NEUROSCIENCE Risk preferences in New Yorkers’ everyday decisions. Correlation of risk preferences across different decision-making domains. ABSTRACT Most of the important decisions that we make in life are made under conditions of uncertainty...
More infoEnvisioning the Improbable: Judgment and Strategy in Heavy-Tailed Contexts
NEUROSCIENCE Envisioning the Improbable: Judgment and Strategy in Heavy-Tailed Contexts ABSTRACT This multi-method research seeks to increase understanding of the judgment, behavior, and performance of individuals and organizations in...
More infoCortical computations underlying decision-making
NEUROSCIENCE Cortical computations underlying decision-making ABSTRACT Relative value coding is governed by divisive normalization, a computational algorithm widely described in sensory cortices, suggesting a common cortical mechanism for...
More infoEconomic decision-making in Drosophila larvae
NEUROSCIENCE Economic decision-making in Drosophila larvae ABSTRACT The goal of this project is two-fold. First, we use tools from microeconomics to characterize the choices of wild type Drosophila larvae as they tradeoff goods (dark and food) in...
More infoNew Research from NYU, Princeton and UCL Researchers Published in PLoS Computational Biology
New Research from NYU, Princeton and UCL Researchers Published in PLoS Computational Biology February 16, 2017 The decisions we make are only as good as the information we base those decisions off of, but a lot of that information comes to us via...
More infoSuboptimal Criterion Learning in Static and Dynamic Environments
NEUROSCIENCE Suboptimal Criterion Learning in Static and Dynamic Environments AUTHORS: LElyse H. Norton, Stephen M. Fleming, Nathaniel D. Daw, and Michael S. Landy ABSTRACT Humans often make decisions based on uncertain...
More infoNature
Road trips, music, festivals & fun await you in the City
More infoEfficient coding in decision circuits
NEUROSCIENCE Efficient coding in decision circuits ABSTRACT A fundamental feature of neurobiological systems is adaptive coding, where neural activity reflects the recent history of information processing. Such adaptation is thought to be...
More infoLink
Choice-theoretic foundations of the divisive normalization model
NEUROSCIENCE Choice-theoretic foundations of the divisive normalization model AUTHORS: Kai Steverson, Adam Brandenburger, and Paul Glimcher ABSTRACT In “Choice-theoretic foundations of the divisive normalization model” (just published in...
More infoMeasuring people’s internal model of motor error distribution
NEUROSCIENCE Measuring people’s internal model of motor error distribution ABSTRACT A good decision maker in perception and action (e.g. a good surgeon, a good basketball player) needs to compensate for the irreducible errors in her own movement...
More info