Notes on How to Run Meta-Analysis
1. ale
A. Make a list of Talairach or MNI coordinates reported in the literature. Place these in a text file, e.g. named Foci.txt, with one XYZ coordinate per line (example, p. 3).
B. Select spatial spread (FWHM in mm) – 12 or 14.12892
C. ale Foci.txt 14.12892 ale.txt ale.img –medx
D. Generates an ALE map (“ALE” stands for Activation Likelihood Estimation).
2. brainNull
A. Count # of foci fed to the ale program (e.g., # of lines in Foci.txt file). Select # bins, # simulations. Use the same FWHM that was used for the ale program.
B. brainNull masked.txt 1601 172 1000 14.12892 brainNull.txt
C. To select an ALE threshold for uncorrected p-level of 0.0001, open up the output text file (e.g., brainNull.txt), and look at the 5th column of numbers, which are the p-values. Find the p-value that is closest to 0.0001. Then look at the corresponding value in the first column of numbers. This is the ALE value, scaled up by 1,000,000; the ALE threshold is therefore this value divided by 1,000,000 (example, p. 4).
3. ale_paper_id
A. Same list of Talairach or MNI coordinates as in 1(A), but include a 4th column indicating paper # (numbering MUST begin with 0, not 1!) (example, p. 5).
B. Make a separate list of coordinates of interest. These can be, e.g., local maxima in the ALE map. As in 1(A), this text file has three columns of numbers
C. Outputs contribution of each paper to each coordinate of interest (example, p. 6).
D. ale_paper_id FociWithPapers.txt Peaks.txt ale_paper_id.txt 111 11 14 14.12892
4. Finding local maxima can be done in MEDx as follows.
A. Using MEDx.
B. Open original ALE map or resliced 32bit version (see 5(A)) into new folder.
C. Select Toolbox à Functional à Local Min/Max
D. Set: report top 100 (or whatever), threshold = ALE threshold selected (e.g., 2(C) above); image = ALE map.
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Sample input for program ale
8 64 21
-52 -30 0
-10 -106 6
28 26 40
22 36 32
54 -48 32
-54 -50 14
-60 -56 0
-52 -60 -14
-52 -64 -6
6 -9 56
-32 0 44
-44 -23 3
-34 -15 4
18 -7 8
34 6 5
-44 -43 28
-6 -74 31
40 -65 27
-48 -40 -21
-51 -58 6
-18 3 -19
48 -30 -26
46 -60 6
44 -20 -6
-2 -10 39
-18 33 -3
8 -3 -15
-44 -43 28
-48 -42 -22
-61 -41 -12
-51 -35 7
-22 3 -19
46 -58 6
42 -21 -1
40 -8 0
14 3 -24
-22 33 -3
-40 13 27
-6 -78 26
-28 -35 46
53 -24 29
4 -75 22
-42 -28 -21
Sample output produced by program brainNull
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3790 1286 5.28533e-06 0.999809 0.000190854
3800 966 3.97016e-06 0.999813 0.000186861
3810 877 3.60438e-06 0.999817 0.000183284
3820 848 3.48519e-06 0.99982 0.000179768
3830 795 3.26737e-06 0.999824 0.000176489
3840 790 3.24682e-06 0.999827 0.000173271
3850 729 2.99612e-06 0.99983 0.00017029
3860 708 2.90981e-06 0.999833 0.00016737
3870 790 3.24682e-06 0.999836 0.000164092
3880 2297 9.44044e-06 0.999845 0.000154674
3890 957 3.93317e-06 0.999849 0.00015074
3900 1508 6.19773e-06 0.999855 0.000144541
3910 901 3.70302e-06 0.999859 0.000140846
3920 793 3.25915e-06 0.999862 0.000137568
3930 831 3.41533e-06 0.999866 0.00013417
3940 633 2.60157e-06 0.999868 0.000131547
3950 546 2.244e-06 0.999871 0.000129342
3960 550 2.26044e-06 0.999873 0.000127077
3970 714 2.93447e-06 0.999876 0.000124097
3980 930 3.82221e-06 0.99988 0.000120282
3990 686 2.81939e-06 0.999883 0.000117481
4000 1378 5.66344e-06 0.999888 0.000111818
4010 761 3.12763e-06 0.999891 0.000108659
4020 679 2.79062e-06 0.999894 0.000105917
4030 712 2.92625e-06 0.999897 0.000102997
4040 633 2.60157e-06 0.9999 0.000100374
4050 483 1.98508e-06 0.999902 9.84073e-05
4060 503 2.06728e-06 0.999904 9.63211e-05
4070 390 1.60286e-06 0.999905 9.47118e-05
4080 469 1.92754e-06 0.999907 9.28044e-05
4090 1018 4.18388e-06 0.999911 8.85725e-05
4100 737 3.029e-06 0.999914 8.55923e-05
4110 526 2.16181e-06 0.999917 8.33869e-05
4120 604 2.48238e-06 0.999919 8.09431e-05
4130 475 1.9522e-06 0.999921 7.89762e-05
4140 449 1.84534e-06 0.999923 7.71284e-05
4150 344 1.41381e-06 0.999924 7.56979e-05
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Sample input for program ale_paper_id
-2 -80 0 0
6 -80 -18 0
16 -100 -8 0
12 -104 0 0
-28 -86 -26 0
-16 -54 -28 0
-54 -68 -14 0
-48 -56 -6 0
-42 -50 -4 1
-42 -62 -14 1
-44 -76 -18 1
-46 -36 -24 1
-54 6 0 2
-58 -26 52 2
-4 -68 24 2
30 -50 22 2
-22 -38 -20 2
6 -62 50 2
-43 11 10 3
-20 -20 10 3
-36 9 10 4
-20 -20 10 4
8 64 21 5
-52 -30 0 5
-10 -106 6 5
28 26 40 6
22 36 32 6
54 -48 32 6
-54 -50 14 7
-60 -56 0 7
-52 -60 -14 7
-52 -64 -6 7
6 -9 56 8
-32 0 44 8
18 -7 8 8
34 6 5 8
-44 -43 28 9
-6 -74 31 9
40 -65 27 9
-48 -40 -21 9
-18 3 -19 9
48 -30 -26 9
46 -60 6 9
44 -20 -6 9
-2 -10 39 9
Sample output produced by program ale_paper_id
-50 25 -6 0.0000
0 0.00000000
1 0.00000000
2 73.86647197
3 21.75920228
4 1.22757006
5 0.00000000
6 0.00000000
7 0.00000000
8 0.00000004
9 0.00553079
10 0.15524565
11 0.00000526
12 2.98597396
13 0.00000000
44 -15 -4 0.0067
0 0.00000000
1 0.00000000
2 0.29885938
3 0.00000000
4 0.00000000
5 0.00000000
6 0.00000000
7 0.00000000
8 0.00636709
9 23.42068335
10 29.09973060
11 17.92556611
12 29.24879348
13 0.00000000
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