–6–
New Program: 3dREMLfit
¥ Implements Solution #2: estimate correlation parameters and use GLSQ
H REML is a (partially nonlinear) method for simultaneously estimating variance + correlation parameters and estimating regression fit parameters (b s)
H Each voxel gets a separate estimate of its own correlation parameters (a,b)
oEstimates of a and b can be spatially smoothed before they are used to compute the b s
oCan also input a and b directly and skip their estimation (the slow part), if desired, and use those values to compute the b s
oVariance estimate uses pre-whitened residuals to keep DOF=N – m
H Even if correlation decay parameter a was the same for all voxels, relative amount of white noise (measured by b) mixed in would vary spatially
o Sample analyses using 1-parameter AR(1) and MA(1) models shown later
¥ Inputs to 3dREMLfit
H Run 3dDeconvolve first to setup .xmat.1D matrix file, GLTs, etc.
o DonÕt have to let 3dDeconvolve finish analysis: -x1D_stop
o 3dDeconvolve also outputs a command line to run 3dREMLfit with the same 3D+time dataset and the matrix file just created
H Then, input matrix file and 3D+time dataset to 3dREMLfit
¥ Output datasets are structured to be similar to those in 3dDeconvolve
H It should be easy to adapt scripts that use 3dDeconvolve output files (e.g., for group analysis) to use the new software