Literature DB >> 34570551

Estimating systematic and random sources of variability in perceptual decision-making: A reply to Evans, Tillman, & Wagenmakers (2020).

Roger Ratcliff1, Philip L Smith2.   

Abstract

Ratcliff, Voskuilen, and McKoon (2018) presented data and model-based analyses that provided strong evidence for across-trial variability in evidence entering the decision process in several perceptual tasks. They did this using a double-pass procedure in which exactly the same stimuli are presented on two widely-separated trials. If there were only random variability (i.e., the first and second presentations of a stimulus were independent), then the agreement in the choice made on the two trials would be a function of accuracy: as accuracy increases from chance to 100% correct, then the probability of agreement increases. In the experiments, agreement was greater than that predicted from independence which means that there was systematic variability in items from trial to trial. Evans et al. (2020) criticized this by arguing that because of possible tradeoffs among parameters, the evidence did not support two sources of across-trial variability, but rather the results could be explained by only a systematic (item) component of variability. However, their own analysis showed that parameter estimates were accurate enough to support identification of the two sources of variability. We present a new analysis of possible sources of across-trial variability in evidence and show that systematic variability can be estimated from accuracy-agreement functions with a functional form that depends on only two diffusion model parameters. We also point out that size of the estimates of these two sources are model-dependent. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Entities:  

Mesh:

Year:  2021        PMID: 34570551      PMCID: PMC9428907          DOI: 10.1037/rev0000212

Source DB:  PubMed          Journal:  Psychol Rev        ISSN: 0033-295X            Impact factor:   8.247


  34 in total

1.  A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions.

Authors:  Roger Ratcliff; Anil Cherian; Mark Segraves
Journal:  J Neurophysiol       Date:  2003-05-21       Impact factor: 2.714

2.  CONSISTENCY OF AUDITORY DETECTION JUDGMENTS.

Authors:  D M GREEN
Journal:  Psychol Rev       Date:  1964-09       Impact factor: 8.934

3.  Evidence for time-variant decision making.

Authors:  Jochen Ditterich
Journal:  Eur J Neurosci       Date:  2006-12       Impact factor: 3.386

Review 4.  An integrated theory of attention and decision making in visual signal detection.

Authors:  Philip L Smith; Roger Ratcliff
Journal:  Psychol Rev       Date:  2009-04       Impact factor: 8.934

5.  Sequential effects in response time reveal learning mechanisms and event representations.

Authors:  Matt Jones; Tim Curran; Michael C Mozer; Matthew H Wilder
Journal:  Psychol Rev       Date:  2013-07       Impact factor: 8.934

6.  Visual signal detection. IV. Observer inconsistency.

Authors:  A E Burgess; B Colborne
Journal:  J Opt Soc Am A       Date:  1988-04       Impact factor: 2.129

7.  Diffusion models of the flanker task: discrete versus gradual attentional selection.

Authors:  Corey N White; Roger Ratcliff; Jeffrey J Starns
Journal:  Cogn Psychol       Date:  2011-10-01       Impact factor: 3.468

8.  Modeling 2-alternative forced-choice tasks: Accounting for both magnitude and difference effects.

Authors:  Roger Ratcliff; Chelsea Voskuilen; Andrei Teodorescu
Journal:  Cogn Psychol       Date:  2018-03-23       Impact factor: 3.468

9.  On the importance of avoiding shortcuts in applying cognitive models to hierarchical data.

Authors:  Udo Boehm; Maarten Marsman; Dora Matzke; Eric-Jan Wagenmakers
Journal:  Behav Res Methods       Date:  2018-08

Review 10.  Bridging Neural and Computational Viewpoints on Perceptual Decision-Making.

Authors:  Redmond G O'Connell; Michael N Shadlen; KongFatt Wong-Lin; Simon P Kelly
Journal:  Trends Neurosci       Date:  2018-07-12       Impact factor: 13.837

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.