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Decision Making01:20

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Several physiological and lifestyle factors influence blood pressure (BP). Understanding these factors is crucial as they are significant in patient education and blood pressure management.
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Evidence or Confidence: What Is Really Monitored during a Decision?

Douglas G Lee1,2, Jean Daunizeau3,4, Giovanni Pezzulo5

  • 1Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy. DouglasGLee@gmail.com.

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|March 14, 2023
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Summary
This summary is machine-generated.

This study proposes a new model where confidence, not just evidence, guides decision-making. This confidence-driven model (cDDM) explains existing findings and extends to multiple choices.

Keywords:
ChoiceMetacognitionPreferential decision-makingValue-based decision-making

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Decision Science

Background:

  • Decision-making models typically rely on accumulated evidence, treating confidence assessment as secondary.
  • Standard models like the drift-diffusion model (DDM) do not integrate confidence into the core choice mechanism.

Purpose of the Study:

  • To propose and validate a novel confidence-driven decision-making model (cDDM).
  • To demonstrate that monitoring evolving confidence, rather than raw evidence, can drive adaptive choices.
  • To show the generalizability of the cDDM to multi-option decisions.

Main Methods:

  • Development of a confidence-driven drift-diffusion model (cDDM).
  • Reinterpretation of existing findings on perceptual and value-based decisions through the lens of the cDDM.
  • Theoretical extension of the model to accommodate decisions with multiple alternatives.

Main Results:

  • The cDDM offers a more parsimonious explanation for previously observed decision-making phenomena.
  • The model naturally generalizes to decisions with more than two options, a limitation of traditional DDMs.
  • Confidence monitoring provides a framework for understanding the trade-off between decision accuracy and resource allocation.

Conclusions:

  • Confidence, not just evidence, is a crucial factor monitored during decision-making.
  • The confidence-driven drift-diffusion model (cDDM) provides a unified and more generalizable framework for understanding choice behavior.
  • Future empirical research is needed to further differentiate between evidence-accumulation and confidence-driven models.