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Samuel J. Gershman

Samuel J. Gershman

· Professor of Psychology

Harvard University · Human Development and Psychology

Active 2009–2026

h-index82
Citations26.2k
Papers493245 last 5y
Funding$39.6M

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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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 authorCorresponding

    Cells 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 authorCorresponding
  • Rationally inattentive intertemporal choice

    Nature Communications · 2020 · 65 citations

    1st authorCorresponding

    Discounting 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

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Labs

Education

  • Ph.D., Cognitive Psychology

    University of Pennsylvania

    2009
  • B.A., Psychology

    Harvard University

    2004

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