LEADER 00000cam a2200733Ia 4500 
001    ocn162574061 
003    OCoLC 
005    20160527041028.9 
006    m     o  d         
007    cr cn||||||||| 
008    070806s2007    ne a    ob    001 0 eng d 
019    659549740|a912946973 
020    9780123725608 
020    0123725607 
020    9780080466507|q(electronic book) 
020    0080466508|q(electronic book) 
020    9786610728992 
020    6610728992 
035    (OCoLC)162574061|z(OCoLC)659549740|z(OCoLC)912946973 
037    116398:116496|bElsevier Science & Technology|nhttp://
       www.sciencedirect.com 
040    OPELS|beng|epn|cOPELS|dOCLCG|dOCLCQ|dN$T|dIDEBK|dOCLCQ
       |dCUS|dOCLCQ|dCHVBK|dOCLCO|dOCLCQ|dOCLCO|dNLGGC|dDEBSZ
       |dYDXCP|dOCLCQ|dS3O|dDHA|dOCLCO|dOCLCQ|dOCLCA 
049    RIDW 
050  4 RC386.6.B7|bS73 2007eb 
082 04 616.8/04754|222 
082 04 611.810222|222 
090    RC386.6.B7|bS73 2007eb 
245 00 Statistical parametric mapping :|bthe analysis of 
       funtional brain images /|cedited by Karl Friston, John 
       Ashburner, Stefan Kiebel, Thomas Nichols, William Penny. 
250    First edition. 
264  1 Amsterdam ;|aBoston :|bElsevier/Academic Press,|c2007. 
300    1 online resource (vii, 647 pages) :|billustrations (some 
       color) 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
340    |gpolychrome|2rdacc 
347    text file|2rdaft 
504    Includes bibliographical references and index. 
505 0  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. 
520    In an age where the amount of data collected from brain 
       imaging is increasing constantly, it is of critical 
       importance to analyse those data within an accepted 
       framework to ensure proper integration and comparison of 
       the information collected. This book describes the ideas 
       and procedures that underlie the analysis of signals 
       produced by the brain. The aim is to understand how the 
       brain works, in terms of its functional architecture and 
       dynamics. This book provides the background and 
       methodology for the analysis of all types of brain imaging
       data, from functional magnetic resonance imaging to 
       magnetoencephalography. Critically, Statistical Parametric
       Mapping provides a widely accepted conceptual framework 
       which allows treatment of all these different modalities. 
       This rests on an understanding of the brain's functional 
       anatomy and the way that measured signals are caused 
       experimentally. The book takes the reader from the basic 
       concepts underlying the analysis of neuroimaging data to 
       cutting edge approaches that would be difficult to find in
       any other source. Critically, the material is presented in
       an incremental way so that the reader can understand the 
       precedents for each new development. This book will be 
       particularly useful to neuroscientists engaged in any form
       of brain mapping; who have to contend with the real-world 
       problems of data analysis and understanding the techniques
       they are using. It is primarily a scientific treatment and
       a didactic introduction to the analysis of brain imaging 
       data. It can be used as both a textbook for students and 
       scientists starting to use the techniques, as well as a 
       reference for practicing neuroscientists. The book also 
       serves as a companion to the software packages that have 
       been developed for brain imaging data analysis. * An 
       essential reference and companion for users of the SPM 
       software * Provides a complete description of the concepts
       and procedures entailed by the analysis of brain images * 
       Offers full didactic treatment of the basic mathematics 
       behind the analysis of brain imaging data * Stands as a 
       compendium of all the advances in neuroimaging data 
       analysis over the past decade * Adopts an easy to 
       understand and incremental approach that takes the reader 
       from basic statistics to state of the art approaches such 
       as Variational Bayes * Structured treatment of data 
       analysis issues that links different modalities and models
       * Includes a series of appendices and tutorial-style 
       chapters that makes even the most sophisticated approaches
       accessible. 
588 0  Print version record. 
590    eBooks on EBSCOhost|bEBSCO eBook Subscription Academic 
       Collection - North America 
650  0 Brain mapping|0https://id.loc.gov/authorities/subjects/
       sh88004413|xStatistical methods.|0https://id.loc.gov/
       authorities/subjects/sh2001008679 
650  0 Brain|xImaging|0https://id.loc.gov/authorities/subjects/
       sh2008117487|xStatistical methods.|0https://id.loc.gov/
       authorities/subjects/sh2001008679 
650  2 Brain Mapping|xmethods.|0https://id.nlm.nih.gov/mesh/
       D001931Q000379 
650  2 Image Processing, Computer-Assisted|xmethods.|0https://
       id.nlm.nih.gov/mesh/D007091Q000379 
650  2 Magnetic Resonance Imaging|xmethods.|0https://
       id.nlm.nih.gov/mesh/D008279Q000379 
650  2 Models, Neurological.|0https://id.nlm.nih.gov/mesh/D008959
650  2 Models, Statistical.|0https://id.nlm.nih.gov/mesh/D015233 
650  7 Brain mapping.|2fast|0https://id.worldcat.org/fast/837764 
650  7 Statistics.|2fast|0https://id.worldcat.org/fast/1132103 
650  7 Brain|xImaging.|2fast|0https://id.worldcat.org/fast/837635
655  4 Electronic books. 
700 1  Friston, K. J.|q(Karl J.),|0https://id.loc.gov/authorities
       /names/no2005069793|eeditor. 
700 1  Ashburner, John,|0https://id.loc.gov/authorities/names/
       no2014088518|eeditor. 
700 1  Kiebel, Stefan,|eeditor. 
700 1  Nichols, Thomas,|eeditor. 
700 1  Penny, William D.,|eeditor. 
776 08 |iPrint version:|tStatistical parametric mapping.|b1st ed.
       |dAmsterdam ; Boston : Elsevier/Academic Press, 2007
       |z9780123725608|z0123725607|w(DLC)  2006933665
       |w(OCoLC)104803228 
856 40 |uhttps://rider.idm.oclc.org/login?url=http://
       search.ebscohost.com/login.aspx?direct=true&scope=site&
       db=nlebk&AN=187303|zOnline eBook. Access restricted to 
       current Rider University students, faculty, and staff. 
856 42 |3Instructions for reading/downloading this eBook|uhttp://
       guides.rider.edu/ebooks/ebsco 
901    MARCIVE 20231220 
948    |d20160615|cEBSCO|tebscoebooksacademic|lridw 
994    92|bRID