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Cognitive and Neural Bases of Multi-Attribute, Multi-Alternative, Value-based Decisions.

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Sequential sampling models now explain value-based decisions involving complex choices. Understanding these models requires exploring intricate decision mechanisms and their neural underpinnings for a complete picture of human decision-making.

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Area of Science:

  • Cognitive Neuroscience
  • Decision Science
  • Neuroeconomics

Background:

  • Evidence-based decision making is characterized as sequential sampling.
  • Sequential sampling models have been extended to value-based decisions involving multi-attribute, multi-alternative choices.
  • These models help explain context effects in preferential choice tasks.

Purpose of the Study:

  • To review complex decision mechanisms needed for sequential sampling models in value-based choice.
  • To explore the neural substrates linked to these complex decision processes.
  • To develop a biologically plausible account of human value-based decision making.

Main Methods:

  • Literature review of sequential sampling models in decision making.
  • Analysis of complex decision mechanisms for multi-attribute, multi-alternative choices.
  • Examination of neural correlates of value-based decision processes.

Main Results:

  • Sequential sampling models require complex mechanisms to predict preferences in value-based choices.
  • Context effects in multi-attribute choices necessitate advanced modeling approaches.
  • Linkages between complex decision processes and neural substrates are identified.

Conclusions:

  • A comprehensive understanding of value-based decision making requires integrating complex cognitive mechanisms with their neural basis.
  • Sequential sampling models, when augmented with sophisticated decision rules, can account for context effects.
  • This review provides a foundation for biologically plausible models of human choice behavior.