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The bounded log-odds model of frequency and probability distortion
NEUROSCIENCE The bounded log-odds model of frequency and probability distortion ABSTRACT People systematically distort probability and frequency information in decision-making and in many other perceptual, motor and cognitive tasks. We show that...
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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...
More infoDecision Making under Stress: acute stress influences how we learn to trust others
NEUROSCIENCE Decision Making under Stress: acute stress influences how we learn to trust others ABSTRACT Stress—a ubiquitous part of everyday life—can affect our daily decisions. We explore how acute stress changes choice behavior in a trust...
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 infoThinking Like A Trader
NEUROSCIENCE Thinking Like A Trader ABSTRACT We know surprisingly little about the role of emotions in decision-making, and nearly nothing about how we can change those emotions, and thereby our choices. In a series of studies, we asked...
More infoDynamical analysis of value coding
NEUROSCIENCE Dynamical analysis of value coding ABSTRACT Information coding in the brain is often viewed in terms of equilibrium levels of activity, but neural circuits exhibit marked temporal dynamics during the decision process. Significant...
More infoA Bayesian model of insight
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 infoCostly information sampling
NEUROSCIENCE Costly information sampling ABSTRACT Theories of optimal information sampling assert that the decision to gather information should take into account accrual costs: time, energy, and money. This project explored how effectively...
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