NEUROSCIENCE A Bayesian model of insight ABSTRACT We are building a computational model of insight. The core of this model permits actions to dissociate from intentions. Our model provides a Bayesian “definition” of insight as the probability...
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More infoAcute Stress and Reinforcement Learning
NEUROSCIENCE Acute Stress and Reinforcement Learning ABSTRACT The physiological response evoked by short-lived stressful events, referred to as acute stress, impacts human decision-making. Past studies assume that stress causes people to fall...
More infoSaving the masses: The impact of perceived efficacy on charitable giving to single vs. multiple beneficiaries
NEUROSCIENCE Saving the masses: The impact of perceived efficacy on charitable giving to single vs. multiple beneficiaries AUTHORS: Professor Vicki Morwitz and Professor Eesha Sharma ABSTRACT People are more generous toward...
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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 infoDynamic estimation of task-relevant variance in movement under risk
NEUROSCIENCE Dynamic estimation of task-relevant variance in movement under risk AUTHORS: Michael Landy, Julia Trommershäuser, Nathaniel Daw ABSTRACT Humans take into account their own movement variability as well as potential consequences...
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More infoRisk preferences in New Yorkers’ everyday decisions. Correlation of risk preferences across different decision-making domains.
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 infoModeling and Measuring Costs of Learning
NEUROSCIENCE Modeling and Measuring Costs of Learning ABSTRACT Theoretical and experimental research is ongoing on models of imperfect perception and how it is impacted by the incentive to learn. The project provides new characterizations of the...
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 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...
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