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A Multiple-Well Framework for Human Perceptual Decision-Making.

Joseph Fluegemann1, Jiaqi Huang2, Morgan Lena Rosendahl1,3

  • 1Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA.

Entropy (Basel, Switzerland)
|February 27, 2026
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Summary
This summary is machine-generated.

This study introduces a quantum cognitive model for decision-making, linking cognitive control to perceptual tasks. The model successfully predicts human choices and response times, offering new insights into the Yerkes-Dodson law.

Keywords:
arousalcognitive controldrift diffusion modelsperceptual decision makingquantum cognition

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Area of Science:

  • Cognitive Science
  • Quantum Physics
  • Decision Neuroscience

Background:

  • Human decision-making involves complex cognitive processes.
  • Understanding the role of cognitive control and arousal is crucial.
  • Existing models may not fully capture these influences.

Purpose of the Study:

  • To present a novel quantum cognitive model integrating cognitive control into perceptual decision-making.
  • To quantitatively model the influence of cognitive arousal on task performance, specifically addressing the Yerkes-Dodson law.
  • To provide a framework for understanding subjective probabilities and evidence accumulation.

Main Methods:

  • Developed a quantum cognitive model using a multiple-square-well potential.
  • Each well represents a decision outcome, with depth encoding signal strength and width encoding domain generality.
  • Validated the model using the dot motion two-alternative forced-choice (2AFC) task and applied it to the Yerkes-Dodson law.

Main Results:

  • The model successfully replicated key empirical findings from the 2AFC task, including correlations between motion coherence and drift rates.
  • The model captured the inverted U-shaped relationship between task accuracy and cognitive arousal, characteristic of the Yerkes-Dodson law.
  • Comparison of two arousal modeling approaches (eigenenergy vs. kinetic energy) yielded distinct predictions.

Conclusions:

  • This work presents the first quantitative model of arousal's impact on human perceptual decision-making.
  • The quantum cognitive model provides a robust framework for understanding decision-making under varying cognitive control and arousal levels.
  • The study lays the groundwork for precisely defining the functional form of the Yerkes-Dodson law.