Sentence examples for using the afni program from inspiring English sources

Single-subject regression modeling was carried out using the AFNI program 3dDeconvolve.

Considering the fact that raw MRI data contain a degree of smoothness introduced, for example, during image reconstruction from k-space (Friedman et al. 2006), the actual smoothness of the images was calculated from error residuals using the AFNI program 3dFWHMx.

The average time course of the MR BOLD response in select ROIs was generated using the AFNI 3dDeconvolve program with the iresp option.

Data analysis was performed using the AFNI software [15], [16] and Matlab (The MathWorks, Inc., Natick MA).

To correct for motion artifacts, all blood-oxygen-level-dependent (BOLD) images were realigned with the fourth frame of the first functional run using the AFNI software [55].

Motion correction and cross-scan alignment were performed using the AFNI (Analysis of Functional NeuroImages) 3dvolreg (3T data).

Preprocessing and whole-brain analyses were conducted using the AFNI (Analysis of Functional Neural Images) software (Cox, 1996).

All preprocessing procedures were performed using the AFNI software (http://afni.nimh.nih.gov/) in the Laboratory of Digital Medical Imaging, the First Affiliated Hospital of Anhui University of Chinese Medicine.

Each data-set was divided into 1000 voxels, each of 20 mm, using the AFNI-to3d-software (AFNI-Analysis of functional neuroimages [ 33]).

A corrected threshold of p < 0.01 (two-tailed) was derived from a combined threshold of p < 0.01 for each voxel and a cluster size of > 35 voxels was determined using the AlphaSim program in AFNI software (Parameters: single voxel p < 0.01, 5000 simulations, FWHM = 6 mm, with gray matter mask, http://afni.nimh.nih.gov/).nih.gov/

Monte Carlo simulations were performed using the AlphaSim program (http://afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf) implemented in AFNI to control the false-positive rate.