在使用Utilities中REST power spectrum时，顺利得到了某一个被试的频谱图。
但是，我想得到具体的频谱序列的值，不知道该怎么办？我查看了源代码，找到了‘theFreqSeries’这个变量，好像就是我需要的，计划增加几句代码将其输出到一个txt文件中。但感觉有点笨，不知道有没有更好的办法？或者REST软件本来已经有了，只是我没有找到？
另外，好像现在只能一个人一个人地计算频谱，我想给出两组被试各自的平均频谱，是否只能先一个一个地先算好了再计算平均值？
非常感谢各位老师在百忙中给予解答。
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Resting-State fMRI Data Analysis Toolkit (REST) is a convenient toolkit to calculate Functional Connectivity (FC), Regional Homogeneity (ReHo), Amplitude of Low-Frequency Fluctuation (ALFF), Fractional ALFF (fALFF), Gragner causality and perform statistical analysis. You also can use REST to view your data, perform Monte Carlo simulation similar to AlphaSim in AFNI, calculate your images, regress out covariates, extract ROI time courses, reslice images, and sort DICOM files. Download a MULTIMEDIA COURSE would be helpful for knowing more about how to use this software. Add REST's directory to MATLAB's path and enter "REST" in the command window of MATLAB to enjoy it.
The latest release is REST_V1.5_101101. |
New features of REST V1.5 release 101101:
1. Fixed a bug in rest_RegressOutCovariates_gui.m while processing multiple subjects with different covaribles in batch mode.
New features of REST V1.5 release 101025:
1. Module of Regional Homogeneity based on Coherence (Cohe-ReHo) has been added by LIU Dong-Qiang and DONG Zhang-Ye. For methodology, please see: Liu D, Yan C, Ren J, Yao L, Kiviniemi VJ and Zang Y (2010) Using coherence to measure regional homogeneity of resting-state fMRI signal. Front. Syst. Neurosci. 4:24. doi: 10.3389/fnsys.2010.00024.
2. In previous release of REST, removing covariates effects will also regress out linear trend. Now regressing out linear trend has been canceled in this step. Users can still regress out polynomial effects by using rest_regressOutCovariates.m in command line.
3. For rest_sliceviewer, fixed a bug of in displaying with MATLAB 2010 and support mouse wheel operation.
4. Fixed a bug in converting .nii files into NIfTI pairs (.img/.hdr).
5. Added new function of "corr(i1,i2,'spatial')" in REST Image Calculator.
6. Now can open a yoked structural image in displaying power spectrum.
7. Now can also pick up .nii files in GUI of reslice image.
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Data Processing Assistant for Resting-State fMRI (DPARSF) is a convenient plug-in software based on SPM and REST. You just need to arrange your DICOM files, and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data, FC, ReHo, ALFF and fALFF results. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. You can use DPARSF to extract AAL or ROI time courses (or extract Gray Matter Volume of AAL regions, command line only) efficiently if you want to perform small-world analysis. DPARSF basic edition is very easy to use, just click on buttons if you are not sure what it means, popup tips would tell you what you need to do. DPARSF advanced edition (alias: DPARSFA) is much more flexible, you can use it to reorient your images interactively or define regions of interest interactively. You can skip or combine the processing steps in DPARSF advanced edition freely. Please download a MULTIMEDIA COURSE to know more about how to use this software. Add DPARSF's directory to MATLAB's path and enter "DPARSF" or "DPARSFA" in the command window to enjoy DPARSF basic edition or advanced edition.
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New features of DPARSF_V2.0_110505:
1. Fixed an error in the future MATLAB version in "[pathstr, name, ext, versn] = fileparts...".
New features of DPARSF_V2.0_101025:
1. DPARSF advanced edition (alias: DPARSFA) is added with the following new features:
1.1. The processing steps can be freely skipped or combined.
1.2. The processing can be start with any Starting Directory Name.
1.3. Support ReHo, ALFF/fALFF and Functional Connectivity calculation in individual space.
1.4. The masks or ROI files would be resampled automatically if the dimension mismatched the functional images.
1.5. The masks or ROI files in standard space can be warped into individual space by using the parameters estimated in unified segmentaion.
1.6. Support VBM analysis by checking "Segment" only.
1.7. Support reorientation interactively if the images in a bad orientation.
1.8. Support define regions of interest interactively based on the participant's T1 image in individual space.
2. DPARSF basic edition is preserved with the same operation style with DPARSF V1.0. DPARSF basic edition has the following new features:
2.1. Fixed a bug in copying "*.ps" files.
2.2. Will not check "wra*" prefix in "FunImgNormalized" directory.
2.3. Fixed a bug while regress out head motion parameters only.
The multimedia course for DPARSF advanced edition is estimated to be released in this November, thanks for your patience.
抱歉有两个不是问题的问题请教：
1. AFNI里AlphaSim还有关于user specified activate region情况，请问REST有考虑将来的版本升级呢？
另外请教，相应参数Zsep (separation between the mean of the noise distribution and the mean of the signal distribution)如何设定呢？
2. REST里AlphaSim关于xthr (xthr = sd*zthr + mean)计算，sd和mean都是每迭代一次，要累积前面迭代的值，我不是很明白。即如下：
count=count+nxyz; 为什么不每次迭代count都赋值为nxyz呢？
敬爱的专家：
你们好，我在做癫痫病人和对照组中分别得到了组内的单样本T检验，现在我想观察组间的T检验情况，但是我想希望单单比较癫痫组和对照组的正性连接，再比较负性连接，因为我在直接将癫痫组和对照组进行双样本T检验，如你们的数据处理视频中所说的做，我发现，有些激活的区域，两个组单样本中其实分别是正负连接，这样可能会导致统计上的放大显著差异，所以我想单单了解正性连接和负性连接的情况。但是我不知道应该怎么样通过rest实现。
希望你们看到后，能白忙中回复下，谢谢！
各位老师好，因为我是刚学，人也比较笨，所以问题很多，有些问题可能很傻，麻烦大家耐心指教啊，十分感谢！
1、因为我想做大脑的小世界性质分析，所以使用Dparsf得到了AAL90个区域的时间序列，但我想要的是90个区域的功能连接图和z-map，要怎么办？是不是要分别制作那90个ROI的mask？有没有简便的方法？
2、在制作AAL的一个ROI的mask的时候，Cluster Size是有什么用的，要怎么设置？我看了Course_Data_Process_of_Rest_fMRI_Part2_Chinese_100820这个视频但还是不明白，能否讲解一下？
3、后来我想反正我只是检验小世界性，只需要z值就行了，于是用corrcoef函数通过前面得到的AALTC求出90个区域的R值，再转换成z值，然后进行后面的计算，这种做法有没有什么不妥啊？
4、检验小世界性时，需要产生100个相应的随机网络和规则网络，是针对每个病人都要产生这100个随机网络么？我看文献上说按照马尔可夫链规则产生，那个规则具体是怎样的？就算这个规则能保证随机网络的平均度和边数与病人的网络相同，怎么能保证度分布还是相同的呢？老师那里有没有检验小世界性的做好的软件，是否是开放的？
有个小问题，我一直想不明白，请大家帮忙。
在一幅fMRI图像中，BOLD信号具体数值是多少？怎么样才能看到这个数据？
举个例子，有篇文章得到了下面的统计图，我想知道BOLD信号的数值是怎么得到的，用SPM能实现吗？
有个小问题，我一直想不明白，请大家帮忙。
在一幅fMRI图像中，BOLD信号具体数值是多少？怎么样才能看到这个数据？
举个例子，有篇文章得到了下面的统计图，我想知道BOLD信号的数值是怎么得到的，用SPM能实现吗？
Hi everybody,
I'm currently processing a series of rest fmri data which need to be manually normalized.
The procedure briefly goes like this:
-- dparsf completed the pre-normalization steps from 'dicom->nifti' to 'realign'
-- toggle spm, 'coregister: estimate',
-- switch AFNI，
'3dWarp -deoblique' and '3drefit -markers ' to generate sturctural .HEAD/BRIK pair
请问谁用时间簇分析法（TCA）处理过fMRI数据啊？
想知道这种方法需要使用什么样的软件，是怎样实现的。
谢谢大家!