern of results.

Also, there is some evidence (e.g., studies by Gauthier and colleagues) that single letters are processed differently than strings. So studies using single-letter tasks may not tap into the abstract letter representations used for string processing.

Guerrera & Forster (2008) in LC&P

The authors investigated priming of eight-letter targets in lexical decision, where the primes employed "extreme transposition". This article includes match scores from the SERIOL model. Again, these scores are based on the original (position-specific) formula for bigram activation, rather than the current assumption that bigram activations depend only on the separation of the constituent letters. Also, the article incorrectly states that the original specification of the SERIOL model placed no limit on the number of intervening letters allowed for bigram activation, whereas this limit has always been two letters.

So here are the match scores under the current parameters, where bigram activation is 1.0 for contiguous letters, 0.8 for a one-letter separation, and 0.4 for a two-letter separation (and 0.0 otherwise).

Note that these numbers are quite different than the published ones for Experiment 3 (in particular) and provide a better fit to those data.

Because bigram activations are no longer positional, the third and fourth primes above now give equivalent match scores. However, simulations give an advantage for matching initial versus final letters due to seriality, as discussed in Whitney (in press).

SOLAR Model - Davis & Bowers (2006) in JEP:HPP

For five-letter targets in lexical decision, the authors compare primes of the form 1d345 vs. 13d45. The SOLAR model predicts stronger priming for 1d345. In the original specification of the SERIOL model, open-bigram activation decreased with increasing string position. Under this assumption, the SERIOL model predicts stronger priming for 13d45. Davis and Bowers found stronger priming for 1d345 than 13d45, and concluded that the SERIOL model is inconsistent with their experimental results.

However, the conclusions of Davis and Bowers (2006) are based on an obsolete parameterization of the SERIOL model. In my 2004 dissertation, the assumption that bigram activation depends on string position was dropped; bigram activations now depend only on the separation between the constituent letters. As a result, the SERIOL model, like the SOLAR model, predicts stronger priming for 1d345 than 13d45. Thus the priming results do not actually differentiate between the two models. (For a discussion of why the positional variation was originally included, why it was dropped, and how the model now accounts for the phenomenon originally explained by the positional variation, see Whitney (in press, LC&P) ).

Despite the fact that a primary focus of Davis and Bowers (2006) was to compare the SERIOL and SOLAR models, JEP:HPP did not invite me to review their article. Hence, their article includes claims that are no longer accurate. (It also includes a claim that is outright incorrect - that even if the positional variation were dropped, the SERIOL model would still be inconsistent with their results.) Nor would JEP:HPP allow me to publish a reply. Fortunately, I found a fairer venue, and my reply to Davis and Bowers (2006) is now in press at Brain and Language.

Briefly, the main points of the response are:

• The SERIOL model is consistent with the results of Davis & Bowers (2006).
• SOLAR's lexical activation function is not biologically plausible.
• A recent re-parameterization of the SOLAR model leads a contradiction of Davis and Bower's core claim that contiguity matters.
• Experimental comparisons between models should test inherent aspects of the models and not depend on particular parameterizations.
• A critical comparison is presented. That is, I specify a pair of primes for which the two models inherently make different predictions. (Colin Davis agrees with this analysis.)