Hi, I'm using 'mri_glmfit' with surface inputs. However, from subject to subject, some vertices have zero-values. One solution is to use the 'prune' flag to keep only non-zeros vertices across subjects. However, this solution seems too conservative as too many vertices are discarded, producing gruyère-like significance maps.
Is it possible to adopt a softer version of prune, i.e., only do the inference on non-zeros frames, without including frames that have null signal? In other words, this solution would consist in having different degrees of freedom throughout the surface. thanks, julien -- Julien Cohen-Adad, PhD Athinoula A. Martinos Center for Biomedical Imaging MGH, Harvard Medical School 149 Thirteen St, Charlestown, MA 02129, USA Work: +1 617 724 2463 ; Cell: +1 857 544 6110 ; Fax: +1 617 726 1383
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