Literature DB >> 32730057

Examining aging and numerosity using an integrated diffusion model.

Roger Ratcliff1, Gail McKoon1.   

Abstract

Two experiments are presented that use tasks common in research in numerical cognition with young adults and older adults as subjects. In these tasks, one or two arrays of dots are displayed, and subjects decide whether there are more or fewer dots of one kind than another. Results show that older adults, relative to young adults, tend to rely more on the perceptual feature, area, in making numerosity judgments when area is correlated with numerosity. Also, convex hull unexpectedly shows different effects depending on the task (being either correlated with numerosity or anticorrelated). Accuracy and response time (RT) data are interpreted with the integration of the diffusion decision model with models for the representation of numerosity. One model assumes that the representation of the difference depends on the difference between the numerosities and that standard deviations (SDs) increase linearly with numerosity, and the other model assumes a log representation with constant SDs. The representational models have coefficients that are applied to differences between two numerosities to produce drift rates and SDs in drift rates in the decision process. The two tasks produce qualitatively different patterns of RTs: One model fits results from one task, but the results are mixed for the other task. The effects of age on model parameters show a modest decrease in evidence driving the decision process, an increase in the duration of processes outside the decision process (nondecision time), and an increase in the amount of evidence needed to make a decision (boundary separation). (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Entities:  

Year:  2020        PMID: 32730057      PMCID: PMC8054446          DOI: 10.1037/xlm0000937

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  76 in total

1.  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

2.  Modeling the interaction of numerosity and perceptual variables with the diffusion model.

Authors:  Inhan Kang; Roger Ratcliff
Journal:  Cogn Psychol       Date:  2020-04-20       Impact factor: 3.468

Review 3.  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

4.  The predictive value of numerical magnitude comparison for individual differences in mathematics achievement.

Authors:  Bert De Smedt; Lieven Verschaffel; Pol Ghesquière
Journal:  J Exp Child Psychol       Date:  2009-03-13

5.  Number sense across the lifespan as revealed by a massive Internet-based sample.

Authors:  Justin Halberda; Ryan Ly; Jeremy B Wilmer; Daniel Q Naiman; Laura Germine
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-25       Impact factor: 11.205

6.  Developing a tool for measuring the decision-making competence of older adults.

Authors:  Melissa L Finucane; Christina M Gullion
Journal:  Psychol Aging       Date:  2010-06

7.  Absolutely relative or relatively absolute: violations of value invariance in human decision making.

Authors:  Andrei R Teodorescu; Rani Moran; Marius Usher
Journal:  Psychon Bull Rev       Date:  2016-02

8.  Declining financial capacity in mild cognitive impairment: A 1-year longitudinal study.

Authors:  K L Triebel; R Martin; H R Griffith; J Marceaux; O C Okonkwo; L Harrell; D Clark; J Brockington; A Bartolucci; Daniel C Marson
Journal:  Neurology       Date:  2009-09-22       Impact factor: 9.910

9.  Number skills are maintained in healthy ageing.

Authors:  Marinella Cappelletti; Daniele Didino; Ivilin Stoianov; Marco Zorzi
Journal:  Cogn Psychol       Date:  2014-01-11       Impact factor: 3.468

10.  Effect of cognitive dysfunction on the relationship between age and health literacy.

Authors:  Kimberly A Kaphingst; Melody S Goodman; William D MacMillan; Christopher R Carpenter; Richard T Griffey
Journal:  Patient Educ Couns       Date:  2014-02-22
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