Bayesian Brain: Probabilistic Approaches to Neural Coding
Bayesian Brain: Probabilistic Approaches to Neural Coding
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Abstract
A 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. This book 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, they examine the modeling of sensory processing, including the neural coding of information about the outside world, and finally, they 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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Front Matter
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Part I Introduction
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PART II Reading Neural Codes
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2
Spike Coding
Adrienne Fairhall
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3
Likelihood-Based Approaches to Modeling the Neural Code
Jonathan Pillow
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4
Combining Order Statistics with Bayes Theorem for Millisecond-by-Millisecond Decoding of Spike Trains
Barry J. Richmond andMatthew C. Wiener
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5
Bayesian Treatments of Neuroimaging Data
Will Penny andKarl Friston
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2
Spike Coding
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PART III Making Sense of the World
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Part IV Making Decisions and Movements
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10
The Speed and Accuracy of a Simple Perceptual Decision: A Mathematical Primer
Michael N. Shadlen and others
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11
Neural Models of Bayesian Belief Propagation
Rajesh P. N. Rao
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12
Optimal Control Theory
Emanuel Todorov
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13
Bayesian Statistics and Utility Functions in Sensorimotor Control
Konrad P. Körding andDaniel M. Wolpert
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10
The Speed and Accuracy of a Simple Perceptual Decision: A Mathematical Primer
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End Matter
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