Cover Image

Statistical parametric mapping : the analysis of funtional brain images /

Other Authors: Nichols, Thomas,
Format: Book
Language:English
Published: Amsterdam ; Boston : Elsevier/Academic Press, 2007.
Edition:First edition.
Subjects:
Brain mapping > Statistical methods.
Brain > Imaging > Statistical methods.
Brain Mapping > methods.
Image Processing, Computer-Assisted > methods.
Magnetic Resonance Imaging > methods.
Models, Neurological.
Models, Statistical.
Eletroencefalografia.
Online-Publikation.
Online Access:http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=187303
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245 0 0 |a Statistical parametric mapping :  |b the analysis of funtional brain images /  |c edited by Karl Friston, John Ashburner, Stefan Kiebel, Thomas Nichols, William Penny. 
250 |a First edition. 
260 |a Amsterdam ;  |b Elsevier/Academic Press,  |c 2007.  |a Boston : 
300 |a 1 online resource (vii, 647 pages) :  |b illustrations (some color) 
504 |a Includes bibliographical references and index. 
505 0 |a INTRODUCTION -- A short history of SPM. -- Statistical parametric mapping. -- Modelling brain responses. -- SECTION 1: COMPUTATIONAL ANATOMY -- Rigid-body Registration. -- Nonlinear Registration. -- Segmentation. -- Voxel-based Morphometry. -- SECTION 2: GENERAL LINEAR MODELS -- The General Linear Model. -- Contrasts & Classical Inference. -- Covariance Components. -- Hierarchical models. -- Random Effects Analysis. -- Analysis of variance. -- Convolution models for fMRI. -- Efficient Experimental Design for fMRI. -- Hierarchical models for EEG/MEG. -- SECTION 3: CLASSICAL INFERENCE -- Parametric procedures for imaging. -- Random Field Theory & inference. -- Topological Inference. -- False discovery rate procedures. -- Non-parametric procedures. -- SECTION 4: BAYESIAN INFERENCE -- Empirical Bayes & hierarchical models. -- Posterior probability maps. -- Variational Bayes. -- Spatiotemporal models for fMRI. -- Spatiotemporal models for EEG. -- SECTION 5: BIOPHYSICAL MODELS -- Forward models for fMRI. -- Forward models for EEG and MEG. -- Bayesian inversion of EEG models. -- Bayesian inversion for induced responses. -- Neuronal models of ensemble dynamics. -- Neuronal models of energetics. -- Neuronal models of EEG and MEG. -- Bayesian inversion of dynamic models -- Bayesian model selection & averaging. -- SECTION 6: CONNECTIVITY -- Functional integration. -- Functional Connectivity. -- Effective Connectivity. -- Nonlinear coupling and Kernels. -- Multivariate autoregressive models. -- Dynamic Causal Models for fMRI. -- Dynamic Causal Models for EEG. -- Dynamic Causal Models & Bayesian selection. -- APPENDICES -- Linear models and inference. -- Dynamical systems. -- Expectation maximisation. -- Variational Bayes under the Laplace approximation. -- Kalman Filtering. -- Random Field Theory. 
650 0 |a Brain mapping  |x Statistical methods. 
650 0 |a Brain  |x Imaging  |x Statistical methods. 
650 2 |a Brain Mapping  |x methods. 
650 2 |a Image Processing, Computer-Assisted  |x methods. 
650 2 |a Magnetic Resonance Imaging  |x methods. 
650 2 |a Models, Neurological. 
650 2 |a Models, Statistical. 
650 7 |a Eletroencefalografia. 
650 7 |a Online-Publikation. 
700 1 |a Nichols, Thomas, 
856 4 0 |a Penny, William D.,  |u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=187303 
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