Computing Brain Activity Maps from FMRI Time-Series Images
fMRI is a very popular method for researchers and clinicians to image human brain activity in response to given mental tasks. This book presents a comprehensive review of the methods for computing activity maps, while providing an intuitive and mathematical outline of how each method works. The approaches include statistical parametric maps (SPM), hemodynamic response modeling and deconvolution, Bayesian, Fourier and nonparametric methods. The newest activity maps provide information on regional connectivity and include principal and independent component analysis, crisp and fuzzy clustering, structural equation modeling, and dynamic causal modeling. Preprocessing and experimental design issues are discussed with references made to the software available for implementing the various methods. Aimed at graduate students and researchers, it will appeal to anyone with an interest in fMRI and who is looking to expand their perspectives of this technique.
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active voxels algorithm approach artifact autocorrelation average balloon model basis functions Bayesian blocked design blood BOLD response BOLD signal cardiac columns correlation cortical covariance defined denoising design matrix detection distribution effective connectivity estimate event-related design event-related fMRI filter fMRI data set fMRI time-series Fourier transform frequency Friston K. J. functional connectivity functional MRI functional neuroimaging fuzzy clustering Gaussian geometric distortion given by Equation global signal gradient hemodynamic response Hum Brain Mapp hyperparameter independent component analysis k-space linear Magn Reson Imaging magnetic field magnetic resonance imaging measure methods model HRF model of Equation motion multivariate Neuroimage noise nonlinear parameters permutation physiological pixel preprocessing pulse sequence random regions replicator dynamics represents Section slice smoothing spatial statistic statistical parametric maps stimulus task temporal threshold time-series values variables variance variation vector Volterra kernels voxel voxel time course wavelet coefficients wavelet transform