Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture.
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.
Max Planck Institute for Human Development, Center for Adaptive Behavior and Cognition, Lentzeallee 94, 14195 Berlin, Germany; Carnegie Mellon University, Department of Psychology, 5000 Forbes Ave, Pittsburgh, PA 15213, USA. Electronic address: hfechner@mpib-berlin.mpg.de.
Hanna B
HB
Fechner
Max Planck Institute for Human Development, Center for Adaptive Rationality, Lentzeallee 94, 14195 Berlin, Germany. Electronic address: pachur@mpib-berlin.mpg.de.
Thorsten
T
Pachur
Syracuse University, Department of Psychology, 301 Hall of Languages, Syracuse, NY 13244, USA; Max Planck Institute for Human Development, Center for Adaptive Behavior and Cognition, Lentzeallee 94, 14195 Berlin, Germany. Electronic address: lschoole@syr.edu.
Lael J
LJ
Schooler
University of Groningen, Department of Artificial Intelligence, Nijenborgh 9, 9747 AG Groningen, The Netherlands; Carnegie Mellon University, Department of Psychology, 5000 Forbes Ave, Pittsburgh, PA 15213, USA. Electronic address: s.k.mehlhorn@rug.nl.
Katja
K
Mehlhorn
University of Trento, Center for Mind/Brain Sciences, Corso Bettini 31, 38068 Rovereto, TN, Italy; University of Tübingen, Werner Reichardt Centre for Integrative Neuroscience, Otfried-Müller-Straβe 25, 72076 Tübingen, Germany. Electronic address: ceren.battal@unitn.it.
Ceren
C
Battal
University of Tübingen, Werner Reichardt Centre for Integrative Neuroscience, Otfried-Müller-Straβe 25, 72076 Tübingen, Germany. Electronic address: kirsten.volz@cin.uni-tuebingen.de.
Kirsten G
KG
Volz
University of Groningen, Department of Artificial Intelligence, Nijenborgh 9, 9747 AG Groningen, The Netherlands; Carnegie Mellon University, Department of Psychology, 5000 Forbes Ave, Pittsburgh, PA 15213, USA. Electronic address: j.p.borst@rug.nl.
Jelmer P
JP
Borst
D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D003071:Cognition / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D005260:Female; D000066506:Heuristics / Q000502:physiology*; D006801:Humans; D007600:Judgment / Q000502:physiology; D008279:Magnetic Resonance Imaging; D008297:Male; D011939:Mental Recall / Q000502:physiology; D008959:Models, Neurological; D008960:Models, Psychological; D011930:Reaction Time; D021641:Recognition, Psychology / Q000502:physiology*; D055815:Young Adult
ACT-R; Computational modeling; Decision making; Memory; Neuroimaging; Recognition heuristic