Recent studies of eye movements in reading and other information processing tasks, such as music reading, typing, visual search, and scene perception, are reviewed. The major emphasis of the review is on reading as a specific example of cognitive processing. Basic topics discussed with respect to reading are (a) the characteristics of eye movements, (b) the perceptual span, (c) integration of information across saccades, (d) eye movement control, and (e) individual differences (including dyslexia). Similar topics are discussed with respect to the other tasks examined. The basic theme of the review is that eye movement data reflect moment-to-moment cognitive processes in the various tasks examined. Theoretical and practical considerations concerning the use of eye movement data are also discussed.

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Eye movements in reading and information processing: 20 years of research.

A parallel distributed processing model of visual word recognition and pronunciation is described. The model consists of sets of orthographic and phonological units and an interlevel of hidden units. Weights on connections between units were modified during a training phase using the back-propagation learning algorithm. The model simulates many aspects of human performance, including (a) differences between words in terms of processing difficulty, (b) pronunciation of novel items, (c) differences between readers in terms of word recognition skill, (d) transitions from beginning to skilled reading, and (e) differences in performance on lexical decision and naming tasks. The model's behavior early in the learning phase corresponds to that of children acquiring word recognition skills. Training with a smaller number of hidden units produces output characteristic of many dyslexic readers. Naming is simulated without pronunciation rules, and lexical decisions are simulated without accessing word-level representations. The performance of the model is largely determined by three factors: the nature of the input, a significant fragment of written English; the learning rule, which encodes the implicit structure of the orthography in the weights on connections; and the architecture of the system, which influences the scope of what can be learned.

A Distributed, Developmental Model of Word Recognition and Naming.

This article presents a theory in which automatization is construed as the acquisition of a domainspeciSc knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur only after practice in a consistent environment. Practice is important because it increases the amount retrieved and the speed of retrieval; consistency is important because it ensures that the retrieved instances will be useful. The theory accounts quantitatively for the power-function speed-up and predicts a power-function reduction in the standard deviation that is constrained to have the same exponent as the power function for the speed-up. The theory accounts for qualitative properties as well, explaining how some may disappear and others appear with practice. More generally, it provides an alternative to the modal view of automaticity, arguing that novice performance is limited by a lack of knowledge rather than a scarcity of resources. The focus on learning avoids many problems with the modal view that stem from its focus on resource limitations.

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Toward an instance theory of automatization

The English Lexicon Project is a multiuniversity effort to provide a standardized behavioral and descriptive data set for 40,481 words and 40,481 nonwords. It is available via the Internet at elexicon.wustl.edu. Data from 816 participants across six universities were collected in a lexical decision task (approximately 3400 responses per participant), and data from 444 participants were collected in a speeded naming task (approximately 2500 responses per participant). The present paper describes the motivation for this project, the methods used to collect the data, and the search engine that affords access to the behavioral measures and descriptive lexical statistics for these stimuli.

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The English Lexicon Project.

Word frequency is the most important variable in research on word processing and memory. Yet, the main criterion for selecting word frequency norms has been the availability of the measure, rather than its quality. As a result, much research is still based on the old Kucera and Francis frequency norms. By using the lexical decision times of recently published megastudies, we show how bad this measure is and what must be done to improve it. In particular, we investigated the size of the corpus, the language register on which the corpus is based, and the definition of the frequency measure. We observed that corpus size is of practical importance for small sizes (depending on the frequency of the word), but not for sizes above 16–30 million words. As for the language register, we found that frequencies based on television and film subtitles are better than frequencies based on written sources, certainly for the monosyllabic and bisyllabic words used in psycholinguistic research. Finally, we found that lemma frequencies are not superior to word form frequencies in English and that a measure of contextual diversity is better than a measure based on raw frequency of occurrence. Part of the superiority of the latter is due to the words that are frequently used as names. Assembling a new frequency norm on the basis of these considerations turned out to predict word processing times much better than did the existing norms (including Kucera & Francis and Celex). The new SUBTL frequency norms from the SUBTLEXUS corpus are freely available for research purposes from http://brm.psychonomic-journals.org/content/supplemental, as well as from the University of Ghent and Lexique Web sites.

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Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English

Three experiments investigated the impact of five lexical variables (instance dominance, category dominance, word frequency, word length in letters, and word length in syllables) on performance in three different tasks involving word recognition: category verification, lexical decision, and pronunciation. Although the same set of words was used in each task, the relationship of the lexical variables to reaction time varied significantly with the task within which the words were embedded. In particular, the effect of word frequency was minimal in the category verification task, whereas it was significantly larger in the pronunciation task and significantly larger yet in the lexical decision task. It is argued that decision processes having little to do with lexical access accentuate the word-frequency effect in the lexical decision task and that results from this task have questionable value in testing the assumption that word frequency orders the lexicon, thereby affecting time to access the mental lexicon. A simple two-stage model is outlined to account for the role of word frequency and other variables in lexical decision. The model is applied to the results of the reported experiments and some of the most important findings in other studies of lexical decision and pronunciation.

Are lexical decisions a good measure of lexical access? The role of word frequency in the neglected decision stage.

The locus of word-frequency effects in the pronunciation task: Lexical access and/or production? ☆

Performance on three different tasks was compared: naming, lexical decision, and reading (with eye fixation times on a target word measured). We examined the word frequency effect for a common set of words for each task and each subject. Naming and reading (particularly gaze duration) yielded similar frequency effects for the target words. The frequency effect found in lexical decision was greater than that found in naming and in eye fixation times. In all tasks, there was a correlation between the frequency effect and average response time. In general, the results suggest that both the naming and the lexical decision tasks yield data about word recognition processes that are consistent with effects found in eye fixations during silent reading.

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Comparing naming, lexical decision, and eye fixation times: Word frequency effects and individual differences

The influence of an isolated word’s meaning on lexical decision reaction time (RT) was demonstrated through four experiments. Subjects in two experiments made lexical decision judgments, those in a third experiment pronounced the words used in the lexical decision task, and those in a fourth experiment quickly pronounced their first associative response to the words. Differences in lexical access time for the words were measured with the pronunciation task, and differences in meaning were assessed with the association task. Multiple regression analyses of lexical decision RT were conducted using associative RT, pronunciation RT, and other target word properties (printed frequency, length, instance dominance, and number of dictionary meanings) as predictor variables. These analyses revealed a relationship between lexical decision RT and associative RT after the effects of other variables had been partialed out. In addition, word frequency continued to have a significant relationship to lexical decision RT beyond that shared with pronunciation RT and the other variables. The results of these experiments indicate that at least some of the effect of word meaning and word frequency in lexical decision is attributable to a decision stage following lexical access.

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A word’s meaning affects the decision in lexical decision

Balota and Chumbley's studies led them to conclude that category verification, lexical decision, and pronunciation tasks involve combinations of processes that cause them to produce differing estimates of the relation between word frequency and ease of lexical identification. Monsell, Doyle, and Haggard challenged Balota and Chumbley's empirical evidence and conclusions, provided empirical evidence to support their challenge, and presented an alternative theoretical position. We show that Monsell et al.'s experiments, analyses, and theoretical perspective do not result in conclusions about the role of word frequency in category verification, lexical decision, and pronunciation that differ from those of Balota and Chumbley.

James I. Chumbley

Papers

Are lexical decisions a good measure of lexical access? The role of word frequency in the neglected decision stage.

The locus of word-frequency effects in the pronunciation task: Lexical access and/or production? ☆

Comparing naming, lexical decision, and eye fixation times: Word frequency effects and individual differences

A word’s meaning affects the decision in lexical decision

Where are the effects of frequency in visual word recognition tasks? Right where we said they were! Comment on Monsell, Doyle, and Haggard (1989).