Abstract
Organisms must act in the face of sensory, motor, and reward uncertainty stemming from a pandemonium of stochasticity and missing information. In many tasks, organisms can make better decisions if they have at their disposal a representation of the uncertainty associated with task-relevant variables. We formalize this problem using Bayesian decision theory and review recent behavioral and neural evidence that the brain may use knowledge of uncertainty, confidence, and probability. ©
Original language | English (US) |
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Pages (from-to) | 205-220 |
Number of pages | 16 |
Journal | Annual Review of Neuroscience |
Volume | 37 |
DOIs | |
State | Published - Jul 2014 |
Keywords
- Bayesian inference
- Decision making
- Perception
- Population encoding
ASJC Scopus subject areas
- General Neuroscience