Literature DB >> 33759115

The distance effect on discrimination ability and response bias during magnitude comparison in a go/no-go task.

Ilgım Hepdarcan1, Merve Bulut1, Ezgi Palaz1, Seda Can1, Seda Dural2.   

Abstract

The distance effect is the change in the performance during numerical magnitude comparison, depending on the numerical distance between the compared numbers (Moyer & Landauer, Nature, 215[5109], 1519-1520, 1967). This effect is generally accepted as evidence for the mental number line (MNL) hypothesis, which proposes that the mental representation of the numbers align in an increasing linear (or monotone) order. The majority of studies investigating the distance effect are focused on the reaction time (RT) findings, which show slower responses for closer numbers. In the present study, we examined the distance effect by applying signal detection theory (SDT) to a magnitude comparison task. We aimed to reveal whether discrimination ability and the response bias measures were affected by the location of numbers on the MNL. To accomplish this, we developed a magnitude comparison task using a go/no-go procedure in which participants performed a magnitude comparison based on a reference number (i.e., 5). Results revealed a substantial distance effect in both sensitivity and response bias measures-a better discrimination performance for far numbers, and a larger response bias for close numbers. In addition, an RT distribution analysis revealed that the distance effect seems to originate mainly from slower responses. Based on the current data, we suggest that sensitivity and response bias measures could offer comprehensive information in the understanding of number-based decisions.

Entities:  

Keywords:  Distance effect; Go/no-go task; Magnitude comparison; Mental number line; Signal detection theory

Year:  2021        PMID: 33759115     DOI: 10.3758/s13414-021-02274-5

Source DB:  PubMed          Journal:  Atten Percept Psychophys        ISSN: 1943-3921            Impact factor:   2.199


  17 in total

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Authors:  Liane Kaufmann; Florian Koppelstaetter; Margarete Delazer; Christian Siedentopf; Paul Rhomberg; Stefan Golaszewski; Stefan Felber; Anja Ischebeck
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Journal:  J Exp Psychol Hum Percept Perform       Date:  2006-02       Impact factor: 3.332

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Authors:  Roi Cohen Kadosh; Warren Brodsky; Michal Levin; Avishai Henik
Journal:  Cortex       Date:  2007-12-23       Impact factor: 4.027

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Authors:  R Ratcliff
Journal:  Psychol Bull       Date:  1979-05       Impact factor: 17.737

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Authors:  P B Buckley; C B Gillman
Journal:  J Exp Psychol       Date:  1974-12

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Authors:  R S Moyer; T K Landauer
Journal:  Nature       Date:  1967-09-30       Impact factor: 49.962

10.  Size before numbers: conceptual size primes numerical value.

Authors:  Shai Gabay; Tali Leibovich; Avishai Henik; Nurit Gronau
Journal:  Cognition       Date:  2013-06-28
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