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An activation-verification model for letter and word recognition yielded predictions of two-alternative forced-choice performance for 864 individual stimuli that were either words, orthographically regular nonwords, or orthographically irregular nonwords. The encoding algorithm (programmed in APL) uses empirically determined confusion matrices to activate units in both an alphabetum and a lexicon. In general, predicted performance is enhanced when decisions are based on lexical information, because activity in the lexicon tends to constrain the identity of test letters more than the activity in the alphabetum. Thus, the model predicts large advantages of words over irregular nonwords, and smaller advantages of words over regular nonwords. The predicted differences are close to those obtained in a number of experiments and clearly demonstrate that the effects of manipulating lexicality and orthography can be predicted on the basis of lexical constraint alone. Furthermore, within each class (word, regular nonword, irregular nonword) there are significant correlations between the simulated and obtained performance on individual items. Our activation-verification model is contrasted with McClelland and Rumelhart's (1981) interactive activation model.

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The assumptions of the activation-verification model regarding the role of word frequency in lexical access were investigated in 2 experiments. Experiment 1 demonstrated that robust frequency effects occur in a standard lexical decision task in which the target remains in view until the subject responds. In Experiment 2 the same materials were followed by a backward pattern mask. Subjects first identified 1 of the 4 letters using a forced-choice task (G. M. Reicher, 1969) and were then probed to make a lexical decision. No frequency effects were observed in the lexical decision task and the significant main effect of frequency found in the subject's analysis of the Reicher task was small and nonmonotonic. A regression analysis on the word data obtained in Experiment 1 indicated that the number of higher frequency neighbors produced a potent interference effect, that the total number of neighbors produced a smaller but significant facilitation effect, and that neither word frequency nor summed bigram frequency accounted for any significant variation once the effects of higher frequency neighbors were partialed out. Regression analyses of other published data showed a similar pattern of results.The idea that verification plays an important role in pattern recognition has now had a fairly long ran (Becker,

A sample of 58 bilingual and 62 monolingual university students completed four tasks commonly used to test for bilingual advantages in executive functioning (EF): antisaccade, attentional network test, Simon, and color-shape switching. Across the four tasks, 13 different indices were derived that are assumed to reflect individual differences in inhibitory control, monitoring, or switching. The effects of bilingualism on the 13 measures were explored by directly comparing the means of the two language groups and through regression analyses using a continuous measure of bilingualism and multiple demographic characteristics as predictors. Across the 13 different measures and two types of data analysis there were very few significant results and those that did occur supported a monolingual advantage. An equally important goal was to assess the convergent validity through cross-task correlations of indices assume to measure the same component of executive functioning. Most of the correlations using difference-score measures were non-significant and many near zero. Although modestly higher levels of convergent validity are sometimes reported, a review of the existing literature suggests that bilingual advantages (or disadvantages) may reflect task-specific differences that are unlikely to generalize to important general differences in EF. Finally, as cautioned by Salthouse, assumed measures of executive functioning may also be threatened by a lack of discriminant validity that separates individual or group differences in EF from those in general fluid intelligence or simple processing speed.

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