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1231 days ago
Unfiled. Edited by Marianne Reddan , Jessica Mollick , luka 1231 days ago
  • add contour plot to coreg preproc output plots
SPM uses neurological convention: the Left is on the Left. Lots of data are collected in radiological convention (the Left is on the Right). SPM isn't going to tell you if it is flipping or not, however the X-coordinate will be negative if SPM thinks it is in radiological and is is therefore flipping it for your viewing convenience. You should mark with vitamin E the Right side of all subjects. If you haven't done this, in order to confirm that what you are analyzing as R side in SPM actually is R side in real life, consider natural asymmetries in the brain: The right hemisphere protrudes anteriorly beyond the left, and the left hemisphere extends posteriorly beyond the right (Toga & Thompson, 2003).
Don't stress too hard about setting the origin in those funky looking EPI images. Do your best. The algorithm will take care of the rest (quite robustly, in my opinion). 
Note: Do not be alarmed when you see mean functional plots widely off the anatomical SPM template during preprocessing BEFORE coregistration. The plotting during that time is arbitrary. Do be alarmed if your coregistration plots are wildly off kilter.
Note: canlab_preproc can produce a movie that displays spikes (example still below), but it is currently disabled due to time & space constraints. 
Marianne R
  • option to change the threshold for removing crap volumes -- visually determine by watching RMSSD movies and then adjust SD (determine PRIOR to preproc)
  • look at ART
Neither: incorporate the measurement time in your models later.
We do linear temporal interpolation based on a specified slice (and your sequence).
Alternatives are: translation, rotation, scaling, shearing.
We register to the first volume [in each run? or first volume of first run for all?]
The Gaussian kernel is determined by the full width at half maximum (FWHM): the width of the kernel at 50% of its peak value. Usually measured in terms of mm (typically 4 - 12mm range).
  • fslval $functional_data_file_here dim3 
Also, to check the acquisition of your images, you can use the script check_acquisition_pars_func.sh in labdata/current which outputs the type of acquisition you have.
You want to look at the value of dim3. This value can help you determine your microtime onset.

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