Masked phonological priming effects in English - Center for Reading ...
Masked phonological priming effects in English - Center for Reading ...
Masked phonological priming effects in English - Center for Reading ...
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
128 K. Rastle, M. Brysbaert / Cognitive Psychology 53 (2006) 97–145cost <strong>in</strong> terms of total orthographic activation, however, a cost which would have to be taken<strong>in</strong>to account <strong>in</strong> the re<strong>for</strong>mulation of any lexical decision rule.Further analyses of the DRC model under this parameterization reveal another veryserious cost: These alterations to the model leave it unable to read aloud exception words.The DRC model used <strong>in</strong> Simulation 5 was presented with the 88 exception words and the88 matched regular words developed by Rastle and Coltheart (1999) <strong>for</strong> read<strong>in</strong>g aloud.Though the model read aloud 85/88 regular words correctly, it read aloud 0/88 exceptionwords correctly. These errors comprised regularizations (69/88; e.g., ‘books’fi/buks/), lexicalizations(3/88; e.g., ‘tsar’fi/tai/), and other k<strong>in</strong>ds of error (16/88; e.g., ‘aft’fi/ææt/).Given the massive contribution of assembled phonology required to simulate fast <strong>phonological</strong><strong>prim<strong>in</strong>g</strong> <strong>effects</strong> on lexical decision, it is not surpris<strong>in</strong>g that exception words posesuch difficulty <strong>for</strong> the DRC model under this parameterization.6.7. Simulation 6These simulations leave us <strong>in</strong> a difficult position. On the one hand, the DRC modeloperat<strong>in</strong>g under the standard set of parameters <strong>for</strong> lexical decision (Simulation 1) doesnot come close to simulat<strong>in</strong>g fast <strong>phonological</strong> <strong>prim<strong>in</strong>g</strong> <strong>effects</strong>. On the other hand, theDRC parameterization that shows some scope <strong>for</strong> simulat<strong>in</strong>g fast <strong>phonological</strong> <strong>prim<strong>in</strong>g</strong><strong>effects</strong> on lexical decision (Simulation 5) cannot correctly read aloud exception words. Ifour evaluation of the DRC model requires that it simulate fast <strong>phonological</strong> <strong>prim<strong>in</strong>g</strong><strong>effects</strong> on lexical decision us<strong>in</strong>g a set of parameters that can also read aloud, then the modelseems almost certa<strong>in</strong>ly false. An alternative approach would be to justify us<strong>in</strong>g theparameters developed <strong>in</strong> Simulation 5 <strong>for</strong> lexical decision while adopt<strong>in</strong>g the standardset of parameters (Coltheart et al., 2001; Rastle & Coltheart, 1999) <strong>for</strong> read<strong>in</strong>g aloud.Indeed, Coltheart et al. (2001) used a parameter set <strong>for</strong> simulat<strong>in</strong>g lexical decision that differedvery slightly (on a s<strong>in</strong>gle parameter) from that used <strong>for</strong> read<strong>in</strong>g aloud—justify<strong>in</strong>g thissmall parameter change as a strategic response to the specific demands posed by the lexicaldecision task.In Simulation 6, we <strong>in</strong>vestigated quantitatively whether we could offer a specific justification<strong>for</strong> adopt<strong>in</strong>g the parameter set used <strong>in</strong> Simulation 5 <strong>for</strong> lexical decision. Our logicwas simple. We reasoned that the lexical decision task requires readers to discrim<strong>in</strong>atebetween word and nonword stimuli. As such, any strategic variation <strong>in</strong> the parametersused <strong>for</strong> lexical decision should maximize—not m<strong>in</strong>imize—the model’s ability to per<strong>for</strong>mthis discrim<strong>in</strong>ation. If the parameters used <strong>in</strong> Simulation 5 are to be justified <strong>in</strong> terms of astrategic variation due to the demands posed by the lexical decision task, then words andnonwords should produce a larger difference <strong>in</strong> the sources of activation used to make alexical decision when the model is controlled by the parameters used <strong>in</strong> Simulation 5 thanwhen it is controlled by the standard parameters <strong>for</strong> read<strong>in</strong>g aloud (Coltheart et al., 2001;Rastle & Coltheart, 1999). We there<strong>for</strong>e presented two parameterizations of the DRCmodel with the 112 word targets and the 112 nonword targets used <strong>in</strong> Experiment 1,and monitored the two sources of activation currently used to make a lexical decision(i.e., the total activation of the orthographic lexicon and the maximum activation ofany s<strong>in</strong>gle unit; see Coltheart et al., 2001) <strong>for</strong> a 100 cycle period with<strong>in</strong> each parameterization.If the parameters developed <strong>in</strong> Simulation 5 are to be justified <strong>for</strong> use <strong>in</strong> lexicaldecision on strategic grounds, then they should work to maximize the model’s ability todiscrim<strong>in</strong>ate between words and nonwords.