Decision criteria in dual discrimination tasks estimated using external-noise methods
- PMID: 22351481
- DOI: 10.3758/s13414-012-0269-0
Decision criteria in dual discrimination tasks estimated using external-noise methods
Abstract
According to classical signal detection theory (SDT), in simple detection or discrimination tasks, observers use a decision parameter based on their noisy internal response to set a boundary between "yes" and "no" responses. Experimental paradigms where performance is limited by internal noise cannot be used to provide an unambiguous measure of the decision criterion and its variability. Here, unidimensional external noise is used to estimate a criterion and its variability in stimulus space. Within this paradigm, the criterion is defined as the stimulus value separating the two response alternatives. This paradigm allows the assessment of interactions between criteria assigned to different targets in dual tasks. Previous studies suggested that observers' criteria interacted or even collapsed to one (hence, nonoptimal) criterion. An alternative interpretation of those results is that observers equated their false alarm (FA) rates. The external-noise method enables the confrontation of the two hypotheses. It is shown that the variability of observers' criterion in stimulus space is about 1.6 times their measured sensory threshold, suggesting that the presence of external noise increases decision uncertainty. Observers' stimulus criterion settings are close to SDT predictions in single tasks, but not in dual tasks where the two criteria tend to "attract" each other. Observers maintain distinct FA rates even when SDT predicts equal rates. Observers trained in psychophysics or provided with basic notions of SDT exemplified with the present experimental design manage to better separate their criteria in some conditions.
Similar articles
-
Spatial four-alternative forced-choice method is the preferred psychophysical method for naïve observers.J Vis. 2006 Nov 10;6(11):1307-22. doi: 10.1167/6.11.13. J Vis. 2006. PMID: 17209737
-
Classification images for detection, contrast discrimination, and identification tasks with a common ideal observer.J Vis. 2006 Feb 28;6(4):335-55. doi: 10.1167/6.4.4. J Vis. 2006. PMID: 16889473
-
What limits performance in the amblyopic visual system: seeing signals in noise with an amblyopic brain.J Vis. 2008 Apr 4;8(4):1.1-23. doi: 10.1167/8.4.1. J Vis. 2008. PMID: 18484840
-
On the measurement of criterion noise in signal detection theory: the case of recognition memory.Psychol Rev. 2012 Jul;119(3):457-79. doi: 10.1037/a0027727. Epub 2012 Apr 2. Psychol Rev. 2012. PMID: 22468607 Review.
-
Statistical decision theory to relate neurons to behavior in the study of covert visual attention.Vision Res. 2009 Jun;49(10):1097-128. doi: 10.1016/j.visres.2008.12.008. Epub 2009 Jan 10. Vision Res. 2009. PMID: 19138699 Review.
Cited by
-
Challenging the fixed-criterion model of perceptual decision-making.Neurosci Conscious. 2023 Apr 20;2023(1):niad010. doi: 10.1093/nc/niad010. eCollection 2023. Neurosci Conscious. 2023. PMID: 37089450 Free PMC article.
-
Humans incorporate attention-dependent uncertainty into perceptual decisions and confidence.Proc Natl Acad Sci U S A. 2018 Oct 23;115(43):11090-11095. doi: 10.1073/pnas.1717720115. Epub 2018 Oct 8. Proc Natl Acad Sci U S A. 2018. PMID: 30297430 Free PMC article.
-
Dynamics of sensory and decisional biases in perceptual decision making: Insights from the face distortion illusion.Psychon Bull Rev. 2025 Feb;32(1):317-325. doi: 10.3758/s13423-024-02539-8. Epub 2024 Jul 9. Psychon Bull Rev. 2025. PMID: 38980570
-
Suboptimality in perceptual decision making.Behav Brain Sci. 2018 Feb 27;41:e223. doi: 10.1017/S0140525X18000936. Behav Brain Sci. 2018. PMID: 29485020 Free PMC article.
-
A robust confidence-accuracy dissociation via criterion attraction.Neurosci Conscious. 2021 Nov 15;2021(1):niab039. doi: 10.1093/nc/niab039. eCollection 2021. Neurosci Conscious. 2021. PMID: 34804591 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources