Literature DB >> 30719974

Time preferences are reliable across time-horizons and verbal versus experiential tasks.

Evgeniya Lukinova1,2, Yuyue Wang1,2, Steven F Lehrer1,2,3,4, Jeffrey C Erlich1,2,5.   

Abstract

Individual differences in delay-discounting correlate with important real world outcomes, for example education, income, drug use, and criminality. As such, delay-discounting has been extensively studied by economists, psychologists and neuroscientists to reveal its behavioral and biological mechanisms in both human and non-human animal models. However, two major methodological differences hinder comparing results across species. Human studies present long time-horizon options verbally, whereas animal studies employ experiential cues and short delays. To bridge these divides, we developed a novel language-free experiential task inspired by animal decision-making studies. We found that the ranks of subjects' time-preferences were reliable across both verbal/experiential and second/day differences. Yet, discount factors scaled dramatically across the tasks, indicating a strong effect of temporal context. Taken together, this indicates that individuals have a stable, but context-dependent, time-preference that can be reliably assessed using different methods, providing a foundation to bridge studies of time-preferences across species. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
© 2019, Lukinova et al.

Entities:  

Keywords:  computational biology; decision-making; delay-discounting; experiential; human; intertemporal; neuroscience; perceptual; systems biology

Mesh:

Year:  2019        PMID: 30719974      PMCID: PMC6363390          DOI: 10.7554/eLife.39656

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


  61 in total

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5.  Within-subject comparison of real and hypothetical money rewards in delay discounting.

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Review 7.  A unified framework for addiction: vulnerabilities in the decision process.

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8.  PsychoPy--Psychophysics software in Python.

Authors:  Jonathan W Peirce
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9.  Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence.

Authors:  Woo-Young Ahn; Divya Ramesh; Frederick Gerard Moeller; Jasmin Vassileva
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Journal:  Elife       Date:  2013-03-19       Impact factor: 8.140

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  1 in total

1.  Temporal discounting when outcomes are experienced in the moment: Validation of a novel paradigm and comparison with a classic hypothetical intertemporal choice task.

Authors:  Virginie M Patt; Renee Hunsberger; Dominoe A Jones; Margaret M Keane; Mieke Verfaellie
Journal:  PLoS One       Date:  2021-05-14       Impact factor: 3.240

  1 in total

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