Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture

•We investigated strategies for memory-based inferences about real-world objects.•The strategies differ in how they use recognition and additional knowledge.•We implemented the strategies as computational models in the ACT-R architecture.•The models were tested on predictions for response times and...

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Bibliographic Details
Published in:Cognition 2016-12, Vol.157, p.77-99
Main Authors: Fechner, Hanna B., Pachur, Thorsten, Schooler, Lael J., Mehlhorn, Katja, Battal, Ceren, Volz, Kirsten G., Borst, Jelmer P.
Format: Article
Language:English
Subjects:
Acknowledgment
ACT-R
Adult
Behavior
Blood
Brain - physiology
Brain Mapping
Cognition - physiology
Cognitive ability
Cognitive-behavioral factors
Computational modeling
Computer applications
Decision making
Decision Making - physiology
Female
Functional magnetic resonance imaging
Heuristics - physiology
Humans
Judgment - physiology
Knowledge
Magnetic Resonance Imaging
Male
Mathematical models
Medical imaging
Memories
Memory
Mental Recall - physiology
Models, Neurological
Models, Psychological
Neuroimaging
Oxygen
Reaction Time
Recognition (Psychology) - physiology
Recognition heuristic
Recognition memory
Usefulness
Young Adult
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Summary:•We investigated strategies for memory-based inferences about real-world objects.•The strategies differ in how they use recognition and additional knowledge.•We implemented the strategies as computational models in the ACT-R architecture.•The models were tested on predictions for response times and neural activation.•A strategy that processes recognition and knowledge sequentially performed best. How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and a third, lexicographic (i.e., sequential) strategy, that considers knowledge conditionally on the evidence obtained from recognition memory. We implemented the strategies as computational models within the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, which allowed us to derive behavioral and neural predictions that we then compared to the results of a functional magnetic resonance imaging (fMRI) study in which participants inferred which of two cities is larger. Overall, versions of the lexicographic strategy, according to which knowledge about many but not all alternatives is searched, provided the best account of the joint patterns of response times and BOLD responses. These results provide insights into the interplay between recognition and additional knowledge in memory, hinting at an adaptive use of these two sources of information in decision making. The results highlight the usefulness of implementing models of decision making within a cognitive architecture to derive predictions on the behavioral and neural level.
ISSN:0010-0277
1873-7838
DOI:10.1016/j.cognition.2016.08.011