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Template Free Methods for the Statistical Analysis of FMRI Data

Template Free Methods for the Statistical Analysis of FMRI Data PDF Author: William Frederick Auffermann
Publisher:
ISBN:
Category : Magnetic resonance imaging
Languages : en
Pages : 258

Book Description


Template Free Methods for the Statistical Analysis of FMRI Data

Template Free Methods for the Statistical Analysis of FMRI Data PDF Author: William Frederick Auffermann
Publisher:
ISBN:
Category : Magnetic resonance imaging
Languages : en
Pages : 258

Book Description


Statistical Analysis of fMRI Data

Statistical Analysis of fMRI Data PDF Author: F. Gregory Ashby
Publisher: MIT Press
ISBN: 0262294419
Category : Medical
Languages : en
Pages : 349

Book Description
An overview of statistical methods for analyzing data from fMRI experiments. Functional magnetic resonance imaging (fMRI), which allows researchers to observe neural activity in the human brain noninvasively, has revolutionized the scientific study of the mind. An fMRI experiment produces massive amounts of highly complex data; researchers face significant challenges in analyzing the data they collect. This book offers an overview of the most widely used statistical methods of analyzing fMRI data. Every step is covered, from preprocessing to advanced methods for assessing functional connectivity. The goal is not to describe which buttons to push in the popular software packages but to help readers understand the basic underlying logic, the assumptions, the strengths and weaknesses, and the appropriateness of each method. The book covers all of the important current topics in fMRI data analysis, including the relation of the fMRI BOLD (blood oxygen-level dependent) response to neural activation; basic analyses done in virtually every fMRI article—preprocessing, constructing statistical parametrical maps using the general linear model, solving the multiple comparison problem, and group analyses; the most popular methods for assessing functional connectivity—coherence analysis and Granger causality; two widely used multivariate approaches, principal components analysis and independent component analysis; and a brief survey of other current fMRI methods. The necessary mathematics is explained at a conceptual level, but in enough detail to allow mathematically sophisticated readers to gain more than a purely conceptual understanding. The book also includes short examples of Matlab code that implement many of the methods described; an appendix offers an introduction to basic Matlab matrix algebra commands (as well as a tutorial on matrix algebra). A second appendix introduces multivariate probability distributions.

Statistical Analysis of fMRI Data, second edition

Statistical Analysis of fMRI Data, second edition PDF Author: F. Gregory Ashby
Publisher: MIT Press
ISBN: 0262354063
Category : Medical
Languages : en
Pages : 569

Book Description
A guide to all aspects of experimental design and data analysis for fMRI experiments, completely revised and updated for the second edition. Functional magnetic resonance imaging (fMRI), which allows researchers to observe neural activity in the human brain noninvasively, has revolutionized the scientific study of the mind. An fMRI experiment produces massive amounts of highly complex data for researchers to analyze. This book describes all aspects of experimental design and data analysis for fMRI experiments, covering every step—from preprocessing to advanced methods for assessing functional connectivity—as well as the most popular multivariate approaches. The goal is not to describe which buttons to push in the popular software packages but to help researchers understand the basic underlying logic, the assumptions, the strengths and weaknesses, and the appropriateness of each method. The field of fMRI research has advanced dramatically in recent years, in both methodology and technology, and this second edition has been completely revised and updated. Six new chapters cover experimental design, functional connectivity analysis through the methods of psychophysiological interactions and beta-series regression, decoding using multi-voxel pattern analysis, dynamic causal modeling, and representational similarity analysis. Other chapters offer new material on recently discovered problems related to head movements, the multivariate GLM, meta-analysis, and other topics. All complex derivations now appear at the end of the relevant chapter to improve readability. A new appendix describes how to build a design matrix with effect coding for group analysis. As in the first edition, MATLAB code is provided with which readers can implement many of the methods described.

The Statistical Analysis of Functional MRI Data

The Statistical Analysis of Functional MRI Data PDF Author: Nicole Lazar
Publisher: Springer Science & Business Media
ISBN: 0387781919
Category : Medical
Languages : en
Pages : 302

Book Description
The study of brain function is one of the most fascinating pursuits of m- ern science. Functional neuroimaging is an important component of much of the current research in cognitive, clinical, and social psychology. The exci- ment of studying the brain is recognized in both the popular press and the scienti?c community. In the pages of mainstream publications, including The New York Times and Wired, readers can learn about cutting-edge research into topics such as understanding how customers react to products and - vertisements (“If your brain has a ‘buy button,’ what pushes it?”, The New York Times,October19,2004),howviewersrespondtocampaignads(“Using M. R. I. ’s to see politics on the brain,” The New York Times, April 20, 2004; “This is your brain on Hillary: Political neuroscience hits new low,” Wired, November 12,2007),howmen and womenreactto sexualstimulation (“Brain scans arouse researchers,”Wired, April 19, 2004), distinguishing lies from the truth (“Duped,” The New Yorker, July 2, 2007; “Woman convicted of child abuse hopes fMRI can prove her innocence,” Wired, November 5, 2007), and even what separates “cool” people from “nerds” (“If you secretly like Michael Bolton, we’ll know,” Wired, October 2004). Reports on pathologies such as autism, in which neuroimaging plays a large role, are also common (for - stance, a Time magazine cover story from May 6, 2002, entitled “Inside the world of autism”).

Handbook of Functional MRI Data Analysis

Handbook of Functional MRI Data Analysis PDF Author: Russell A. Poldrack
Publisher: Cambridge University Press
ISBN: 1139498363
Category : Medical
Languages : en
Pages : 239

Book Description
Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Web-based Tutorial for Statistical Analysis of Functional Magnetic Resonance Imaging Data

Web-based Tutorial for Statistical Analysis of Functional Magnetic Resonance Imaging Data PDF Author: Ian Lai
Publisher:
ISBN:
Category :
Languages : en
Pages : 63

Book Description


Statistical Analysis of FMRI Data

Statistical Analysis of FMRI Data PDF Author: Yongmei Chen
Publisher:
ISBN:
Category : Magnetic resonance imaging
Languages : en
Pages : 190

Book Description


Statistical Parametric Mapping: The Analysis of Functional Brain Images

Statistical Parametric Mapping: The Analysis of Functional Brain Images PDF Author: William D. Penny
Publisher: Elsevier
ISBN: 0080466508
Category : Psychology
Languages : en
Pages : 689

Book Description
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

Handbook of Functional MRI Data Analysis

Handbook of Functional MRI Data Analysis PDF Author: Russell A. Poldrack
Publisher: Cambridge University Press
ISBN: 9780521517669
Category : Medical
Languages : en
Pages : 238

Book Description
Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook for Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM, and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling, and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Statistical Learning Methods for Group Analysis in FMRI Data

Statistical Learning Methods for Group Analysis in FMRI Data PDF Author: Arunava Samaddar
Publisher:
ISBN:
Category :
Languages : en
Pages : 262

Book Description
In this dissertation, we aim to answer three questions concerning group analysis of functional magnetic resonance imaging (fMRI) data. First, we propose a model-free cluster method that groups brain signals in to clusters, based on wavelet transformation and principal component analysis. From the clustered maps we identify activated regions related to the given tasks. We then use a resampling approach to compare clustered maps between practice groups and scan sessions. Second, we compare differences of groups of subjects in brain activation changes across two scan sessions. Using the property that brain signals in regions of interest (ROIs) may contain a similar pattern across subjects in a task-related experiment, we develop a semiparametric approach under shape invariance to quantify and test differences between sessions and groups. We conduct statistical inference on the scale parameter in the model to determine whether attenuation is present between two sessions for each group and whether a group difference exists between two sessions in multiple ROIs. Last, we take a functional data analysis approach to classify fMRI data. We propose a spatially weighted functional support vector machine (FSVM) that utilizes a parameter to estimate correlation between different brain regions. Using both numerical study and a real fMRI dataset, we show our proposed method achieves higher classification accuracy compared to a regular FSVM method.