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Parameter estimation of hyper-spherical diffusion models with a time-dependent threshold: An integral equation

Amir Hosein Hadian Rasanan1, Nathan J Evans2,3, Jamal Amani Rad4

  • 1Department of Psychology, University of Basel, Basel, Switzerland. amir.h.hadian@gmail.com.

Behavior Research Methods
|September 10, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for analyzing decision-making models, specifically hyper-spherical diffusion models. The integral equation method accurately estimates decision parameters, even when caution changes over time.

Keywords:
Collapsing thresholdsContinuous option spaceDecision makingParameter estimationSequential sampling models

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Area of Science:

  • Cognitive Psychology
  • Decision-Making Research
  • Mathematical Modeling

Background:

  • Decision-making research traditionally focused on binary choices, assuming constant caution.
  • Recent studies explore continuous responses and time-dependent caution but remain separate.
  • A methodological gap exists in estimating decision models with time-dependent parameters for continuous responses.

Purpose of the Study:

  • To develop a stable and efficient parameter estimation technique for hyper-spherical diffusion models.
  • To address the lack of methodology for decision models with time-dependent parameters in continuous response tasks.
  • To enable the study of how caution changes during decision-making in continuous tasks.

Main Methods:

  • Proposed an integral equation method for estimating the first-passage time distribution.
  • Utilized hyper-spherical diffusion models with time-dependent thresholds.
  • Conducted parameter recovery studies to assess method robustness.

Main Results:

  • The integral equation method provides efficient and precise parameter estimates.
  • Demonstrated robustness for both constant and time-dependent threshold models.
  • Successfully estimated parameters for hyper-spherical diffusion models with varying caution.

Conclusions:

  • The proposed integral equation method bridges the gap between continuous response tasks and time-dependent decision-making models.
  • This technique allows for more realistic modeling of decision-making processes where caution may vary.
  • Facilitates future research into the dynamics of decision-making under varying time constraints and response types.