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Research Areas:

Cognition & Cognitive Neuroscience | Developmental Science | 听Social & Personality | Quantitative & Modelling

Research Summary:

Prof. Shultz is interested in cognitive science, cognitive development, decision-making, cognitive consistency, evolution and learning, and computational and mathematical modeling. Current projects include decision making, integration of Bayesian and neural network approaches to psychological development, and evolution of early hominin species.

Selected References:

Shultz, T. R., & Nobandegani, A. S. (2021, In press). A computational model of infant learning and reasoning with probabilities. Psychological Review.

Montrey, M., & Shultz, T. R. (2021, In press). Copy-the-ingroup: group membership trumps perceived reliability, warmth, and competence in a social learning task. Psychological Science.

Montrey, M., & Shultz, T. R. (2020). The evolution of high-fidelity social learning. Proceedings of the Royal Society B: Biological Sciences, 287 (1928), 1-8.

Nobandegani, A. S., & Shultz, T. R. (2020). A resource-rational, process-level account of the St. Petersburg Paradox. Topics in Cognitive Science, 12, 417-432.

Helfer, P., & Shultz, T. R. (2020). A computational model of systems memory reconsolidation and extinction. Hippocampus, 30, 659-677.

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