Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific serial positions or specific local contexts (e.g., letter clusters). The spatial coding model described here adopts a different approach to letter position coding and lexical matching based on context-independent letter representations. In this model, letter position is coded dynamically, with a scheme called spatial coding. Lexical matching is achieved via a method called superposition matching, in which input codes and learned codes are matched on the basis of the relative positions of their common letters. Simulations of the model illustrate its ability to explain a broad range of results from the masked form priming literature, as well as to capture benchmark findings from the unprimed lexical decision task.

Predictions derived from the interactive activation (IA) model were tested in 3 experiments using the masked priming technique in the lexical decision task. Experiment 1 showed a strong effect of prime lexicality: Classifications of target words were facilitated by orthographically related nonword primes (relative to unrelated nonword primes) but were inhibited by orthographically related word primes (relative to unrelated word primes). Experiment 2 confirmed IA's prediction that inhibitory priming effects are greater when the prime and target share a neighbor. Experiment 3 showed a minimal effect of target word neighborhood size (N) on inhibitory priming but a trend toward greater inhibition when nonword foils were high-N than when they were low-N. Simulations of 3 different versions of the IA model showed that the best fit to the data is produced when lexical inhibition is selective and when masking leads to reset of letter activities.

This article describes a Windows program that enables users to obtain a broad range of statistics concerning the properties of word and nonword stimuli, including measures of word frequency, orthographic similarity, orthographic and phonological structure, age of acquisition, and imageability. It is designed for use by researchers in psycholinguistics, particularly those concerned with recognition of isolated words. The program computes measures of orthographic similarity on line, either with respect to a default vocabulary of 30,605 words or to a vocabulary specified by the user. In addition to providing standard orthographic neighborhood measures, the program can be used to obtain information about other forms of orthographic similarity, such as transposed-letter similarity and embedded-word similarity. It is available, free of charge, from the following Web site: http://www.maccs.mq. edu.au/colin/N-Watch/.

This article describes a Windows program that enables users to obtain a broad range of statistics concerning the properties of word and nonword stimuli in Spanish, including word frequency, syllable frequency, bigram and biphone frequency, orthographic similarity, orthographic and phonological structure, concreteness, familiarity, imageability, valence, arousal, and age-of-acquisition measures. It is designed for use by researchers in psycholinguistics, particularly those concerned with recognition of isolated words. The program computes measures of orthographic similarity online, with respect to either a default vocabulary of 31,491 Spanish words or a vocabulary specified by the user. In addition to providing standard orthographic and phonological neighborhood measures, the program can be used to obtain information about other forms of orthographic similarity, such as transposed-letter similarity and embedded-word similarity. It is available, free of charge, from the following Web site: www.maccs.mq.edu.au/~colin/B-Pal.

According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account for the data that are obtained, making the models unfalsifiable. It further relates to the fact that Bayesian theories are rarely better at predicting data compared with alternative (and simpler) non-Bayesian theories. Second, we show that the empirical evidence for Bayesian theories in neuroscience is weaker still. There are impressive mathematical analyses showing how populations of neurons could compute in a Bayesian manner but little or no evidence that they do. Third, we challenge the general scientific approach that characterizes Bayesian theorizing in cognitive science. A common premise is that theories in psychology should largely be constrained by a rational analysis of what the mind ought to do. We question this claim and argue that many of the important constraints come from biological, evolutionary, and processing (algorithmic) considerations that have no adaptive relevance to the problem per se. In our view, these factors have contributed to the development of many Bayesian "just so" stories in psychology and neuroscience; that is, mathematical analyses of cognition that can be used to explain almost any behavior as optimal.

Ratings of age of acquisition (AoA), imageability, and familiarity were collected for 1,526 words. The methodology made use of a modular approach, in which the full sample of words was divided into five separate blocks. Within each block, each word was rated on each of the three variables by 20 participants (undergraduate students from the University of Bristol). Analyses comparing these ratings to existing norm databases demonstrated that this methodology resulted in high reliability (assessed by Cronbach's ) and validity. The ratings were also transformed to be compatible with the Gilhooly and Logie (1980) norms. This transformation resulted in a set of norms for 3,394 words, which is by far the largest database of ratings for AoA, imageability, and familiarity to date. The resulting database should be useful for researchers interested in manipulating or controlling these factors in word recognition, neuropsychological, or memory studies. These norms can be downloaded from language.psy.bris .ac.uk/bristol_norms.html.

An orthographically similar masked nonword prime facilitates responding in a lexical decision task (Forster & Davis, 1984). Recently, this masked priming paradigm has been used to evaluate models of orthographic coding--odels that attempt to quantify prime-target similarity. One general finding is that priming effects often do not occur when prime-target similarity is moderate, a result that the authors interpret as being due to uncontrolled effects of lexical inhibition. In the present research, a new version of the masked priming paradigm, sandwich priming, was introduced in an effort to minimize the impact of lexical inhibition. Masked sandwich priming involves briefly presenting the target itself prior to the presentation of each prime. Results indicate that the new paradigm was successful. The predicted priming effects were observed for Guerrera and Forster's (2008) T-All primes (e.g., avacitno-VACATION) and for primes differing from their targets at 3 letter positions (e.g., coshure-CAPTURE)-effects that are not found with the conventional masked priming paradigm. In addition to demonstrating the usefulness of the sandwich priming technique, these results also support the assumption that inhibitory processes play an important role in lexical processing.

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