Hello,
I have noticed that my data shows some discrepencies between what is shown in AFNI vs. MATLAB regarding the voxel indexing and I would greatly appreciate any help possible. To elaborate, my basic processing pipeline is as follows:

Pre-processing (alignment, motion correction, smoothing etc...)
Project data onto surface volume in SUMA
Draw a line, serving as an ROI (where each node should be a data point)
Transform that "ROI line" from a .niml file to a .1D node list via ROI2dataset and again transforming this output to XYZ mm coordinates via SurfMeasures
Load all data into MATLAB via BrikLoad and use AFNI_XYZcontinuous2Index to get indices of the "line ROI"

Here is where the trouble starts. For example when referencing the voxel index in AFNI, I will get an index of 372560 which according to the field of view for these functional runs should be 68,33,52 in 3 dimensions, which is what MATLAB shows, but in AFNI it comes up as 68,32,51. I even performed several sanity checks, such as writing out my 'line ROI' into .BRIK format just to see how it looks in the 3D volume and surface volume, and this small difference projects the 'line ROI' slightly off of where it is supposed to be according to what was drawn in SUMA (landing in white matter). Several other examples of how this might be impacting my data, (these are actual results following a cross-correlation analysis) the voxel index of 372560 = -2.927 in matlab but is 3.048 in AFNI; the voxel at. 61,38,55 is in matlab list and on curve, index of 394801, but in AFNI has an index of 402145. The data at these two different voxel indices is -3.126 in matlab and 2.909 in AFNI.

What could be going wrong here? Could there be a problem in the manner in which I am transforming my functional data from volume to surface space? Any help would be greatly appreciated. Thank you!