The Statistical Analysis of Functional MRI Data
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”).
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Design of fMRI Experiments
Noise and Data Preprocessing
Statistical Issues in fMRI Data Analysis
Basic Statistical Analysis
Temporal Spatial and Spatiotemporal Models
Basis Function Approaches
Bayesian Methods in fMRI
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active voxels algorithm analysis of fMRI approach assumption authors average baseline basis functions Bayesian behavior block design BOLD response Bonferroni correction brain Bullmore Chapter coefficients combining correlation course covariance data set detected distribution effect model estimated example experimental false discovery false discovery rate frequency Friston Functional MRI gradient group map head motion hemodynamic response hence interest k-space Larmor equation least squares linear model magnetic field Magnetic Resonance matrix methods multiple multivariate neuroimaging noise normal null null hypothesis number of subjects number of voxels p-values parameters patterns performed permutation posterior principal components prior procedure protons pulse random effect random effect model random field regions resampling researchers ROC curve scan scanner signal significant simple slice smoothing spatial spatiotemporal Springer Science+Business Media statistical analysis stimulus task task-related techniques temporal test statistic threshold tissue transform variability variance wavelet zero