One of the core principles of how the mind works is the graded, parallel activation of multiple related or similar representations. Parallel activation of multiple representations has been particularly important in the development of theories and models of language processing, where coactivated representations ("neighbors") have been shown to…

A 2-layer symbolic network model based on the equilibrium equations of the Rescorla-Wagner model (Danks, 2003) is proposed. The study first presents 2 experiments in Serbian, which reveal for sentential reading the inflectional paradigmatic effects previously observed by Milin, Filipovic Durdevic, and Moscoso del Prado Martin (2009) for unprimed…

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…

R. Ratcliff, P. Gomez, and G. McKoon (2004) suggested much of what goes on in lexical decision is attributable to decision processes and may not be particularly informative about word recognition. They proposed that lexical decision should be characterized by a decision process, taking the form of a drift-diffusion model (R. Ratcliff, 1978), that…

The diffusion model for 2-choice decisions (R. Ratcliff, 1978) was applied to data from lexical decision experiments in which word frequency, proportion of high- versus low-frequency words, and type of nonword were manipulated. The model gave a good account of all of the dependent variables--accuracy, correct and error response times, and their…

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…

Data and models about recognition and recall of words and nonwords are unified using a real-time network processing theory. Adaptive resonance theory arose from an analysis of how a language system self-organizes in real time in response to its complex input environment. (Author/LMO)