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Bayesian brain : probabilistic approaches to neural coding / Kenji Doya [and others].

MIT Press Direct (eBooks) Available online

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Format:
Book
Contributor:
Doya, Kenji.
Series:
Computational neuroscience
Language:
English
Subjects (All):
Brain.
Neurons.
Bayesian statistical decision theory.
Physical Description:
1 online resource (xiii, 326 pages) : illustrations.
Place of Publication:
Cambridge, Mass. : MIT Press, [2007]
System Details:
text file
Summary:
Experimental and theoretical neuroscientists use Bayesian approaches to analyse the brain mechanisms of perception decision-making, and motor control.
Contents:
1 A Probability Primer / Kenji Doya, Shin Ishii 3
1.1 What Is Probability? 3
1.2 Bayes Theorem 6
1.3 Measuring Information 6
1.4 Making an Inference 8
1.5 Learning from Data 10
1.6 Graphical Models and Other Bayesian Algorithms 13
II Reading Neural Codes 15
2 Spike Coding / Adrienne Fairhall 17
2.1 Spikes: What Kind of Code? 17
2.2 Encoding and Decoding 25
2.3 Adaptive Spike Coding 42
3 Likelihood-Based Approaches to Modeling the Neural Code / Jonathan Pillow 53
3.1 The Neural Coding Problem 53
3.2 Model Fitting with Maximum Likelihood 55
3.3 Model Validation 64
4 Combining Order Statistics with Bayes Theorem for Millisecond-by-Millisecond Decoding of Spike Trains / Barry J. Richmond, Matthew C. Wiener 71
4.2 An Approach to Decoding 72
4.3 Simplifying the Order Statistic Model 82
5 Bayesian Treatments of Neuroimaging Data / Will Penny, Karl Friston 93
5.2 Attention to Visual Motion 94
5.3 The General Linear Model 95
5.4 Parameter Estimation 98
5.5 Posterior Probability Mapping 101
5.6 Dynamic Causal Modeling 104
III Making Sense of the World 113
6 Population Codes / Alexandre Pouget, Richard S. Zemel 115
6.2 Coding and Decoding 116
6.3 Representing Uncertainty with Population Codes 120
7 Computing with Population Codes / Peter Latham, Alexandre Pouget 131
7.1 Computing, Invariance, and Throwing Away Information 131
7.2 Computing Functions with Networks of Neurons: A General Algorithm 132
7.3 Efficient Computing; Qualitative Analysis 136
7.4 Efficient Computing; Quantitative Analysis 137
8 Efficient Coding of Visual Scenes by Grouping and Segmentation / Tai Sing Lee, Alan L. Yuille 145
8.2 Computational Theories for Scn̈e Segmentation 148
8.3 A Computational Algorithm for the Weak-Membrane Model 152
8.4 Generalizations of the Weak-Membrane Model 156
8.5 Biological Evidence 161
8.6 Summary and Discussion 180
9 Bayesian Models of Sensory Cue Integration / David C. Knul 189
9.2 Psychophysical Tests of Bayesian Cue Integration 191
9.3 Psychophysical Tests of Bayesian Priors 195
9.4 Mixture models. Priors, and Cue Integration 199
IV Making Decisions and Movements 207
10 The Speed and Accuracy of a Simple Perceptual Decision: A Mathematical Primer / Michael N. Shadlen, Timothy D. Hanks, Anne K. Churchland, Roozbeh Kiani, Tianming Yang 209
10.2 The Diffusion-to-Bound Framework 210
10.3 Derivation of Choice and Reaction Time Functions 213
10.4 Implementation of Diffusion-to-Bound Framework in the Brain 226
11 Neural Models of Bayesian Belief Propagation / Rajesh P.N. Rao 239
11.2 Bayesian Inference through Belief Propagation 240
11.3 Neural Implementations of Belief Propagation 244
11.4 Results 248
12 Optimal Control Theory / Emanuel Todorov 269
12.1 Discrete Control: Bellman Equations 270
12.2 Continuous Control: Hamilton-Jacobi-Bellman Equations 273
12.3 Deterministic Control: Pontryagin's Maximum Principle 277
12.4 Linear-Quadratic-Gaussian Control: Riccati Equations 283
12.5 Optimal Estimation: Kalman Filter 287
12.6 Duality of Optimal Control and Optimal Estimation 290
12.7 Optimal Control as a Theory of Biological Movement 294
13 Bayesian Statistics and Utility Functions in Sensorimotor Control / Konrad P. Kording, Daniel M. Wolpert 299
13.2 Motor Decisions 301
13.3 Utility: The Cost of Using our Muscles 308
13.4 Neurobiology 314.
Notes:
OCLC-licensed vendor bibliographic record.
ISBN:
9780262294188
0262294184
9781435624672
143562467X
OCLC:
191730642
Access Restriction:
Restricted for use by site license.

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