We present a theoretical framework and a simplified simulation model for the co-evolution of knowledge and event memory, both termed SARKAE (Storing and Retrieving Knowledge and Events). Knowledge is formed through the accrual of individual events, a process that operates in tandem with the storage of individual event memories. In 2 studies, new…

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…

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…

We present a neural network model of learning and processing the English past tense that is based on the notion that experience-dependent cortical development is a core aspect of cognitive development. During learning the model adds and removes units and connections to develop a task-specific final architecture. The model provides an integrated…

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…

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…

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…

We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to…

Processing language requires the retrieval of concepts from memory in response to an ongoing stream of information. This retrieval is facilitated if one can infer the gist of a sentence, conversation, or document and use that gist to predict related concepts and disambiguate words. This article analyzes the abstract computational problem…

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…

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…

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++…

The importance of phonology in assigning words to the correct grammatical category in language processing is discussed. Correlations between phonology and grammatical class are discussed. Experiments demonstrating that adults and children have learned these correlations are proposed and evaluated. (SLD)