Hi,
Recentlty, I have been processing my monkey data in DPABI. According to template paremetes, I do not execute brain extraction and nusiance covariates regression, due to there were error in bet and nusiance covariates regression will lead to a bad result.
I have some questions about monkey data processing,
Dear all
Hi,
I'm using DPARSF for 12 subjects.
Today I found that in one subject, functional connectivity images from all 4 sessions of BOLD resting state fMRI have different image from others.
Here I attached a screenshot, left one is different from right normal image.
I did every analysis in same procedure and checked several times.
It seems like participants moved during measurement, but when I checked a realignment parameter, movement is less than 0.5mm.
I want to obtain network measurements that illustrate the group comparisons I’m performing on my data. The data itself consists of coherence matrixes previously calculated by Matlab routines external to GraphVar. So, in order to work with them, I’m selecting the “Raw Matrix” checkbox in the “Raw Matrix (link wise)” panel.
For this exposition, let’s focus solely on the computation of the “Binary Degree” of each node. I imposed the relative network thresholds of 0.1, 0.2, 0.3, 0.4 and 0.5 in the “Network Construction” menu.
严老师，您好！
我目前正在使用DPABI中的DPARSF for monkey版本处理猴子静息态功能磁共振图像，其扫描参数为，间隔扫描，FOV：96*90*76，number of slice: 76, size of voxel: 1*1*1mm3 , TR: 6000ms, time of point: 336。
先是以其中一个被试的数据（4D NiFTI .nii格式）为例进行测试。事先已经剔除了前6个时间点。处理的过程以及疑问清晰描述在word（比较好排版）里面，所以麻烦老师了。
郭承珍
Hello Dr Yan
please i want to know how to rank voxel in ReHO calculations (rank according to what??)?
Thank for your effort.
Hi all:
I am working on a resting state data set of mice. I have followed the tutorial of rodents data processing. My question is after I augmented each voxel by 10 what is the smoothing kernel I should use?. I understand it is supposed to be 2-3 times the size of the voxel, so should I consider the size of the voxel before or after the augmentation?.
for example: the original size of the voxel was 0.5X0.5X0.5 and after augmentation it became 5X5X5, so the kernel should be 1X1 or 10X10.
Thank you.
Amr
Hi!
I am doing an analyses on two groups of subjects with data that was acquired with different scanning parameters:
1. TR 2.3, 37 slices, 3x3x3
2. TR 2.3, 34 slices, 4x4x4
What would be the best common voxel size for the analyses?
To what point should I preprocess the data separately?
Thank you for any hepl in advance,
Emilia Cheladze