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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 DynamicBC_V1.1_20140710.  

Manual could also be downloaded here.

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)

有几个问题。

老师们好,我在投稿的过程中遇到些问题,想请教下。

1) reviewer说臧老师在2004年的ReHo的第一篇文章中,smooth是在计算ReHo之前做的,现在改到之后做,原因是什么?

2)我做了全脑的Voxel-wise的相关性后,选了ROI做了相关性,reviewer认为在没有先验假设ROI的情况下,做ROI-wise是错误的,会增加统计学错误。奇怪,我看别人的文章似乎都是这么做的。但是我改用ANOVA的voxel-wise的结果做了MASK,结果也比ROI-wise的结果更加符合我的假设。

3)正常人的ALFF和ReHo值是高度相关的么?

关于Deparsf处理DKI图像的问题

我在用Deparsf处理DKI的图像,做空间标准化,我想问下,是不是DKI图像也需要做Slicetiming等等步骤,还是直接空间标准化就好了?

Multiple positions available in Hangzhou Normal University (Research Assistant, Junior Faculty, student)

At the Center for Cognition and Brain Disorders (CCBD), Hangzhou Normal University, we are recruiting one junior faculty, one research assistant, and one or two postdocs in the field of functional neuroimaging. Requirements for faculty and postdocs are: PhD in MRI, EE, BME, CS, or math. Salary for junior faculty depends on the track record and potentials and can be up to 300,000 RMB/year.

Dprasf 预处理后图像的问题,用其他方法预处理则没有出现,求解

请教一下各位老师们

为什么我用Dprasf 预处理后图像在脑底部出现黑色条带(见附件),而用其他方法预处理则没有出现?是否可以通过修改dparsf的处理过程得到改善,这样的结果对后面的分析会产生怎样的影响?

非常感谢!

the way of normalize

各位老师,

请教一下,在常用的dparsf软件中做normalize 是用的什么方法? 

非常感谢!

echo

Resting-State fMRI Free Webinar Course – Jan 25th, 2016

Dear Colleagues,
 

突然想到,那些DTI之类的图像处理,不是也可以用DPARSF进行空间标准化么?

呵呵,突然想到的,这样可行么?

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