Literature DB >> 34561303

How top-down and bottom-up attention modulate risky choice.

Yonatan Vanunu1, Jared M Hotaling2,3, Mike E Le Pelley2, Ben R Newell2.   

Abstract

We examine how bottom-up (or stimulus-driven) and top-down (or goal-driven) processes govern the distribution of attention in risky choice. In three experiments, participants chose between a certain payoff and the chance of receiving a payoff drawn randomly from an array of eight numbers. We tested the hypothesis that initial attention is driven by perceptual properties of the stimulus (e.g., font size of the numbers), but subsequent choice is goal-driven (e.g., win the best outcome). Two experiments in which task framing (goal driven) and font size (stimulus driven) were manipulated demonstrated that payoffs with the highest values and the largest font sizes had the greatest impact on choice. The third experiment added a number in large font to the array, which could not be an outcome of the gamble (i.e., a distractor). Eye movement and choice data indicated that although the distractor attracted attention, it had no influence on option selection. Together with computational modeling analyses, the results suggest that perceptual salience can induce bottom-up effects of overt selection but that the perceived value of information is the crucial arbiter of intentional control over risky choice.

Entities:  

Keywords:  bottom-up; extreme outcomes; risky choice; selective attention; top-down

Year:  2021        PMID: 34561303      PMCID: PMC8488801          DOI: 10.1073/pnas.2025646118

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  26 in total

1.  Visual fixations and the computation and comparison of value in simple choice.

Authors:  Ian Krajbich; Carrie Armel; Antonio Rangel
Journal:  Nat Neurosci       Date:  2010-09-12       Impact factor: 24.884

Review 2.  Half a century of research on the Stroop effect: an integrative review.

Authors:  C M MacLeod
Journal:  Psychol Bull       Date:  1991-03       Impact factor: 17.737

3.  Simultaneous modeling of visual saliency and value computation improves predictions of economic choice.

Authors:  R Blythe Towal; Milica Mormann; Christof Koch
Journal:  Proc Natl Acad Sci U S A       Date:  2013-09-09       Impact factor: 11.205

4.  Attentional capture is contingent on the interaction between task demand and stimulus salience.

Authors:  Shena Lu; Shihui Han
Journal:  Atten Percept Psychophys       Date:  2009-07       Impact factor: 2.199

5.  Effects of salience are both short- and long-lived.

Authors:  Jacob L Orquin; Carl Johan Lagerkvist
Journal:  Acta Psychol (Amst)       Date:  2015-07-16

6.  Gaze Amplifies Value in Decision Making.

Authors:  Stephanie M Smith; Ian Krajbich
Journal:  Psychol Sci       Date:  2018-12-07

Review 7.  Computational modelling of visual attention.

Authors:  L Itti; C Koch
Journal:  Nat Rev Neurosci       Date:  2001-03       Impact factor: 34.870

8.  Salience driven value integration explains decision biases and preference reversal.

Authors:  Konstantinos Tsetsos; Nick Chater; Marius Usher
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-25       Impact factor: 11.205

9.  Ensemble perception: Extracting the average of perceptual versus numerical stimuli.

Authors:  David Rosenbaum; Vincent de Gardelle; Marius Usher
Journal:  Atten Percept Psychophys       Date:  2021-01-03       Impact factor: 2.199

10.  Value-based attention but not divisive normalization influences decisions with multiple alternatives.

Authors:  Sebastian Gluth; Nadja Kern; Maria Kortmann; Cécile L Vitali
Journal:  Nat Hum Behav       Date:  2020-02-03
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  1 in total

1.  Formalizing the fundamental Faustian bargain: Inefficacious decision-makers sacrifice their freedom of choice to coercive leaders for economic security.

Authors:  Daniel A DeCaro; Marci S DeCaro; Jared M Hotaling; Rachel Appel
Journal:  PLoS One       Date:  2022-09-27       Impact factor: 3.752

  1 in total

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