Hi,<div><br></div><div>I&#39;m using &#39;mri_glmfit&#39; with surface inputs. However, from subject to subject, some vertices have zero-values. One solution is to use the &#39;prune&#39; 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.</div>
<div><br></div><div>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.</div>
<div><br></div><div>thanks,</div><div><br></div><div>julien</div><div><br></div><div><br></div><div>-- <br>Julien Cohen-Adad, PhD<br>Athinoula A. Martinos Center for Biomedical Imaging<br>MGH, Harvard Medical School<br>149 Thirteen St, Charlestown, MA 02129, USA<br>
Work: +1 617 724 2463 ; Cell: +1 857 544 6110 ; Fax: +1 617 726 1383<br>
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