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Bayesian BrainProbabilistic Approaches to Neural Coding$
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Kenji Doya, Shin Ishii, Alexandre Pouget, and Rajesh P.N. Rao

Print publication date: 2006

Print ISBN-13: 9780262042383

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262042383.001.0001

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Bayesian Statistics and Utility Functions in Sensorimotor Control

Bayesian Statistics and Utility Functions in Sensorimotor Control

(p.299) 13 Bayesian Statistics and Utility Functions in Sensorimotor Control
Bayesian Brain

Konrad P. Körding

Daniel M. Wolpert

The MIT Press

This chapter, which investigates how decision theory can be applied to the study of sensorimotor control, focuses on the concepts behind Bayesian decision making and their application to decisions in human movement. First, it discusses the concept of a utility function and how it quantifies the relative values of different decision outcomes. The chapter then examines whether people use Bayesian statistics to estimate the values of variables important to movement, how people’s utility function is defined, and how people represent probabilities and combine them with utilities to choose how to move.

Keywords:   decision, sensorimotor control, Bayesian decision making, movement, utility function, Bayesian statistics

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