Dear experts,
Hi Chao-Gan,
There is a problem with masks containing NaN-values. Because Matlabs function 'unique' handles each NaN-value as a distinct value, in a multilabel ROI-defining mask with NaN-values each mask voxel with the value NaN is considered as a separate ROI. This situation can lead to maximum size exceeding errors when calculationg the covariance matrix.
I recommend to modify in the function y_ExtractROISignal the line 197
Dear DPARSF experts
Hi everyone
I found there are many black points scattering on the pictures for checking normalization (see below). No such points were found in the FunImg data. I don't know these black points means voxels lost or some other meaning. The preprocessing steps include: slice timing, realign, bet, T1 coreg to FUN, new segment+DARTEL, Covariates Regression, Filter, Normalize by DARTEL.
Dear all,
I cannot figure out precise meaning of some files in the folder of FunImgRWSCovs, such as ROICorrelation_subjn.txt, ROICorrelation_FisherZ_subjn.txt.
Dear DPARSF users
I try to use DPARSF for my rest data but I face the following error which is related to Mask. I also chose NO mask to skip this step, but this error was appeared again. What should I do?
Hi,
Sorry to bother you frequently these days. An error occured after completing filtering and before nomalization (normalize with DARTEL). The same error happened with Matlab version 2014a and 2013b. The whole lines in the command window are as below:
Dear Colleagues,
I.
Would it be possible to implement calculation of a network homogeniety in the context of ReHo.. How would you do that? Would you just calculate KCC [Kendall's coefficient concordance] for all voxels within a given mask? (say, if we use Yeo's parcellation of major brain networks). Could you please suggest a function/script I can look into?
II.
Hi
An error happened when I perform Bet using DPARSFA 4.1 . The Matlab command window gives some options to solve these problem, but I don't understand how to choose one option and continue processing. It reads as below in the command window: