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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More infoMeasuring people’s internal models of motor error distribution
NEUROSCIENCE Measuring people’s internal models of motor error distribution ABSTRACT A good decision maker in perception and action (e.g. a good surgeon) needs to allow for the irreducible errors in her own movement. In simple reaching tasks, the...
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Costly 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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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 infoChoice-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 infoAn Analysis of Decision under Risk in Rats
NEUROSCIENCE An Analysis of Decision under Risk in Rats AUTHORS Christine Constantinople ABSTRACT In 1979, Daniel Kahneman and Amos Tversky published a ground-breaking paper titled ‘‘Prospect Theory: An Analysis of Decision under Risk,’’ which...
More infoCognitive Control Mode Predicts Behavioral Expression of Model-Based Reinforcement-Learning
NEUROSCIENCE Cognitive Control Mode Predicts Behavioral Expression of Model-Based Reinforcement-Learning ABSTRACT A converging body of work suggests that cognitive control operates via two distinct operating modes – proactive control and reactive...
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