![]() 'Error in Removing First 10Time Points: Sub_001' Removing First 10 Time Points: Sub_003 OK Removing First 10 Time Points: Sub_002 OK Removing First 10 Time Points: Sub_001 OK ![]() Starting parallel pool (parpool) using the 'local' profile. Saving /home/labuser/dpabi/T1Img/Sub_003/cot1mpragesag.nii Saving /home/labuser/dpabi/T1Img/Sub_003/ot1mpragesag.niiĬropping NIfTI/Analyze image /home/labuser/dpabi/T1Img/Sub_003/ot1mpragesag.nii ĭear teacher: I come from Department of Psychiatry The 1st Affiliated Hospital of Kunming Medical University.After we completed the installation according to the tutorial, the next error occurred, which has not been resolved, please ask the teacher to help solve the next problem Robert W Cox noted: "Simulations were also repeated with the now infamously "buggy" version of 3dClustSim: the effect of the bug on FPRs was minimal (of order a few percent).". The estimation of mean and standard deviation is within the whole bounding box as well, which we believe is better than estimating in a small mask (estimation of mean and standard deviation within a small mask might be inaccurate). The code was revised to smooth the whole bounding box first and apply mask later, and the code was distributed with DPABI_V1.2_141101. Katharina Wittfeld reported a bug with AlphaSim for small masks in combination with high smoothness: applying mask before the Gauss filter while the Gauss filter will blur the boundaries of the masked region which will cause problems later ( ). For the so-called “bug” - the edge effects within the mask (apply mask and then smooth), DPABI doesn’t have such an issue since DPABI_V1.2_141101. Finally, the corrected results could be viewed by the convenient surface viewer DPABISurf_VIEW, which is derived from spm_mesh_render.m. These processed metrics then enters surfaced-based statistical analyses within DPABISurf, which could perform surfaced-based permutation test with TFCE by integrating PALM. DPABISurf also performs surface-based smoothing by calling FreeSurfer’s mri_surf2surf command. DPABISurf further performs nuisance covariates regression (including ICA-AROMA) on the surface-based data (volume-based data is processed as well), and then calculate the commonly used R-fMRI metrics: amplitude of low frequency fluctuation (ALFF) (Zang et al., 2007), fractional ALFF (Zou et al., 2008), regional homogeneity (Zang et al., 2004), degree centrality (Zuo and Xing, 2014), and seed-based functional connectivity. ![]() ![]() With fMRIPprep, the data is processed into FreeSurfer fsaverage5 surface space and MNI volume space. DPABISurf provides user-friendly graphical user interface (GUI) for pipeline surface-based preprocessing, statistical analyses and results viewing, while requires no programming/scripting skills from the users. The DPABISurf pipeline first converts the user specified data into BIDS format (Gorgolewski et al., 2016), and then calls fMRIPprep 1.3.0.post3 docker to preprocess the structural and functional MRI data, which integrates FreeSurfer, ANTs, FSL and AFNI. DPABISurf was released! DPABISurf is a surface-based resting-state fMRI data analysis toolbox evolved from DPABI/DPARSF, as easy-to-use as DPABI/DPARSF.
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