Literature DB >> 29224184

Experimental validation of the diffusion model based on a slow response time paradigm.

Veronika Lerche1, Andreas Voss2.   

Abstract

The diffusion model (Ratcliff, Psychol Rev 85(2):59-108, 1978) is a stochastic model that is applied to response time (RT) data from binary decision tasks. The model is often used to disentangle different cognitive processes. The validity of the diffusion model parameters has, however, rarely been examined. Only few experimental paradigms have been analyzed with those being restricted to fast response time paradigms. This is attributable to a recommendation stated repeatedly in the diffusion model literature to restrict applications to fast RT paradigms (more specifically, to tasks with mean RTs below 1.5 s per trial). We conducted experimental validation studies in which we challenged the necessity of this restriction. We used a binary task that features RTs of several seconds per trial and experimentally examined the convergent and discriminant validity of the four main diffusion model parameters. More precisely, in three experiments, we selectively manipulated these parameters, using a difficulty manipulation (drift rate), speed-accuracy instructions (threshold separation), a more complex motoric task (non-decision time), and an asymmetric payoff matrix (starting point). The results were similar to the findings from experimental validation studies based on fast RT paradigms. Thus, our experiments support the validity of the parameters of the diffusion model and speak in favor of an extension of the model to paradigms based on slower RTs.

Keywords:  Diffusion model; Fast-dm; Mathematical models; Reaction time methods

Mesh:

Year:  2017        PMID: 29224184     DOI: 10.1007/s00426-017-0945-8

Source DB:  PubMed          Journal:  Psychol Res        ISSN: 0340-0727


  36 in total

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Authors:  M Usher; J L McClelland
Journal:  Psychol Rev       Date:  2001-07       Impact factor: 8.934

2.  Estimating parameters of the diffusion model: approaches to dealing with contaminant reaction times and parameter variability.

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Journal:  Psychon Bull Rev       Date:  2002-09

3.  A diffusion model account of response time and accuracy in a brightness discrimination task: fitting real data and failing to fit fake but plausible data.

Authors:  Roger Ratcliff
Journal:  Psychon Bull Rev       Date:  2002-06

4.  On the locus of speed-accuracy trade-off in reaction time: inferences from the lateralized readiness potential.

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5.  A diffusion model analysis of the effects of aging in the lexical-decision task.

Authors:  Roger Ratcliff; Anjali Thapar; Pablo Gomez; Gail McKoon
Journal:  Psychol Aging       Date:  2004-06

6.  Interpreting the parameters of the diffusion model: an empirical validation.

Authors:  Andreas Voss; Klaus Rothermund; Jochen Voss
Journal:  Mem Cognit       Date:  2004-10

7.  Programming strategies for rapid aiming movements under simple and choice reaction time conditions.

Authors:  Michael A Khan; Gavin P Lawrence; Eric Buckolz; Ian M Franks
Journal:  Q J Exp Psychol (Hove)       Date:  2006-03       Impact factor: 2.143

Review 8.  The diffusion decision model: theory and data for two-choice decision tasks.

Authors:  Roger Ratcliff; Gail McKoon
Journal:  Neural Comput       Date:  2008-04       Impact factor: 2.026

9.  The simplest complete model of choice response time: linear ballistic accumulation.

Authors:  Scott D Brown; Andrew Heathcote
Journal:  Cogn Psychol       Date:  2008-02-20       Impact factor: 3.468

10.  Fast-dm: a free program for efficient diffusion model analysis.

Authors:  Andreas Voss; Jochen Voss
Journal:  Behav Res Methods       Date:  2007-11
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  14 in total

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Journal:  Psychol Res       Date:  2020-06-13

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Journal:  Alcohol Clin Exp Res       Date:  2022-02-13       Impact factor: 3.455

3.  Task-general efficiency of evidence accumulation as a computationally-defined neurocognitive trait: Implications for clinical neuroscience.

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4.  The Effect of Ingroup vs. Outgroup Members' Behavior on Charity Preference: A Drift-Diffusion Model Approach.

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5.  Mental speed is high until age 60 as revealed by analysis of over a million participants.

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Journal:  Nat Hum Behav       Date:  2022-02-17

6.  A New Spin on Spatial Cognition in ADHD: A Diffusion Model Decomposition of Mental Rotation.

Authors:  Jason S Feldman; Cynthia Huang-Pollock
Journal:  J Int Neuropsychol Soc       Date:  2020-12-09       Impact factor: 2.892

7.  Parallel and serial task processing in the PRP paradigm: a drift-diffusion model approach.

Authors:  André Mattes; Felice Tavera; Anja Ophey; Mandy Roheger; Robert Gaschler; Hilde Haider
Journal:  Psychol Res       Date:  2020-04-25

8.  The diffusion model visualizer: an interactive tool to understand the diffusion model parameters.

Authors:  Rainer W Alexandrowicz
Journal:  Psychol Res       Date:  2018-10-25

9.  Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence.

Authors:  Anna-Lena Schubert; Dirk Hagemann; Christoph Löffler; Gidon T Frischkorn
Journal:  J Intell       Date:  2019-12-25

10.  Age-related differences in visual encoding and response strategies contribute to spatial memory deficits.

Authors:  Vladislava Segen; Marios N Avraamides; Timothy J Slattery; Jan M Wiener
Journal:  Mem Cognit       Date:  2021-02
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