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Joint Modelling of Latent Cognitive Mechanisms Shared Across Decision-Making Domains
Niek Stevenson1, Reilly J Innes1, Russell J Boag1
1Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.
Computational Brain & Behavior
|March 1, 2024
Summary
Evidence accumulation models (EAMs) parameters show consistency across time points for most decision-making tasks. Joint modeling reveals information processing ability is linked across domains, but response caution and urgency vary.
Area of Science:
- Cognitive Psychology
- Decision Science
- Computational Neuroscience
Background:
- Evidence accumulation models (EAMs) are widely used to understand decision-making.
- A key assumption is the consistency of EAM parameters across different decision-making domains.
- The stability of these cognitive constructs over time and across tasks requires empirical validation.
Purpose of the Study:
- To investigate the consistency of EAM parameters across different decision-making domains.
- To examine the stability of EAM parameters across different time points.
- To explore the relationships between latent cognitive constructs in decision-making.
Main Methods:
- Utilized a novel joint modeling approach to simultaneously analyze parameters from multiple decision-making domains.
- Incorporated factor analysis within the joint model to identify underlying relationships between parameters.
- Accounted for measurement error and uncertainty in parameter estimation.
Main Results:
- EAM parameters demonstrated consistency across time points in three out of four decision-making tasks.
- A two-factor joint model revealed that information processing ability was consistently related across different decision-making domains.
- Other cognitive constructs, such as response caution and urgency, showed domain-specific comparability.
Conclusions:
- EAM parameters exhibit temporal stability for most decision-making tasks.
- Information processing ability appears to be a general cognitive factor influencing decisions across domains.
- Domain-specific variations in response caution and urgency suggest context-dependent decision strategies.
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