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An R-Based Landscape Validation of a Competing Risk Model
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Context-Dependent Risk Aversion: A Model-Based Approach.

Darío Cuevas Rivera1, Florian Ott1, Dimitrije Markovic1

  • 1Chair of Neuroimaging, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.

Frontiers in Psychology
|November 13, 2018
PubMed
Summary

This study reveals individual differences in how people adapt their risk aversion based on context. A new model quantifies this adaptation at a single-trial level, linking it to internal task representations.

Keywords:
active inferencedecision makingmodelingrisk aversionsingle subject

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Area of Science:

  • Behavioral science
  • Cognitive psychology
  • Decision science

Background:

  • Traditional risk aversion research often overlooks context-dependent adaptation.
  • Recent studies investigate risk aversion adaptation in sequential decision-making.
  • Evidence for single-subject risk aversion adaptation remains an open question.

Purpose of the Study:

  • To investigate single-subject risk aversion adaptation in sequential decision-making.
  • To develop and apply a model-based approach for estimating risk-taking behavior adaptation.
  • To explore the relationship between individual differences in adaptation and internal task representations.

Main Methods:

  • Conducted a behavioral experiment using a sequential decision-making task.
  • Developed a model-based approach for single-trial resolution estimation of risk-taking behavior adaptation.
  • Modeled subjects' goals and internal representation of task contingencies.

Main Results:

  • Estimated subject-specific adaptation of risk aversion based on task context.
  • Observed significant inter-subject variations in risk-taking behavior adaptation.
  • Linked these variations to differences in subjects' internal representations of task contingencies and goals.

Conclusions:

  • Demonstrated the feasibility of estimating single-subject risk aversion adaptation.
  • Highlighted the role of internal representations and goals in adaptive risk-taking.
  • Proposed a versatile approach applicable to various experimental paradigms and behavioral measures.