Resting-state fMRI topics

网上共享数据给出的fMRI数据和atlas的维度不同怎么办

下载ABIDE提供的数据,发现fMRI和提供的atlas的voxel size都是3mm*3mm*3mm大小,但是两者的维度分别是:

fMRI data 维度 <61×73×61×T> (T is the number of time points).;
Harvard-Oxford (HO) atlas 维度<65×77×63>.

我尝试去除HO atlas两端的数据,使其维度变成<61×73×61>,而后先获取voxel time series,再对各个ROI内的voxel time series取平均,但是得到的ROI time series与ABIDE下下载的差异很大。

我尝试从其他网站下载Harvard-Oxford (HO) atlas,发现维度是 <61×73×61>,但是用这个atlas得到的对应ROI time series与ABIDE下载的差异也很大。

我把我上述处理结果附上,见附件。

我的目标是获得voxel time series,请问这种情况如何处理?

Do I need to strip off all the additional planes of zeros before matching the fMRI data and the atlas?

Dear all,

I hope this email finds you well..

I have a question about what kind of processing should be done before matching the fMRI data and the atlas. I got a suggestion that “additional planes of zeros should be firstly stripped off before changing the atlas to match the data”. If the Harvard-oxford atlas and the preprocessed functional image have different number of additional planes of zeros. What kind of processing should be done before matching them.

使用REST1.8运行ROIwise静息态功能连接,生成的zFC文件中没有相关系数,如图

使用REST1.8设置好两个球形ROI之后(FC中的ROIwise选项),添加预处理过的静息态数据,勾选detrend和filter,生成的zFCMap(txt文件)没有生成相关被试两个ROI之间的相关系数,如截图。而且ROI_FCMap(txt文件)也没有按照时间序列生成两列ROI信号值。在运行过程中都没有报错。

How to get the coordinates of centre of mass for each ROI

Dear all,

I downloaded the Harvard-Oxford atlas (ho_labels.csv and ho_roi_atlas.nii). These two files can be downloaded from http://preprocessed-connectomes-project.org/abide/Pipelines.html, where youu can find "The subcortical and cortical ROIs were combined and then fractionated into functional resolution using nearest-neighbor interpolation. [Atlas][Labels]". Through load_nii('ho_mask_pad.nii'), I can get the index of voxel in each ROI. Fox example, I use the following code to get the index of the ROI labeled 10

load_nii('ho_mask_pad.nii');

请问Harvard-Oxford atlas下的110个Nodes能否归类到几个大网络(resting state networks)

请教各位一个问题。

我看到一些文章,都会把Nodes划分到不同网络,比如看到有的文章说到we utilized data from Smith et al.’s study to assign
264 nodes into 10 functional networks corresponding to the primary resting state networks (RSNs) [40].

[40] S. M. Smith, K. L. Miller, G. Salimi-Khorshidi, M. Webster, C. F. Beckmann, T. E. Nichols, J. D. Ramsey, and M. W.
Woolrich, “Network modelling methods for fmri,” Neuroimage, vol. 54, no. 2, pp. 875–891, 2011.

请问Harvard-Oxford 这种模板下的Nodes有没有谁做过归类?直接按照现在110个Nodes的顺序画出的功能连接图(functional connectivity)看上去很散,很乱。谢谢

resting pCASL brain MRI images analysis 静息态pCASL磁共振分析

小白一个,想请问各位大神、前辈、老师:

静息态pCASL磁共振成像是否可以分析结构和功能像,除了它的CBF脑血流的主要特征?有没有老师可以分享一下如何进行分析,谢非常感谢!