Bayesian hierarchical multi-subject multiscale analysis of functional MRI data
Abstract
We develop a methodology for Bayesian hierarchical multi-subject multiscale analysis of functional Magnetic Resonance Imaging (fMRI) data. We begin by modeling the brain images temporally with a standard general linear model. After that, we transform the resulting estimated standardized regression coefficient maps through a discrete wavelet transformation to obtain a sparse representation in the wavelet space. Subsequently, we assign to the...
Paper Details
Title
Bayesian hierarchical multi-subject multiscale analysis of functional MRI data
Published Date
Nov 1, 2012
Journal
Volume
63
Issue
3
Pages
1519 - 1531
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