Nonreading tasks that share some (but not all) of the task demands of reading have often been used to make inferences about how cognition influences when the eyes move during reading. In this article, we use variants of the E-Z Reader model of eye-movement control in reading to simulate eye-movement behavior in several of these tasks, including…

Reading is a highly complex task involving a precise integration of vision, attention, saccadic eye movements, and high-level language processing. Although there is a long history of psychological research in reading, it is only recently that imaging studies have identified some neural correlates of reading. Thus, the underlying neural mechanisms…

The authors present a computational model that builds a holographic lexicon representing both word meaning and word order from unsupervised experience with natural language. The model uses simple convolution and superposition mechanisms to learn distributed holographic representations for words. The structure of the resulting lexicon can account…

What is the root cause of word frequency effects on lexical decision times? W. S. Murray and K. I. Forster (2004) argued that such effects are linear in rank frequency, consistent with a serial search model of lexical access. In this article, the authors (a) describe a method of testing models of such effects that takes into account the…

B. Rapp and M. Goldrick (2000) claimed that the lexical and mixed error biases in picture naming by aphasic and nonaphasic speakers argue against models that assume a feedforward-only relationship between lexical items and their sounds in spoken word production. The author contests this claim by showing that a feedforward-only model like WEAVER++…

Real-time language comprehension is a principal cognitive ability and thereby relates to central properties of the human cognitive architecture. Yet how do the presumably universal cognitive and neural substrates of language processing relate to the astounding diversity of human languages (over 5,000)? The authors present a neurocognitive model of…

A processing model is presented that deals explicitly with both the text-comprehension and problem-solving aspects of word arithmetic problems. The model simulates construction of cognitive representations at various levels, distinguishes several information processing steps, and analyzes processing requirements that differ among types of…

A simulation model of episodic memory, MINERVA Z, is applied to the learning of concepts, as represented by the schema-abstraction task. The model successfully predicts basic findings from the scheme-abstraction literature, including some that have been cited as evidence against exemplary theories of concepts. (Author/LMO)

A model of information processing has been developed that combines concepts from the study of attention and the study of problem solving. The model has been realized as a computer program and used to simulate a variety of phenomena from the attention and performance literature. (Author/LMO)

Plaut and Booth developed a distributed connectionist model of written word comprehension and evaluated it against empirical findings on individual and developmental differences in semantic priming in visual lexical decision. Borowsky and Besner raised a number of challenges for this model. First, the model was not shown to be capable of…

D. C. Plaut and J. R. Booth presented a parallel distributed processing model that purports to simulate human lexical decision performance. This model (and D. C. Plaut, 1995) offers a single mechanism account of the pattern of factor effects on reaction time (RT) between semantic priming, word frequency, and stimulus quality without requiring a…