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Resting-State fMRI Data Analysis Toolkit plus V1.1 (RESTplus V1.1)


RESTplus evolved from REST (Resting-State fMRI Data Analysis Toolkit). It is based on Matlab and SPM8. RESTplus includes four main modules, i.e., pipeline, statistical analysis, utilities and viewer.

     The pipeline (either fixed or flexible) module provides a very easy way for data processing. After arrangethe DICOM or NIFTI filesand click a few buttons to set parameters, the pipeline (or flexible) module will automatically calculate each processing step and give you all the processed data. The pipeline and flexible module can perform slice timing, realign, reorient, normalize, smooth, detrend, filter, nuisance covariates regression, Functional Connectivity (FC), Regional Homogeneity (ReHo), Amplitude of Low-Frequency Fluctuation (ALFF), fractional ALFF (fALFF), Granger causality, degree centrality, voxel-mirrored homotopic connectivity (VMHC), and percent amplitude of fluctuation (PerAF). 


DOWNLOAD 

Multimedia Course: Data Processing of Resting-State fMRI

 

     You can also use RESTplus to perform statistical analysis, view your data, perform Monte Carlo simulation (similar to AlphaSim in AFNI), perform Gaussian random field theory multiple comparison correction like easythresh in FSL, calculate your images, regress out covariates, extract ROI time courses, reslice images, calculate intraclass correlation, perform quality assurance, normalize PET data, inverse data into original space, and sort DICOM files. RESTplus also includes ASL toolbox.

Contributor list:

     JIA Xi-Ze, Wang Jue, Liao Wei, Zhang Han, Liu Dong-qiang, Ji Gong-jun, Gao Zhong-zhan, Li Xun, Huang Hui-yuan, Wang Ze, Yan Chao-gan, Song Xiao-wei, Zang Yu-feng

 

New features of RESTplus V1.1 (released 20160122)

1. SPM12 Compatible (JIA Xi-Ze)

2. Added ASL toolbox for pcasl and 3D ASL (WANG Ze and JIA Xi-Ze)

3. Updated rp_spm_write_vol.m and rp_spm_read_vols.m from SPM5 to SPM12 (JIA Xi-Ze and LI Xun).

4. Spatial correlation of images in Imaging Calculator, supporting mask selection (JIA Xi-Ze; Thanks the report by JIAO Fang-Yang).

5. Added standardized effect size for t-tests (GAO Zhong-Zhan and JIA Xi-Ze)

6. Fixed a bug when subject ID of dicom header includes ‘-’ or ‘:’. ‘_’ and ‘:’ will be replaced by ‘_’. (JIA Xi-Ze; Thanks report of LIU Yan)

 

Jia Xi-Ze, Wang Jue, Liao Wei, Zhang Han, Liu Dong-qiang, Ji Gong-jun, Gao Zhong-zhan, Li Xun, Huang Hui-yuan, Wang Ze, Yan Chao-gan, Song Xiao-wei, Zang Yu-feng.
   Jia Xi-Ze, Wang Jue, Liao Wei, Zhang Han, Liu Dong-qiang, Ji Gong-jun, Gao Zhong-zhan, Li Xun, Huang Hui-yuan, Wang Ze, Yan Chao-gan, Song Xiao-wei, Zang Yu-feng.

New features of RESTplus V1.0 beta release 151028:

1 Added pipeline module (JIA Xi-Ze)

2 Added flexible module (JIA Xi-Ze)

3 Added quality assurance module (JIA Xi-Ze)

4 Added REST inverse module (JIA Xi-Ze)

5 Added PET Normalize module (JIA Xi-Ze)

6 Added REST Intraclass correlation module (JIA Xi-Ze)

7 Added ASL toolbox for pasl (Wang Ze and JIA Xi-Ze)

8 fix a bug in of NIfTI nii to NIfTI pairs. (Li Xun and JIA Xi-Ze)

9 Nuisance covariates regression can add mean back (JIA Xi-Ze)

10 Module of percent amplitude of fluctuation (PerAF) has been added. (JIA Xi-Ze)

 

Thanks a lot for your email to JIA Xi-Ze (jiaxize@foxmail.com) for any suggestion.

Dynamic brain connectome analysis toolbox


Dynamic brain connectome (DynamicBC) analysis toolbox is a Matlab toolbox to calculate Dynamic Functional Connectivity (d-FC) and Dynamic Effective Connectivity (d-EC). Sliding window analysis (Bivariate Pearson correlation and Granger causality) and time varying parameter regression method (Flexible Least Squares) are two dynamic analysis strategies for time-variant connectivity analysis in the DynamicBC. Granger causality density/strength (GCD/GCS) and functional connectivity density/strength (FCD/FCS) analysis would be performed in this toolbox. Add DynamicBC's directory to MATLAB's path and enter "DynamicBC" in the command window of MATLAB to enjoy it.

The latest release is DynamicBC1.2_20160415.  

Manual could also be downloaded here.

New features of DynamicBC 1.2 release 20160415: 

 

Fixed the step bugs when selecting window size.

New features of DynamicBC 1.1 release 20140710:
1. Added the new utilties including the ‘Clustering’ and 'Spectrum' for dynamic FC/EC time series.
2. Added the new output of variance of dynamic FC/EC time series.  
 

New features of DynamicBC 1.0 release 20140429: 
This release fixed some minor bugs in dynamic FCD.

Resting-State fMRI Data Analysis Toolkit V1.8 (静息态功能磁共振数据处理工具包 V1.8)

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, degree centrality, voxel-mirrored homotopic connectivity (VMHC) and perform statistical analysis. You also can use REST to view your data, perform Monte Carlo simulation similar to AlphaSim in AFNI, perform Gaussian random field theory multiple comparison correction like easythresh in FSL, 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.

Citation of REST is: 
Xiao-Wei Song, Zhang-Ye Dong, Xiang-Yu Long, Su-Fang Li, Xi-Nian Zuo, Chao-Zhe Zhu, Yong He, Chao-Gan Yan, Yu-Feng Zang. (2011) REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing. PLoS ONE 6(9): e25031. doi:10.1371/journal.pone.0025031

The latest release is REST_V1.8_130615


DOWNLOAD 

Multimedia Course: Data Processing of Resting-State fMRI

New features of REST V1.8 release 130615:
1. Fixed a bug in temporal correlation of two groups of images in Image Calculator. (Thanks for the report of ZHANG Han)

2. The midline of VMHC results were set to zero. (YAN Chao-Gan)
 

New features of REST V1.8 release 130303:
When calling Mingrui Xia's BrainNet Viewer (http://www.nitrc.org/projects/bnv/), the default surface template is changed to the smoothed version (BrainMesh_ICBM152_smoothed.nv). The previous default template (BrainMesh_ICBM152.nv) hide more information in the sulcus. If the users want to use BrainMesh_ICBM152.nv as default surface template, please uncomment Line 3740 in rest_sliceviewer: %SurfFileName=[BrainNetViewerPath,filesep,'Data',filesep,'SurfTemplate',filesep,'BrainMesh_ICBM152.nv'];
(After discussion with Mingrui Xia).

New features of REST V1.8 release 130214:
1.    This release fixed some minor bugs, will not affect any data analysis.
2.    Fixed a bug when using .nii(.gz) files in REST Image Calculator. (WANG Xin-Di)
3.    Fixed a bug in using .nii(.gz) files in GCA analyses. (ZANG Zhen-Xiang)
4.    Fixed the imresize_old bug of REST Slice Viewer with Matlab 2012b. (YAN Chao-Gan)

New features of REST V1.8 release 121225:
1.    Support parallel computing! If you installed the MATLAB parallel computing toolbox, REST can distribute the subjects into different CPU cores. (WANG Xin-Di and YAN Chao-Gan).
2.    Algorithm change: (1) Filtering: a separate function for matrix filtering was written. The low cutoff frequency index calculation changed from round (in REST V1.7) to "ceil". E.g., if low cut off corresponded to index 5.1, now it will start from 6 other than 5. This change also applies to ALFF and fALFF calculation. The filtered data changes slightly, about 0.0001. (2) The ALFF generated by the new version is sqrt(2/N) times of the original version. (new version used: 2*abs(fft(x))/N; original version used:  sqrt(2*abs(fft(x))^2/N)). This change will not affect group analysis (as each individual scaled the same number), and will not affect mALFF and fALFF calculation as this factor will be normalized. (3) In the calculation of ReHo, the rank will keep as double and no longer converted into uint16, thus created slight difference with REST V1.7. (YAN Chao-Gan)
3.    REST Slice Viewer support 4D file display and the maximum and minimum value could be set. (WANG Xin-Di)
4.    Gaussian random field (GRF) theory multiple comparison correction (like easythresh in FSL) was supported. The smoothness could be evaluated for GRF correction or AlphaSim correction. (GUI by WANG Xin-Di, algorithm by YAN Chao-Gan)
5.    Modules of voxel-mirrored homotopic connectivity (VMHC) (Zuo et al., 2010), Degree Centrality (Buckner et al., 2009) were added. (GUI by WANG Xin-Di, algorithm by YAN Chao-Gan)
6.    REST GCA: could handle multiple ROIs (other than 2) in ROI-wise GCA now. Fixed a bug of discordance between the outputs and the description in REST-GCA readme in the pre-release of REST V1.8. (ZANG Zhen-Xiang)
7.    rest_readfile.m and rest_writefile: The default format changed to .nii from .img. (WANG Xin-Di)
8.    rest_to4d.m: now support one 4d file other than a directory, also support a cell of image filenames. (YAN Chao-Gan)
9.    rest_regress_ss.m: add the output of T value. (YAN Chao-Gan)
10.    rest_Write4DNIfTI.m: This function was added for write 4D nifti files based on SPM’s nifti function. (YAN Chao-Gan)
11.    rest_writefile.m: No longer need to change to RPI before writing. (YAN Chao-Gan)

rest1.8 EXTRACT ROI SIGNAL and FC

    rest 里面的extract ROI Signal功能,我用自己弄的90个脑区作为ROI,最后得到的resultCorr.txt(90*90矩阵),是90个脑区的相关系数,接着去除了这90个脑区的协变量,再做了功能连接之后的ROI-WISE也得到FCMap.txt 或zFCMap.txt(90*90矩阵),这个也是90个脑区相关系数。

臧玉峰文章引用检索报告

编号:2016-NLC-LWCZ-1371
 
 
 
检 索 报 告
 
检索课题:臧玉峰发表的学术论文被SCI和SSCI、ESI数据库收录引用情况
委托单位:杭州师范大学
委 托 人:臧玉峰
检索工具:
 Science Citation Index Expanded (SCI-EXPANDED) 1900-pre
Social Sciences Citation Index (SSCI)

北师大心理学院的11212015246错误邮箱

北师大心理学院的11212015246新注册用户您好:你留的信箱可能是错误的,无法完成注册。请与我联系。zangyf@gmail.com

Help running the multimedia course part 1

Hi, 

I am new at using dpabi, so I am trying to use the multimedia course module part 1. However when I try to run the sample data after selecting choices as shown on the video, I obtained the following message on MATLAB:

如何分析三组被试ALFF在哪些脑区有差异并与行为学指标进行相关分析

(新手)我有三组数据要进行分析,下面是我尝试的分析处理过程,但是不知道对不对,求老师指导一下,谢谢!

利用rest首先进行的ANOVA,找到差异性显著的clusters,(不知如何选择ROI做mask,所以只是单纯的存为clusterA.txt)。然后进行two sample t-test,又出来一些差异性显著的clusters,3组每进行两两比较就得到3个这样的clusters,分别记为cluster1,2,3。然后我将clusterA中具体的cluster与cluster1,2,3中的进行比对,将能对应起来的看作是两两比较时有差异性的脑区。这样做对吗?如果不对的话,麻烦教一下正确的方法。

自编voxel-wise correlation和REST voxel-wise correlation生成文件的差异

各位,我用Matlab自己写了一个voxel-wise correlation的小插件,和REST voxel-wise correlation生成文件相比,*.img内数据一样(是pearson相关后的r值),但是头文件不同,我用的源空间头文件是预处理以后的某一volume的*.hdr。

请问,差别在哪里?

 

谢谢!

ICA结果中表征组间差异问题

各位好:

         我研究的是中风病人和正常人ICA网络的组间差异问题,拿运动网络为例,我们发现病人组和正常人组的单样本图差异很大(前提是卡了同一个阈值),主要是涉及的脑区范围存在显著差异,正常人组单样本图比较正常,病人组的单样本图明显比正常人组小了好几圈,为了定量表征两组间这种差异,体素个数上的差异(或者说网络覆盖程度的差异),我具体的应该怎样统计呢?我的预想是将每个被试的运动网络的map的体素个数输出来,然后对正常人和病人进行双样本T检验,但是,问题是,我在想每个个体的map在计数前得先卡个阈值,可是卡多大呢?还有是在全脑内计数,还是在一个motor网络的mask内计数呢?而这个mask我选择什么呢?

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