A Cohort Model of Visual Word Recognition

Johnson, Neal F.; Pugh, Kenneth R.

doi:10.1006/cogp.1994.1008

Cited by 93 publications

(154 citation statements)

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“…It is well established, for example, that the frequency with which a word is encountered is inversely correlated with word access times in both lexical decision and naming (e.g., Balota & Spieler, 1999;Coltheart et al, 1993;Ferrand & Grainger, 1996;Gerhand & Barry, 1998;Lukatela, Frost, & Turvey, 1998;Lupker, Brown, & Colombo, 1997;Plaut et al, 1996;Ziegler & Perry, 1998). Similarly, the number of words that share all but a single letter with the target word (orthographic neighborhood size) has been shown to have an impact on word access times (e.g., Johnson & Pugh, 1994;Sears, Hino, & Lupker, 1995Sears, Lupker, & Hino, in press). Even syllable frequency plays a complex role in determining reading speed and accuracy (Perea & Carreiras, 1998).…”

Section: Methodsmentioning

confidence: 99%

“…Wallace and his colleagues have been investigating the claims of cohort theory (e.g., Johnson & Pugh, 1994;Marslen-Wilson, 1984, 1987 in spoken word recognition using the false memory paradigm for a number of years. Wallace et al (1998) investigated the extent to which early (i.e., melancholy → belancholy) versus late (i.e., melancholy → melanchoby) phonemic changes in auditorily presented nonwords would result in later familiarity (as measured by the number of false memories) for unheard items.…”

Section: The Role Of the Headmentioning

confidence: 99%

“…This level of control makes it possible to directly test hypotheses about the structure of the phonological lexicon. The cohort model (Johnson & Pugh, 1994;Marslen-Wilson, 1990) predicts that experience with head-related word sets will prime related words more strongly than will experience with rime-related word sets. Treiman et al's (1995) view that the rime plays a special role in word recognition suggests the opposite prediction.…”

Section: False Memory Experimentsmentioning

confidence: 99%

“…Assumptions about the organizing characteristics and structures of these memory systems are found in various discussions of lexical neighborhoods (Coltheart, Davelaar, Jonasson, & Besner, 1977) or cohorts (Johnson & Pugh, 1994;Marslen-Wilson, 1990). The focus of neighborhood research in visual word recognition has been primarily at the orthographic level.…”

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confidence: 99%

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Sounds of the Neighborhood: False Memories and the Structure of the Phonological Lexicon

Westbury

Buchanan

Brown

2002

Journal of Memory and Language

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Section: Methodsmentioning

confidence: 99%

Section: The Role Of the Headmentioning

confidence: 99%

Section: False Memory Experimentsmentioning

confidence: 99%

mentioning

confidence: 99%

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Sounds of the Neighborhood: False Memories and the Structure of the Phonological Lexicon

Westbury

Buchanan

Brown

2002

Journal of Memory and Language

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“…Both studies more or less directly tested predictions of interactive activation models of word recognition (Grainger and Jacobs, 1996;Jacobs and Grainger, 1992;Johnson and Pugh, 1994;McClelland and Rumelhart, 1981). Thus, while currently available neuroimaging evidence concerning the effects of orthographic neighborhood density does not support predictions of localist connectionist models of word recognition, the evidence from an ERP study does so.…”

Section: Introductionmentioning

confidence: 91%

Model-generated lexical activity predicts graded ERP amplitudes in lexical decision

et al. 2006

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. These studies relate the orthographic neighborhood density of letter strings to the amount of global lexical activity in the brain, generated by a hypothetical mental lexicon as speculated in an early paper by [Jacobs, A.M. and Carr, T.H. (1995). Mind mappers and cognitive modelers: Toward crossfertilization, Behav. Brain. Sci. 18 362-363]. The present study uses model-generated stimuli theoretically eliciting graded global lexical activity and relates this activity to activation of lexical processing networks using event-related potentials (ERPs). The results from a lexical decision task provide evidence for an effect of lexicality around 350 ms post-stimulus and also a graded effect of global lexical activity for nonwords around 500 ms post-stimulus. The data are interpreted as reflecting two different decision processes: an identification process based on local lexical activity underlying the 'yes' response to words and a temporal deadline process underlying the 'no' response to nonwords based on global lexical activity. IntroductionStudies of visual word recognition focusing on lexical access employ a number of variables assumed to influence this process (e.g., word frequency or neighborhood density) in a number of tasks (e.g., lexical or semantic decision, naming, or perceptual identification). One of the most prominent variables is neighborhood density, i.e., the number of orthographic neighbors, which can be generated by changing one letter of a given word, often referred to as the N-metric (Coltheart et al., 1977). When participants make a lexical decision, a standard finding is that responses to words of large neighborhoods (so called high-N words) are faster than to words having small neighborhoods (Andrews, 1989(Andrews, , 1992(Andrews, , 1997; Carreiras et al.,

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Word Processing

Cai

Vigliocco

2018

Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience

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This chapter reviews theories and empirical research on how humans retrieve meaning from speech or text. We first review research concerning how word meanings are represented. Here theories are divided between embodiment accounts proposing that word meanings are grounded in sensorimotor systems, and distributional semantics accounts proposing that meanings can be viewed as inter‐word distributional relations. We argue that these two approaches deal with different aspects of word meanings and should be integrated. For meaning retrieval, we discuss previous research showing that both meaning dominance and prior context determine the access and retrieval of meanings. We also discuss how the selected and unselected meanings may be later suppressed and re‐instantiated. Finally, we propose that prior, concurrent, or subsequent contexts—situated in the framework of inferential/predictive language processing—play different roles in word processing. Prior context constitutes the prior knowledge that sets the stage for word recognition and meaning retrieval, concurrent context constrains the recognition of the word/meaning, and subsequent context updates lexico‐semantic knowledge against recent experience. We propose that future research should investigate words in their natural habitat of contextualized and multimodal language communication.

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A Cohort Model of Visual Word Recognition

Cited by 93 publications

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Sounds of the Neighborhood: False Memories and the Structure of the Phonological Lexicon

Sounds of the Neighborhood: False Memories and the Structure of the Phonological Lexicon

Model-generated lexical activity predicts graded ERP amplitudes in lexical decision

Word Processing

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