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Statistical Parametric Mapping: The Analysis of Functional Brain Images: The Analysis of Functional Brain Images(English)

Statistical Parametric Mapping: The Analysis of Functional Brain Images: The Analysis of Functional Brain Images(English)

          
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About the Book

Statistical Parametric Mapping: The Analysis of Functional Brain Images

Table of Contents:
Part 1: Introduction Chapter 1: A short history of SPM Chapter 2: Statistical parametric mapping Chapter 3: Modelling brain responses Part 2: Computational anatomy Chapter 4: Rigid Body Registration Chapter 5: Non-linear Registration Chapter 6: Segmentation Chapter 7: Voxel-Based Morphometry Part 3: General linear models Chapter 8: The General Linear Model Chapter 9: Contrasts and Classical Inference Chapter 10: Covariance Components Chapter 11: Hierarchical Models Chapter 12: Random Effects Analysis Chapter 13: Analysis of Variance Chapter 14: Convolution Models for fMRI Chapter 15: Efficient Experimental Design for fMRI Chapter 16: Hierarchical models for EEG and MEG Part 4: Classical inference Chapter 17: Parametric procedures Chapter 18: Random Field Theory Chapter 19: Topological Inference Chapter 20: False Discovery Rate procedures Chapter 21: Non-parametric procedures Part 5: Bayesian inference Chapter 22: Empirical Bayes and hierarchical models Chapter 23: Posterior probability maps Chapter 24: Variational Bayes Chapter 25: Spatio-temporal models for fMRI Chapter 26: Spatio-temporal models for EEG Part 6: Biophysical models Chapter 27: Forward models for fMRI Chapter 28: Forward models for EEG Chapter 29: Bayesian inversion of EEG models Chapter 30: Bayesian inversion for induced responses Chapter 31: Neuronal models of ensemble dynamics Chapter 32: Neuronal models of energetics Chapter 33: Neuronal models of EEG and MEG Chapter 34: Bayesian inversion of dynamic models Chapter 35: Bayesian model selection and averaging Part 7: Connectivity Chapter 36: Functional integration Chapter 37: Functional connectivity: eigenimages and multivariate analyses Chapter 38: Effective Connectivity Chapter 39: Non-linear coupling and kernels Chapter 40: Multivariate autoregressive models Chapter 41: Dynamic Causal Models for fMRI Chapter 42: Dynamic causal models for EEG Chapter 43: Dynamic Causal Models and Bayesian selection Appendices Linear models and inference Dynamical systems Expectation maximization Variational Bayes under the Laplace approximation Kalman filtering Random field theory Index Color Plates


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Product Details
  • ISBN-13: 9780123725608
  • Publisher: Elsevier Science Publishing Co Inc
  • Publisher Imprint: Academic Press Inc
  • Depth: 38
  • Height: 276 mm
  • No of Pages: 688
  • Series Title: English
  • Sub Title: The Analysis of Functional Brain Images
  • Width: 216 mm
  • ISBN-10: 0123725607
  • Publisher Date: 02 Nov 2006
  • Binding: Hardback
  • Edition: 1
  • Language: English
  • Returnable: Y
  • Spine Width: 39 mm
  • Weight: 2310 gr


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