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Data Processing & Analysis of Resting-State fMRI
Chao-Gan YAN, Ph.D. 严超赣 Research Scientist The Nathan Kline Institute for Psychiatric Research Research Assistant Professor Department of Child and Adolescent Psychiatry / NYU Langone Medical Center Child Study Center, New York University
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 2
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DPARSF (Yan and Zang, 2010) 3
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Data Processing Assistant for Resting-State fMRI (DPARSF)
Yan and Zang, Front Syst Neurosci. 4
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DPABI: a toolbox for Data Processing & Analysis of Brain Imaging
License: GNU GPL Chao-Gan Yan Programmer Initiator Xin-Di Wang Programmer 5
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 6
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Data Organization ProcessingDemoData.zip FunRaw T1Raw
Sub_001 Sub_002 Sub_003 T1Raw Functional DICOM data Structural DICOM data 7
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Data Organization ProcessingDemoData.zip FunImg T1Img
Sub_001 Sub_002 Sub_003 T1Img Functional NIfTI data (.nii.gz., .nii or .img) Structural NIfTI data (.nii.gz., .nii or .img) 8
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 11
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Preprocessing Working Dir where stored Starting Directory (e.g., FunRaw) Detected participants 13
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Detected participants
Preprocessing Detected participants 14
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(if 0, detect automatically) (if 0, detect from NIfTI header)
Preprocessing Number of time points (if 0, detect automatically) TR (if 0, detect from NIfTI header) Template Parameters 15
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Resting State fMRI Data Processing
Template Parameters 16
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What’s new? 17
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Reorient and Quality control
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For checking EPI coverage and generating group mask
Automask generation For checking EPI coverage and generating group mask FunImgAR/Sub_001 Masks/AutoMasks/ 20
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Brain extraction (Skullstrip)
For better coregistration For Linux and Mac: Need to install FSL. For Windows: Thanks to Chris Rorden's compiled version of bet in MRIcroN, our modified version can work on NIfTI images directly. 21
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Bet & Coregistration Segment bet Apply Coregister T1ImgCoreg/Sub_001
T1Img/Sub_001 RealignParameter/Sub_001/mean*.nii Apply Coregister RealignParameter/Sub_001/Bet_mean*.nii T1ImgBet/Sub_001 22
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Nuisance regression 23
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Nuisance Regression Mask based on segmentation or SPM apriori
CompCor or mean [note: for CompCor, detrend (demean) and variance normalization will be applied before PCA, according to Behzadi et al., 2007] Global Signal based on Automask 24
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 25
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R-fMRI measures Calculation
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 27
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Quality Control 29
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Quality Control 30
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Quality Control 31
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Quality Control 32
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Quality Control 33
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Quality Control 34
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Quality Control 35
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Quality Control 36
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Quality Control 37
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Quality Control 38
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Quality Control 39
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Quality Control 40
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This mask is very important for group statistical analysis!!!
Quality Control This mask is very important for group statistical analysis!!! 41
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Quality Control 42
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Quality Control 43
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Quality Control 44
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Quality Control Using the visual inspection step within DPARSF, subjects showing severe head motion in the T1 image and subjects showing extremely poor coverage in the functional images, as well as subjects showing bad registration were excluded Subjects with overlap with the group mask (voxels present at least 90% of the participants) less than 2*SD under the group mean overlap (threshold: 92.2%) were excluded Subjects with motion (Mean FD Jenkinson greater than 2*SD above the group mean motion (threshold: 0.192) were excluded Yan et al., 2013, Neuroimage 45
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 46
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Statistical Analysis 48
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{DPABI_Dir}/StatisticalAnalysis/y_GroupAnalysis_Image.m
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Attention!!! 50
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{DPABI_Dir}/StatisticalAnalysis/y_GroupAnalysis_Image.m
Smoothness estimation based on the 4D residual is built in this function!!! 51
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{Download}/ProcessingDemoData/StatisticalDemo/AD_MCI_NC/
Statistical Analysis {Download}/ProcessingDemoData/StatisticalDemo/AD_MCI_NC/ ALFF: AD – NC Two Sample T Test: Applied smooth kernel in preprocessing: [4 4 4] Smooth kernel estimated on 4D residual: [ ] Smooth kernel estimated on statistical image (T to Z, as in easythresh): [ ] ReHo: AD – NC Two Sample T Test: Smooth kernel estimated on 4D residual: [ ] Smooth kernel estimated on statistical image (T to Z, as in easythresh): [ ] Thus, only using smooth kernel applied in preprocessing is NOT sufficient!!! 52
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Outline Overview Data Preparation Preprocessing
R-fMRI measures Calculation Quality Control Statistical Analysis Results Viewing 53
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Voxel Z > 2.3, Cluster P < 0.05, Two One-Tailed Corrections:
equivalent to Voxel P < , Cluster P < 0.1, Two Tailed. 61
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Further Help Further questions: http://rfmri.org/dpabi
The R-fMRI Network 68 68
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Further Help 69 69
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Send emails only to rfmri. org@gmail
Send s only to 1) sending new means you are posting your personal blogs, 2) replying means you are posting comments to that topic/blog, 3) then all the other R-fMRI nodes will receive updates of your posts. 72 72
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Xin-Di Wang Programmer Yu-Feng Zang Consultant
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Acknowledgments Nathan Kline Institute Charles Schroeder
Stan Colcombe Gary Linn Mark Klinger Hangzhou Normal University Yu-Feng Zang Beijing Normal University Yong He NYU Child Study Center F. Xavier Castellanos Adriana Di Martino Clare Kelly Fudan University Tian-Ming Qiu Chinese Academy of Sciences Xi-Nian Zuo Different Axis!!! Child Mind Institute Michael P. Milham R. Cameron Craddock Zhen Yang Princeton University Han Liu
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Advertisement Charles E. Schroeder F. Xavier Castellanos NKI/Columbia
NKI/NYU Charles E. Schroeder NKI/Columbia David A. Leopold NIMH 75
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Thanks for your attention!
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