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An illustrative guide to expressing cognitive theories using evidence accumulation modelling
Luke Strickland1, Russell J Boag2, Niek Stevenson3
1The Future of Work Institute, Curtin University, 78 Murray Street, Perth, 6000, Australia. luke.strickland@curtin.edu.au.
Behavior Research Methods
|April 1, 2026
Summary
This tutorial introduces the EMC2 R package for embedding cognitive process theories into evidence accumulation models (EAMs). It provides a framework for mapping EAM parameters to experimental designs, enhancing cognitive modeling capabilities.
Area of Science:
- Cognitive Psychology
- Computational Neuroscience
- Decision Science
Background:
- Evidence accumulation models (EAMs) offer a cognitive process-based approach to understanding human choice and response times.
- Existing EAMs lack clear guidance for instantiating complex cognitive process theories and mapping parameters to experimental designs.
Purpose of the Study:
- To provide a tutorial on embedding cognitive process theories into EAMs using the R package EMC2.
- To demonstrate a method for estimating cognitive process effects by mapping EAM parameters to experimental designs.
Main Methods:
- Utilized an augmented linear model language within the EMC2 package to map EAM parameters to experimental designs.
- Instantiated theories of prospective memory and advice integration from automated decision aids.
- Demonstrated combining multiple theories within a unified framework.
Main Results:
- Successfully embedded complex cognitive theories into EAMs using the EMC2 package.
- Showcased the estimation of cognitive process effects through parameter mapping.
- Illustrated the flexibility of the framework for integrating diverse theoretical components.
Conclusions:
- The EMC2 package offers a practical solution for theory embedding in EAMs.
- Future directions include non-linear mappings and trial-by-trial dynamics for advanced cognitive modeling.
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