Parametric response surface models for analysis of multi-site fMRI data.
Analyses of fMRI brain data are often based on statistical tests applied to each voxel or use summary statistics within a region of interest (such as mean or peak activation). These approaches do not explicitly take into account spatial patterns in the activation signal. In this paper, we develop a response surface model with parameters that directly describe the spatial shapes of activation patterns. We present a stochastic search algorithm for parameter estimation. We apply our method to data from a multi-site fMRI study, and show how the estimated parameters can be used to analyze different sources of variability in image generation, both qualitatively and quantitatively, based on spatial activation patterns.
Kim
Seyoung
S
Bren School of Information and Computer Sciences, University of California, Irvine, USA. sykim@ics.uci.edu
Smyth
Padhraic
P
Stern
Hal
H
Turner
Jessica
J