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Doctor cao,In REST Version: 1.3,I want to know the difference of ALFF and fALFF.can you tell me the page in you web which tell about it.
thanks
I am trying to use the rest_Y_RegressOutCovariables function to write our covariable-corrected image files. I get the error below, which I was hoping you could help me with. I've double-checked, and the timeseries vectors are the correct length.
Thanks for your help,
Alex
Dear REST experts
Recently , we moved our analysis platform from windows to 64 bits centos 5.3 system with Matlab R2009a
All the resting fmri data were processed by using DPARSF_V1.0_Beta_090701
when enter into the stage of remove linear trend , we meet the following error
could someone can help us to slove the problem ?
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Removing the linear trend:
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, nomalize, 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. This software 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. You also can download a MULTIMEDIA COURSE to know more about how to use this software. Add DPARSF's directory to MATLAB's path and enter "DPARSF" in the command window of MATLAB to enjoy it. The latest release is DPARSF_V1.0_100510.DOWNLOAD Multimedia Course: Data Processing of Resting-State fMRI |
New features of DPARSF_V1.0_100510:
1. Added a right-click menu to delete all the participants' ID.
2. Fixed a bug in converting DICOM files to NIfTI in Windows 7, thanks to Prof. Chris Rorden's new dcm2nii.
3. Now will detect if co* T1 image (T1 image which is reoriented to the nearest orthogonal direction to 'canonical space' and removed excess air surrounding the individual as well as parts of the neck below the cerebellum) exists before normalization by using T1 image unified segmentation. T1 image without 'co' is also allowed in the analysis now.
New features of DPARSF_V1.0_100420:
1. After extracting ROI time courses, not just functional connectivity will be calculated, but also transform the r values to z values by Fisher's z transformation.
2. Fixed a bug in generating pictures for checking normalization when the bounding box is not [-90 -126 -72;90 90 108].