Decomposing task-switching costs with the diffusion model.

Abstract

In four experiments, task-switching processes were investigated with variants of the alternating runs paradigm and the explicit cueing paradigm. The classical diffusion model for binary decisions (Ratcliff, 1978) was used to dissociate different components of task-switching costs. Findings can be reconciled with the view that task-switching processes take place in successive phases as postulated by multiple-components models of task switching (e.g., Mayr & Kliegl, 2003; Ruthruff, Remington, & Johnston, 2001). At an earlier phase, task-set reconfiguration (Rogers & Monsell, 1995) or cue-encoding (Schneider & Logan, 2005) takes place, at a later phase, the response is selected in accord with constraints set in the first phase. Inertia effects (Allport, Styles, & Hsieh, 1994; Allport & Wylie, 2000) were shown to affect this later stage. Additionally, findings support the notion that response caution contributes to both global as well as to local switching costs when task switches are predictable.

Cueing Effects in the Attentional Network Test: a Spotlight Diffusion Model Analysis

“…This suggests that the presence of the cues, which reduces uncertainty about the timing and location of the stimulus, caused participants to decrease their caution for the upcoming response (see "Discussion"). This is consistent with work in taskswitching that showed the predictability of an upcoming trial can lead to changes in response caution (Schmitz and Voss 2012). Further, this effect can be seen in the behavioral data as accuracy was slightly but significantly lower for the orienting cue condition (Fig.…”

“…Such analysis with standard driftdiffusion models has been successfully employed to investigate performance across a range of tasks, including recognition memory (e.g., Ratcliff et al 2004), numerosity judgments (Ratcliff et al 1999), visual perception (e.g., Ratcliff and Rouder 1998), and task-switching (e.g., Schmitz and Voss 2012;Schmitz and Voss 2014). Newly developed conflict diffusion models, like the shrinking spotlight model, the dual-stage two-phase model, and the diffusion model for conflict tasks, can broaden the application of this approach to include tasks for which the standard diffusion model does not apply like the Stroop (Stroop 1935) and Simon (Simon 1969) tasks.…”

How many trials are required for parameter estimation in diffusion modeling? A comparison of different optimization criteria

“…In recent years, however, the diffusion model has increasingly attracted the attention of researchers from various other fields of psychology. Examples indicating the wide range of applications for the diffusion model include analyses of cognitive processes in such typical experimental paradigms as the lexical decision task (e.g., Yap, Balota, & Tan, 2013), sequential priming paradigms (e.g., Voss, Rothermund, Gast, & Wentura, 2013), task switching (Schmitz & Voss, 2012, or prospective memory paradigms (e.g., Boywitt & Rummel, 2012). Other applications encompass social cognitive research (e.g., Germar, Schlemmer, Krug, Voss, & Mojzisch, 2014;Klauer, Voss, Schmitz, & Teige-Mocigemba, 2007;Voss, Rothermund, & Brandtstädter, 2008), cognitive aging (e.g., McKoon & Ratcliff, 2013;Spaniol, Madden, & Voss, 2006), cognitive processes related to psychological disorders (e.g., Metin et al, 2013;Pe, Vandekerckhove, & Kuppens, 2013;White, Ratcliff, Vasey, & McKoon, 2010b), and other fields of psychology.…”

Supplemental Material for Factoring Out Nondecision Time in Choice Reaction Time Data: Theory and Implications

“…In the figures below, we present the full set of results (for all parameters) of the traditional and D*M diffusion model fits to the data from Schmitz and Voss (2012). In Figure 8, task-switching trials are compared to pure task trials; in Figure 8, task-repeating trials are compared to pure task trials.…”