A diffusion model account of normal and impaired readers

Ratcliff, Roger; Perea, Manuel; Colangelo, Annette; Buchanan, Lori

doi:10.1016/j.bandc.2004.02.051

“…Diffusion model analyses show that this comes about because they set more conservative criteria and have longer nondecision times (Ratcliff, Perea, et al, 2004). The differences in these components between aphasic subjects and normal subjects are considerably larger than the differences between college students and 60-to 75-year-old subjects.…”

Section: Effects Of Aphasia-mentioning

confidence: 98%

“…Because the diffusion model can separate components of processing, it has come to be used in a variety of research domains, for example, to study the effects of age and aphasia on memory and decision criteria (college students to 90 year old; Ratcliff, Thapar, & McKoon, 2001, 2003Ratcliff, Perea, Coleangelo, & Buchanan, 2004) and the effects of depression on information processing (White, Ratcliff, Vasey, & McKoon, 2007). Recent studies have also mapped the model's components of processing onto neural firing rate data, in part because diffusion processes appear to naturally approximate the behavior of aggregate firing rates of populations of neurons.…”

Section: Introductionmentioning

confidence: 99%

The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks

Ratcliff

¹

,

McKoon

²

2008

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The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data-accuracy, mean response times, and response time distributions-into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either speed or accuracy affect the criterial amounts of information that a subject requires before initiating a response; and the relative proportions of the two stimuli affect biases in drift rate and starting point. The experiments also illustrate the strong constraints that ensure the model is empirically testable and potentially falsifiable. The broad range of applications of the model is also reviewed, including research in the domains of aging and neurophysiology.

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“…To do that, we employed Ratcliff's (1978) diffusion model for speeded two-choice decisions. This model has been quite successful at accounting for lexical decision data (e.g., Ratcliff, Gomez, & McKoon 2004; see also Gomez, Ratcliff, & Perea, 2007;Ratcliff, Perea, Colangelo, & Buchanan 2004;Wagenmakers, Ratcliff, Gomez, & McKoon, 2008). According to the diffusion model account of the lexical decision task, the visual stimulus is encoded so that the relevant stimulus features (e.g., lexical features) are utilized to accumulate evidence toward a "word" or "nonword" response.…”

Section: Introductionmentioning

confidence: 99%

Increasing interletter spacing facilitates encoding of words

Perea

¹

,

Gómez

²

2012

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Recent research has suggested that words presented with a slightly increased interletter spacing are identified faster than words presented with the default spacing settings (i.e., is faster to identify than ; see Perea, Moret-Tatay, & Gomez, 2011). To examine the nature of the effect of interletter spacing in visual-word recognition (i.e., affecting encoding processes vs. quality of information), we fitted Ratcliff's (1978) diffusion model to a lexical decision experiment in which we manipulated a range of five interletter spacings (from condensed [-0.5] to expanded [1.5]). The results showed an effect of interletter spacing on latencies to word stimuli, which reflected a linear decreasing trend: Words presented with a more expanded interletter spacing were identified more rapidly than those with a narrower spacing. Fits from the diffusion model revealed that interletter spacing produces small changes in the encoding process rather than changes in the quality of lexical information. This finding opens a new window of opportunities to examine the role of interletter spacing in more applied settings.

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“…analyses show that this comes about because they set more conservative criteria and have longer nondecision times (Ratcliff, Perea, et al, 2004). The differences in these components between aphasic subjects and normal subjects are considerably larger than the differences between college students and 60-to 75-year-old subjects.…”

Section: Effects Of Aphasiamentioning

confidence: 96%

Untitled

2008

Neural Computation

0

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The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data-accuracy, mean response times, and response time distributions-into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either speed or accuracy affect the criterial amounts of information that a subject requires before initiating a response; and the relative proportions of the two stimuli affect biases in drift rate and starting point. The experiments also illustrate the strong constraints that ensure the model is empirically testable and potentially falsifiable. The broad range of applications of the model is also reviewed, including research in the domains of aging and neurophysiology.

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A diffusion model account of normal and impaired readers

Cited by 44 publications

References 16 publications

The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks

The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks

Increasing interletter spacing facilitates encoding of words

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