Diffusion Decision Model: Current Issues and History

Abstract

There is growing interest in diffusion models to represent the cognitive and neural processes of speeded decision making. Sequential-sampling models like the diffusion model have a long history in psychology. They view decision making as a process of noisy accumulation of evidence from a stimulus. The standard model assumes that evidence accumulates at a constant rate during the second or two it takes to make a decision. This process can be linked to the behaviors of populations of neurons and to theories of optimality. Diffusion models have been used successfully in a range of cognitive tasks and as psychometric tools in clinical research to examine individual differences. In this article, we relate the models to both earlier and more recent research in psychology.

The channel capacity of visual awareness divided among multiple moving objects

“…Such constant-rate processes are found in many physical phenomena, such as radioactive decay, Brownian motion, and molecular diffusion. Diffusion processes have been shown to account for speed and accuracy in a variety of discrimination, decision-making, and attention tasks (e.g., Ratcliff, 2014;Ratcliff et al, 2016;Smith, 2010;Smith & Ratcliff, 2009). A diffusion process is also compatible with aspects of the present results.…”

The Parallel Episodic Processing (PEP) model 2.0: A single computational model of stimulus-response binding, contingency learning, power curves, and mixing costs

“…This is similar to models of choice behaviour, where each episode "votes" for the response to make (e.g., Howard & Kahana, 2002). This is also similar to how diffusion models (for a review, see Ratcliff, Smith, Brown, & McKoon, 2016) simulate a practice curve with (in addition to other factors) increased accrual of evidence for the likely response with training (Dutilh, Vandekerckhove, Tuerlinckx, & Wagenmakers, 2009;Ratcliff, Thapar, & McKoon, 2006). This is unlike the model of Logan where episodes "race" each other for retrieval and the "winner" determines the response.…”

Individual Differences in Language Acquisition and Processing

“…Means and standard deviations of lexical decision tasks exhibit excellent test/retest reliability (r = 0.87 [142]). However, these raw means reflect the combination of many distinct cognitive parameters, such as encoding, evidence accumulation, response thresholds, and response execution times [143]. This means that two participants might have different means on a task despite being identical in the component process of interest, or have identical means despite differing in the component of interest.…”