<div>Hi Donald et al.,</div><div><br></div><div>It appears that our connectivity output depends on the voxel dimensions of the seed, include, and mask images that are used when performing "streamtrack".</div><div>
<br></div><div>We have used two approaches to get our seed (binarised and dilated FreeSurfer white matter segmentation), include (parcellation based on FreeSurfer aparca2009s and FSL FIRST), and mask (combination of seed and include) images into FA space.</div>
<div><br></div><div>Prior to implementing Approach 1 or Approach 2, which are described below, we put our structural (FreeSurfer brain.mgz), seed, include, and mask images into standard space using "fslreorient2std", then we coregistered the FA image (generated by MRtrix) to the structural image (in standard space) and generated what we will call the fa2std transform matrix using FSL's "flirt". The target images refer to the seed, include, and mask images (all in standard space).</div>
<div><br></div><div>Approach 1. FSL. We inverted the fa2std transform matrix using "convert_xfm -inverse". Then, using the inverted fa2std transform matrix in "flirt -applyxfm", we applied spatial transformations to the target images, creating outputs that were in FA space and that had the same voxel dimensions as the FA image (2.3x2.3x2.3).</div>
<div><br></div><div>Approach 2. MRtrix. Using "mrtransform -inverse", we inverted the fa2std transform matrix and applied spatial transformations to the target images, creating outputs that were in FA space, but which retained their native voxel dimensions (1x1x1).</div>
<div><br></div><div>These outputs were used in subsequent steps as described below.</div><div><br></div><div>We eroded the 2.3x2.3x2.3 white matter segmentation to create the single fibre mask. Note that we encountered an error when attempting to erode the 1x1x1 white matter segmentation, probably because the "erode" step includes specification of the FA image (which is 2.3x2.3x2.3) for "mrmult" and therefore the voxel dimensions are not compatible.</div>
<div><br></div><div>We used the single fibre mask to estimate the response function coefficient.</div><div><br></div><div>We performed "csdeconv" with the mask specified as our 2.3x2.3x2.3 hybrid brain mask (a combination of the 2.3x2.3x2.3 seed and include images). Note that we encountered an error when attempting to specify our 1x1x1 hybrid brain mask as the mask, again probably due to incompatible voxel dimensions.</div>
<div><br></div><div>Then we performed "streamtrack" twice: firstly at the 2.3x2.3x2.3 resolution (i.e., we used the 2.3x2.3x2.3 seed, include, and mask images); and secondly at the 1x1x1 resolution (i.e., we used the 1x1x1 seed, include, and mask images). We also discovered that "streamtrack" will allow any combination of seed, include, and mask images; i.e., the voxel dimensions of these images do not need to be identical - why is this? Anyhow, we generated one million streamlines using either all 2.3x2.3x2.3 images or all 1x1x1 images.</div>
<div><br></div><div>From each of the track files we extracted streamlines connecting two or more regions (where regions were specified by the include image). Then we generated two connectivity matrices (one that was based on the 2.3x2.3x2.3 images/streamlines and another that was based on the 1x1x1 images/streamlines) by counting the number of streamlines interconnecting each pair of regions. Interestingly, these connectivity matrices were noticeably different, suggesting that the connectivity values depended on the voxel dimensions of the seed, include, and mask images that were used when performing "streamtrack".</div>
<div><br></div><div>We were wondering whether the resolution of the masks affects the tractography in anyway? Is there any reason for preferring one over the other? We presume that the native 1 x 1 x 1 resolution is preferable, but wanted to make sure we are not missing anything here.</div>
<div><br></div><div>Thanks in advance,</div><div><br></div>-- <br><br>Simon Baker<br>PhD Candidate<br>Faculty of Medicine, Nursing and Health Sciences<br>Monash University