Data Processing of Resting-State fMRI (Part 2) - PowerPoint PPT Presentation

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Data Processing of Resting-State fMRI (Part 2)

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Data Processing of Resting-State fMRI (Part 2) YAN Chao-Gan Ph. D. ycg.yan_at_gmail.com State Key Laboratory of Cognitive Neuroscience and Learning, – PowerPoint PPT presentation

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Title: Data Processing of Resting-State fMRI (Part 2)


1
Data Processing of Resting-State fMRI (Part 2)
YAN Chao-Gan ??? Ph. D. ycg.yan_at_gmail.com Stat
e Key Laboratory of Cognitive Neuroscience and
Learning, Beijing Normal University, China
2
Outline
  • Statistical Analysis
  • Results Viewing
  • Multiple Comparisons
  • REST Image Calculator
  • Other Functions

3
Statistical Analysis
One sample T test Two Sample T test Paired T
test ANOVA analysis
4
One sample T test
  • Preparation
  • ALFF mALFF-1
  • fALFF mfALFF-1
  • ReHo smReHo-1
  • FC zFC

5
One sample T test
6
One sample T test
smReHo mALFF
g1-1
7
One sample T test
8
One sample T test
m-1 images zFC images
Brain Mask
Directory for saving SPM.mat
9
One sample T test
The generated spm.mat
10
One sample T test
The generated spm.mat
1
11
One sample T test
spmT_0001.img
HeightthresholdT 2.687659 plt0.05(FDR) Extentth
resholdk 10 voxels
12
Two sample T test
  • Preparation
  • ALFFmALFF
  • fALFF mfALFF
  • ReHo smReHo
  • FC zFC
  • Mask

13
Two sample T test
  • Mask
  • Brain Mask
  • Mask(Patient_1T.imggtThrd)(CON_1T.imggtThrd)gt0

Patient_1T.img CON_1T.img
Mask_2T.img
(i1gt1.96i2gt1.96)gt0
14
Two sample T test
Brain Mask or Mask_2T.img
m or zFC images for the two groups
Directory for saving SPM.mat
15
Two sample T test
The generated spm.mat
16
Two sample T test
The generated spm.mat
1 -1
17
Two sample T test
spmT_0001.img
HeightthresholdT Inf plt0.05(FDR) Extentthresho
ldk 0 voxels
18
Paired T test
19
Paired T test
m or zFC images for each pair
Brain Mask
20
Paired T test
21
ANOVA Analysis
22
ANOVA Analysis
3
Corresponding level
Images for this group
23
ANOVA Analysis
24
Statistical Analysis in REST
25
One-Sample T-Test
0 for m-1 images 1 for m images
Brain Mask
T Statistic Image
26
Two-Sample T-Test
T Statistic Image positive corresponds to the
mean of Group 1 is greater than the mean of Group
2
27
Two-Sample T-Test
Two-Sample T-Test with covariates e.g. gray
matter proportion images (Oakes et al., 2007,
Neuroimage)
Please make sure the correspondence between the
group images and the covariate images order and
voxel size
Other covariate can be also specified as text
files. (E.g. age, brain size, IQ etc.)
28
Paired T-Test
Situation 1 Situation 2 Please make sure
the correspondence
T Statistic Image
29
ANOVA or ANCOVA
ANCOVA e.g. gray matter proportion images (Oakes
et al., 2007, Neuroimage)
F Statistic Image
Please make sure the correspondence between the
group images and the covariate images order and
voxel size
Other covariate can be also specified as text
files. (E.g. age, brain size, IQ etc.)
30
Correlation Analysis
The imaging measure ALFF maps
Traits e.g. MMSE.txt 19 15 23 14 23
31
Outline
  • Statistical Analysis
  • Results Viewing
  • Multiple Comparisons
  • REST Image Calculator
  • Other Functions

32
Results Viewing
  • SPM5
  • xjview
  • MRIcroN
  • REST Slice Viewer

33
Results Viewing - SPM5
34
Results Viewing - SPM5
35
Results Viewing - xjview
36
????xjview
37
Results Viewing - MRIcroN
38
REST Slice Viewer
39
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41
For Voxel size 333
Voxels are connected if their faces touch rmm4
Voxels are connected if their faces or edges
touch rmm5 SPM_Criterion
Voxels are connected if their faces, edges, or
corners touch rmm6
42
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47
This report is based on CUI Xu's xjview.
(http//www.alivelearn.net/xjview/) Revised by
YAN Chao-Gan and ZHU Wei-Xuan 20091108 suitable
for different Cluster Connectivity Criterion
surface connected, edge connected, corner
connected. Number of clusters found
7 ---------------------- Cluster 1 Number of
voxels 59 Peak MNI coordinate 27 6 -45 Peak
MNI coordinate region // Right Cerebrum //
Temporal Lobe // Superior Temporal Gyrus // White
Matter // undefined // Temporal_Inf_R (aal) Peak
intensity 3.5023 voxels structure
59 --TOTAL VOXELS-- 40 Right Cerebrum
33 Temporal Lobe 20 White Matter
19 Temporal_Inf_R (aal) 16 Gray Matter
14 Superior Temporal Gyrus 13 Fusiform_R
(aal) 11 brodmann area 38 8 Inferior
Temporal Gyrus 7 Middle Temporal Gyrus
7 Limbic Lobe 6 Uncus 6 Temporal_Pole_Mid_
R (aal) 5 brodmann area 20
3 Sub-Gyral ---------------------- Cluster
2 Number of voxels 98 Peak MNI coordinate -9
-78 -51
48
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50
Create Brodmann Mask
Template\brodmann.nii Or Template\Brodmann_61x73x6
1.nii
51
Create Brodmann Mask
52
Data Resample
0 Nearest Neighbor 1 Trilinear 2- 2nd degree
b-spline
53
Outline
  • Statistical Analysis
  • Results Viewing
  • Multiple Comparisons
  • REST Image Calculator
  • Other Functions

54
Multiple Comparisons
P0.05 Probability of not getting a false
positive result 1 - 0.05 0.95
P0.05 Probability of not getting a false
positive result 1 - 0.05 0.95
P0.05 Probability of not getting a false
positive result 1 - 0.05 0.95
P0.05 Probability of not getting a false
positive result 1 - 0.05 0.95
P0.05 Probability of not getting a false
positive result 1 - 0.05 0.95
0.95 0.95 0.95 0.95
0.95 0.9550.774
55
Multiple Comparisons
  • Bonferroni correction 0.05/50.01
  • Family-Wise Error (FWE) correction
  • False Discovery Rates (FDR) correction
  • Monte Carlo simulations (AlphaSim)

56
FDR Theory
  • False discovery rate QeE(V/(VS))E(V/R)

Benjamini and Hochberg, 1995, Journal of the
Royal Statistical Society
56
57
FDR Theory
  • Let H1, , Hm be the null hypotheses and P1, ,
    Pm their corresponding p-values. Order these
    values in increasing order and denote them by
    P(1), , P(m). For a given q, find the largest k
    such that P(k) ? kq/m.
  • Then reject (i.e. declare positive) all H(i) for
    i 1, , k.

57
58
FDR in REST
58
59
FDR in REST
59
60
FDR in REST
60
61
Multiple Comparisons
Monte Carlo simulations (AlphaSim)
?
62
REST AlphaSim
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64
Cl Size Frequency Cum Prop p/Voxel Max
Freq Alpha 1 235971 0.619898 0.009613 0 1.00000
0 2 76150 0.819945 0.006282 0 1.000000 3 32297
0.904789 0.004131 0 1.000000 4 15940 0.946664
0.002763 0 1.000000 5 8476 0.968930 0.001863 0
1.000000 6 4786 0.981503 0.001265 1 1.000000
7 2767 0.988772 0.000860 19 0.999000 8 1606 0
.992991 0.000586 51 0.980000 9 1011 0.995647 0.
000405 127 0.929000 10 585 0.997184 0.000276 13
2 0.802000 11 391 0.998211 0.000194 172 0.6700
00 12 236 0.998831 0.000133 146 0.498000 13 16
4 0.999262 0.000093 107 0.352000 14 98 0.99951
9 0.000063 78 0.245000 15 69 0.999701 0.000043
61 0.167000 16 37 0.999798 0.000029 30 0.10600
0 17 22 0.999856 0.000020 22 0.076000 18 22 0
.999913 0.000015 21 0.054000 19 11 0.999942 0.0
00010 11 0.033000 20 7 0.999961 0.000007 7 0.0
22000 21 5 0.999974 0.000005 5 0.015000 22 5
0.999987 0.000003 5 0.010000 23 4 0.999997 0.00
0002 4 0.005000 24 1 1.000000 0.000000 1 0.001
000
65
Outline
  • Statistical Analysis
  • Results Viewing
  • Multiple Comparisons
  • REST Image Calculator
  • Other Functions

66
REST Image Calculator
67
REST Image Calculator
68
REST Image Calculator
  • Example expressions
  • (a) g1-1 Subtract 1 from each image in
    group 1
  • (b) g1-g2 Subtract each image in group 2
    from each corresponding image in group1
  • (c) i1-i2 Subtract image 2 from image 1
  • (d) i1gt100 Make a binary mask image at
    threshold of 100
  • (e) g1.(i1gt100) Make a mask and then
    apply to each image in group 1
  • mean(g1) Calculate the mean image of group 1
  • (i1-mean(g1))./std(g1) Calculate the z value of
    i1 related to group 1
  • (g) corr(g1,g2,''temporal'') Calculate
    the temporal correlation between two groups, i.e.
    one correlation coefficient between two ''time
    courses'' for each voxel.
  • (h) corr(g1,g2,''spatial'') Calculate
    the spatial correlation between two groups, i.e.
    one correlation coefficient between two images
    for each ''time point''.

69
Outline
  • Statistical Analysis
  • Results Viewing
  • Multiple Comparisons
  • REST Image Calculator
  • Other Functions

70
Power Spectrum
71
Power Spectrum
72
Power Spectrum
73
Power Spectrum
74
Granger Causality Analysis
Contributed by Mr. ZANG Zhen-Xiang
75
Theory of Granger Causality
Signed path coefficient Chen et al, 2009, ISMRM
Granger 1969 Ding et al., 2006
76
Theory of Granger Causality
Residual based
Granger 1969 Ding et al., 2006
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NIfTI nii to NIfTI pairs
79
NIfTI .nii to NIfTI pairs
80
Reading and Writing functions
Reading Data Vox Headrest_readfile('brodmann.n
ii') Data 181217181 double Vox
1 1 1 Head - Structure Processing BA20
Data(Data20) Writing rest_WriteNiftiImage(BA
20Data,Head,'BA20.img')
81
Solve Problem "Out Of Memory"
1. Reboot your computer and do not run any other
programs. 2. Enlarge your memory. 3. MATLAB
Version 7.1 or above is suggested. 4. You can
turn on the 3GB switch of Windows XP!!! Please
see more details in http//msdn.microsoft.com/en-u
s/library/ff556232.aspx. 5. If this problem
remains, please install Linux, especially 64 bit
Linux and Matlab.
82
Solve Problem "Out Of Memory"
Enable the 3GB switch on Windows XP
Right-click My Computer -gt Properties -gt Advanced
-gt Startup and Recovery -gt Settings -gt Edit.
Modify the following line (maybe not exactly
same) in the boot.ini file multi(0)disk(0)rdisk(
0)partition(1)\WINDOWS"WinXP Pro 3GB"
/noexecuteoptin /fastdetect /3GB Save and
close -gt Restart your computer. Enable the 3GB
switch on Windows Vista and Windows 7 (32-bit)
Right-click Command Prompt in the Accessories
program group of the Start menu. Click Run as
Administrator. At the command prompt, enter
"bcdedit /set IncreaseUserVa 3072" Restart
the computer.
83
Further Help
Further questions
www.restfmri.net
84
Thanks to
SPM Team Wellcome Department of Imaging
Neuroscience, UCL MRIcroN Team Chris
RORDEN Xjview Team CUI Xu
  • DONG Zhang-Ye
  • GUO Xiao-Juan
  • HE Yong
  • LONG Xiang-Yu
  • SONG Xiao-Wei
  • YAO Li
  • ZANG Yu-Feng
  • ZHANG Han
  • ZHU Chao-Zhe
  • ZOU Qi-Hong
  • ZUO Xi-Nian

All the group members!
85
  • Thanks for your attention!
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