
Samuel J. Gershman
· Professor of PsychologyHarvard University · Human Development and Psychology
Active 2009–2026
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About
Samuel J. Gershman is a Professor of Psychology at Harvard University, based in the Department of Psychology and the Northwest Laboratory located at 52 Oxford Street, Cambridge, MA. His research aims to understand how richly structured knowledge about the environment is acquired and how this knowledge aids adaptive behavior. The Gershman lab employs a combination of behavioral, neuroimaging, and computational techniques to explore these questions. Gershman received his B.A. in Neuroscience and Behavior from Columbia University in 2007 and his Ph.D. in Psychology and Neuroscience from Princeton University in 2013. Following his doctoral studies, he was a postdoctoral fellow in the Department of Brain and Cognitive Sciences at MIT from 2013 to 2015. His research interests include learning, memory, decision making, and computational neuroscience.
Research topics
- Computer Science
- Psychology
- Cognitive psychology
- Neuroscience
- Machine Learning
- Artificial Intelligence
- Cognitive science
- Biology
- Economics
- Evolutionary biology
Selected publications
A Unified Framework for Dopamine Signals across Timescales
Cell · 2020 · 335 citations
Hippocampal remapping as hidden state inference
eLife · 2020 · 174 citations
Senior authorCorrespondingCells in the hippocampus tuned to spatial location (place cells) typically change their tuning when an animal changes context, a phenomenon known as remapping. A fundamental challenge to understanding remapping is the fact that what counts as a ''context change'' has never been precisely defined. Furthermore, different remapping phenomena have been classified on the basis of how much the tuning changes after different types and degrees of context change, but the relationship between these variab…
Structured Event Memory: A neuro-symbolic model of event cognition.
Psychological Review · 2020 · 172 citations
Senior authorCorresponding(SEM) model of event cognition, which accounts for human abilities in event segmentation, memory, and generalization. SEM is derived from a probabilistic generative model of event dynamics defined over structured symbolic scenes. By embedding symbolic scene representations in a vector space and parametrizing the scene dynamics in this continuous space, SEM combines the advantages of structured and neural network approaches to high-level cognition. Using probabilistic reasoning over this generati…
Resource-rational decision making
Current Opinion in Behavioral Sciences · 2021 · 171 citations
Senior authorCorrespondingRationally inattentive intertemporal choice
Nature Communications · 2020 · 65 citations
1st authorCorrespondingDiscounting of future rewards is traditionally interpreted as evidence for an intrinsic preference in favor of sooner rewards. However, temporal discounting can also arise from internal uncertainty in value representations of future events, if one assumes that noisy mental simulations of the future are rationally combined with prior beliefs. Here, we further develop this idea by considering how simulation noise may be adaptively modulated by task demands, based on principles of rational inattent…
Recent grants
Towards a Unified Framework for Dopamine Signaling in the Striatum
NIH · $32.4M · 2019–2025
Towards a Unified Framework for Dopamine Signaling in the Striatum
NIH · $7.2M · 2019–2024
Frequent coauthors
- 61 shared
Joshua B. Tenenbaum
Massachusetts Institute of Technology
- 51 shared
Eric Schulz
Max Planck Institute for Biological Cybernetics
- 39 shared
Matthew Botvinick
- 38 shared
Momchil S. Tomov
Harvard University
- 31 shared
Tomer Ullman
Harvard University
- 31 shared
Kenneth A. Norman
Princeton University
- 30 shared
Ishita Dasgupta
- 29 shared
Rahul Bhui
Labs
Not provided
Education
- 2009
Ph.D., Cognitive Psychology
University of Pennsylvania
- 2004
B.A., Psychology
Harvard University
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