Statistical Analysis of fMRI Data 2/e

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.

第二版的《功能性磁共振成像實驗設計與數據分析指南》是對所有實驗設計和數據分析方面進行全面修訂和更新的指南。

功能性磁共振成像（fMRI）是一種非侵入性觀察人腦神經活動的技術，徹底改變了對心智的科學研究。fMRI實驗產生了大量高度複雜的數據供研究人員分析。本書描述了fMRI實驗的所有方面，從預處理到評估功能連接的高級方法，以及最流行的多變量方法。目標不是描述如何在常用軟件包中操作，而是幫助研究人員理解基本的邏輯、假設、優點和缺點以及每種方法的適用性。

近年來，fMRI研究領域在方法學和技術方面取得了巨大進展，第二版已經完全修訂和更新。新增了六章，包括實驗設計、通過心理生理相互作用和β系列回歸方法進行功能連接分析、使用多體素模式分析進行解碼、動態因果建模和表徵相似性分析。其他章節提供了關於頭部運動、多變量GLM、元分析和其他主題的新材料。所有複雜的推導現在出現在相關章節的末尾，以提高可讀性。附錄中還描述了如何使用效應編碼構建群體分析的設計矩陣。與第一版一樣，提供了MATLAB代碼，讀者可以實施描述的許多方法。

F. Gregory Ashby is Professor and Chair in the Department of Psychology and former Director of the Brain Imaging Center at the University of California, Santa Barbara.

F. Gregory Ashby是加州大學聖塔芭芭拉分校心理學系的教授和系主任，曾任腦影像中心主任。