A theory of the way working memory capacity constrains comprehension is proposed. The theory proposes that both processing and storage are mediated by activation and that the total amount of activation available in working memory varies among individuals. Individual differences in working memory capacity for language can account for qualitative and quantitative differences among college-age adults in several aspects of language comprehension. One aspect is syntactic modularity: The larger capacity of some individuals permits interaction among syntactic and pragmatic information, so that their syntactic processes are not informationally encapsulated. Another aspect is syntactic ambiguity: The larger capacity of some individuals permits them to maintain multiple interpretations. The theory is instantiated as a production system model in which the amount of activation available to the model affects how it adapts to the transient computational and storage demands that occur in comprehension.Working memory plays a central role in all forms of complex thinking, such as reasoning, problem solving, and language comprehension. However, its function in language comprehension is especially evident because comprehension entails processing a sequence of symbols that is produced and perceived over time. Working memory plays a critical role in storing the intermediate and final products of a reader's or listener's computations as she or he constructs and integrates ideas from the stream of successive words in a text or spoken discourse. In addition to its role in storage, working memory can also be viewed as the pool of operational resources that perform the symbolic computations and thereby generate the intermediate and final products. In this article, we examine how the human cognitive capacity accommodates or fails to accommodate the transient computational and storage demands that occur in language comprehension. We also explain the differences among individuals in their comprehension performance in terms of their working memory capacity. The major thesis is that cognitive capacity constrains comprehension, and it constrains comprehension more for some people than for others.This article begins with a general outline of a capacity theory of language comprehension. In the second section we use the capacity theory to account for several phenomena relating individual differences in language processing to working memory
This article presents a model of reading comprehension that accounts for the allocation of eye fixations of college students reading scientific passages. The model deals with processing at the level of words, clauses, and text units. Readers make longer pauses at points where processing loads are greater. Greater loads occur while readers are accessing infrequent words, integrating information from important clauses, and making inferences at the ends of sentences. The model accounts forthe gaze duration on each word of text as a function of the involvement of the various levels of processing. The model is embedded in a theoretical framework capable of accommodating the flexibility of reading.Although readers go through many of the same processes as listeners, there is one striking difference between reading and listening comprehension-a reader can control the rate of input. Unlike a listener, a reader can skip over portions of the text, reread sections, or pause on a particular word. A reader can take in information at a pace that matches the internal comprehension processes. By examining where a reader pauses, it is possible to learn about the comprehension processes themselves. Using this approach, a process model of reading comprehension is developed that accounts for the gaze durations of college students reading scientific passages.
The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.
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