TY - JOUR
T1 - Strategies for memory-based decision making
T2 - Modeling behavioral and neural signatures within a cognitive architecture
AU - Fechner, Hanna B.
AU - Pachur, Thorsten
AU - Schooler, Lael J.
AU - Mehlhorn, Katja
AU - Battal, Ceren
AU - Volz, Kirsten G.
AU - Borst, Jelmer P.
N1 - Funding Information:
This work was supported by a grant from the German Academic Exchange Service (DAAD), the Center for Adaptive Behavior and Cognition (ABC) and the Center for Adaptive Rationality (ARC) at the Max Planck Institute for Human Development, the International Max Planck Research Network on Aging (MaxNetAging), and the Werner Reichardt Centre for Integrative Neuroscience (CIN) at the Eberhard Karls University of Tübingen . The CIN is an Excellence Cluster funded by the Deutsche Forschungsgemeinschaft (DFG) within the framework of the Excellence Initiative (EXC 307). We thank John R. Anderson and his research group for hosting the first author at Carnegie Mellon University, where substantial proportions of the data analysis and computational modeling were conducted. We thank Anita Todd for editing the manuscript.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - 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.
AB - 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.
KW - ACT-R
KW - Computational modeling
KW - Decision making
KW - Memory
KW - Neuroimaging
KW - Recognition heuristic
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U2 - 10.1016/j.cognition.2016.08.011
DO - 10.1016/j.cognition.2016.08.011
M3 - Article
C2 - 27597646
AN - SCOPUS:84984817875
VL - 157
SP - 77
EP - 99
JO - Cognition
JF - Cognition
SN - 0010-0277
ER -