## Bayesian Brain: Probabilistic Approaches to Neural CodingA Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering experimental data. Bayesian Brain brings together contributions from both experimental and theoretical neuroscientists that examine the brain mechanisms of perception, decision making, and motor control according to the concepts of Bayesian estimation.After an overview of the mathematical concepts, including Bayes' theorem, that are basic to understanding the approaches discussed, contributors discuss how Bayesian concepts can be used for interpretation of such neurobiological data as neural spikes and functional brain imaging. Next, contributors examine the modeling of sensory processing, including the neural coding of information about the outside world. Finally, contributors explore dynamic processes for proper behaviors, including the mathematics of the speed and accuracy of perceptual decisions and neural models of belief propagation. |

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### Contents

1 A Probability Primer | 3 |

Part II Reading Neural Codes | 15 |

2 Spike Coding | 17 |

3 LikelihoodBased Approaches to Modeling the Neural Code | 53 |

4 Combining Order Statistics with Bayes Theorem for MillisecondbyMillisecond Decoding of Spike Trains | 71 |

5 Bayesian Treatments of Neuroimaging Data | 93 |

Part III Making Sense of the World | 113 |

6 Population Codes | 115 |

9 Bayesian Models of Sensory Cue Integration | 189 |

Part IV Making Decisions and Movements | 207 |

A Mathematical Primer | 209 |

11 Neural Models of Bayesian Belief Propagation | 239 |

12 Optimal Control Theory | 269 |

13 Bayesian Statistics and Utility Functions in Sensorimotor Control | 299 |

Contributors | 321 |

324 | |

7 Computing with Population Codes | 131 |

8 Efficient Coding of Visual Scenes by Grouping and Segmentation | 145 |

### Other editions - View all

Bayesian Brain: Probabilistic Approaches to Neural Coding Kenji Doya,Shin Ishii,Alexandre Pouget No preview available - 2011 |