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Statistical analysis of PET data using FMRISTAT (!)

Statistical analysis of PET data using FMRISTAT (!). Keith Worsley Department of Mathematics and Statistics, McConnell Brain Imaging Centre, McGill University. c:/keith/fMRI/manou/cbf non kin/bach allan -h1 tal 200008161003.mnc, slice 21. 4. x 10. 4. 1. 6. 11. 16. 21. 25. 30. 35. 40.

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Statistical analysis of PET data using FMRISTAT (!)

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  1. Statistical analysis of PET data using FMRISTAT (!) Keith Worsley Department of Mathematics and Statistics, McConnell Brain Imaging Centre, McGill University

  2. c:/keith/fMRI/manou/cbf non kin/bach allan -h1 tal 200008161003.mnc, slice 21 4 x 10 4 1 6 11 16 21 25 30 35 40 45 50 55 60 65 3.5 2 7 12 17 22 26 31 36 41 46 51 56 61 66 3 4 3 2 1 Task 2.5 3 8 13 18 23 27 32 37 42 47 52 57 62 67 2 4 9 14 19 24 28 33 38 43 48 53 58 63 68 1.5 1 5 10 15 20 29 34 39 44 49 54 59 64 69 0.5 0 Subjects CBF non kinetic • Unnormalized data (z = -6 mm) base

  3. c:/keith/fMRI/manou/cbf non kin/normalized, slice 21 1.5 1 6 11 16 21 25 30 35 40 45 50 55 60 65 2 7 12 17 22 26 31 36 41 46 51 56 61 66 4 3 2 1 Task 1 3 8 13 18 23 27 32 37 42 47 52 57 62 67 4 9 14 19 24 28 33 38 43 48 53 58 63 68 0.5 5 10 15 20 29 34 39 44 49 54 59 64 69 0 Subjects CBF non-kinetic • Normalized: thresh at ½ max, average, divide base

  4. Correlation models Independent scans Autocorrelation AR(1) Autocorrelation AR(2) All correlations DF: (#subj-1) × (#scans-1) = 51 Depends on correlations, contrast (#subj-1) = 13 Standard error of contrasts: bias variance Safest: DOT, FMRISTAT boost df by pooling/smoothing SPM?

  5. Is pooling sd valid?Is sd constant across the brain?Unsmoothed sd assuming independent scans, 51 df: Pooled Sd = 0.027

  6. 100 100 50 50 0 0 0 0 5 5 10 10 Infinity FMRISTAT: smoothing instead of poolingEffective df depends on FWHMsd: FWHMsd2 3/2 FWHMdata2 dfeff = dfresidual(2 + 1) e.g. FWHMdata = 8.3 mm: Infinity pooled sd, dfeff = infinity Target = 100 df dfeff independent no smoothing, dfeff = 51 dfeff = 13 all correlations FWHM = 10.0 mm FWHMsd FWHM = 4.4 mm

  7. FMRISTAT: smooth sd by FWHM = 4.4 mm, df = 100

  8. CBF non kinetic (z = 57 mm) T statistic SD: Voxel Smooth Pooled DF: 51 100 infinite Effect is always same

  9. Stat_summarytask 4 – base CLUSTERS: clus vol resel Pval (one) 1 4688 10.92 0 ( 0) 2 7067 10.58 0 ( 0) 3 947 1.6 0.033 (0.001) 4 543 0.88 0.22 ( 0.01) 5 415 0.75 0.323 (0.015) 6 169 0.39 0.788 ( 0.06) Effective FWHM: 15 PEAKS: clus peak Pval (one) Qval (i j k) ( x y z ) 2 8.03 0 ( 0) 0 ( 35 62 64) (-38.9 -19.4 58.5) 1 6.8 0 ( 0) 0 ( 81 40 13) ( 22.8 -57.3 -18) 1 6.58 0 ( 0) 0 ( 76 43 11) ( 16.1 -52.1 -21) 2 6.34 0 ( 0) 0 ( 39 59 67) (-33.5 -24.6 63) 2 6.33 0 ( 0) 0 ( 42 64 70) (-29.5 -16 67.5) 1 5.41 0.019 (0.001) 0 ( 70 42 12) ( 8 -53.8 -19.5) 1 5.4 0.02 (0.001) 0 ( 68 41 13) ( 5.4 -55.6 -18) 1 5.38 0.021 (0.001) 0 ( 69 42 13) ( 6.7 -53.8 -18) 2 5.25 0.037 (0.002) 0 ( 30 57 63) (-45.6 -28 57) 3 5.08 0.076 (0.004) 0.001 ( 17 76 42) ( -63 4.6 25.5) 2 5 0.104 (0.005) 0.001 ( 31 59 64) (-44.2 -24.6 58.5) 9 4.9 0.155 (0.007) 0.001 ( 14 67 12) ( -67 -10.8 -19.5) 3 4.85 0.191 (0.008) 0.001 ( 16 75 42) (-64.3 2.9 25.5) 5 4.81 0.223 ( 0.01) 0.001 ( 65 77 61) ( 1.3 6.4 54) 10 5 0

  10. c:/keith/fMRI/manou/cbf kin/bach allan -h1 sumpetkinetic tal 200008161003.mnc, slice 21 80 1 6 11 19 24 29 34 39 44 49 54 59 64 70 2 7 12 20 25 30 35 40 45 50 55 60 65 60 4 3 2 1 Task 50 3 8 13 16 21 26 31 36 41 46 51 56 61 66 40 4 9 14 17 22 27 32 37 42 47 52 57 62 67 30 20 5 10 15 18 23 28 33 38 43 48 53 58 63 68 10 0 Subjects CBF kinetic • Unnormalized, z= -6 mm base

  11. Is pooling sd valid?Is sd constant across the brain?Unsmoothed sd assuming independent scans, 51 df: Pooled Sd = 7.2

  12. CBF kinetic (z = 57 mm) T statistic SD: Voxel Smooth Pooled DF: 51 100 infinite Effect is always same

  13. T stat, smoothed sd, 100 dfCBF non kinetic vs. kinetic

  14. Stat_summarytask 4 – base (search region is where CBF non kinetic T > 5) CLUSTERS: clus vol resel Pval (one) 1 1338 3.11 0 (0.002) 2 363 1 0.008 (0.043) Effective FWHM: PEAKS: clus peak Pval (one) Qval (i j k) ( x y z ) 1 6.24 0 ( 0) 0 (33 63 61) (-41.5 -17.7 54) 1 5.32 0 ( 0) 0 (32 62 63) (-42.9 -19.4 57) 1 5.14 0 (0.001) 0 (35 63 60) (-38.9 -17.7 52.5) 2 4.82 0.001 (0.003) 0 (79 43 11) ( 20.1 -52.1 -21) 2 4.48 0.003 (0.009) 0 (78 44 12) ( 18.8 -50.4 -19.5) 2 4.32 0.005 (0.015) 0 (81 42 11) ( 22.8 -53.8 -21) 1 4.3 0.005 (0.015) 0 (41 62 70) (-30.8 -19.4 67.5) 1 4.19 0.007 (0.021) 0 (40 61 69) (-32.2 -21.2 66) 1 4.16 0.007 (0.023) 0 (32 60 66) (-42.9 -22.9 61.5) 6 3.91 0.016 (0.049) 0.001 (31 59 64) (-44.2 -24.6 58.5) 2 3.64 0.034 (0.099) 0.001 (81 41 10) ( 22.8 -55.6 -22.5) 2 3.52 0.047 (0.135) 0.002 (82 41 11) ( 24.1 -55.6 -21) 1 3.5 0.05 (0.143) 0.002 (39 58 69) (-33.5 -26.3 66) 3 3.42 0.062 (0.175) 0.002 (30 58 64) (-45.6 -26.3 58.5) 1 3.33 0.077 (0.214) 0.002 (38 65 68) (-34.8 -14.3 64.5) 2 3.16 0.116 (0.313) 0.003 (82 38 10) ( 24.1 -60.7 -22.5) 15 10 5 0

  15. c:/keith/fMRI/manou/cmro kin/bach allan -o1 sumpetkinetic tal 200008161158.mnc, slice 21 300 1 6 11 16 21 26 31 36 45 50 55 60 65 250 2 7 12 17 22 27 32 37 41 46 51 56 61 66 4 3 2 1 Task 200 3 8 13 18 23 28 33 38 42 47 52 57 62 67 150 4 9 14 19 24 29 34 39 43 48 53 58 63 68 100 5 10 15 20 25 30 35 40 44 49 54 59 64 69 50 0 Subjects CMRO kinetic • Unnormalized, z = -6 mm base

  16. CMRO kinetic • Unnormalized, smoothed 16mm FWHM

  17. Is pooling sd valid?Is sd constant across the brain?Unsmoothed sd assuming independent scans, 48 df: Pooled Sd = 12.7

  18. CMRO kinetic T statistic, z = 57 mm SD: Voxel Smooth Pooled DF: 48 100 infinite T statistic, z = -6 mm SD: Voxel Smooth Pooled DF: 48 100 infinite

  19. Sd 30 0 1 8 1 16 1 24 1 32 1 40 1 48 1 56 1 64 1 72 1 20 0 2 8 2 16 2 24 2 32 2 40 2 48 2 56 2 64 2 72 2 10 0 T statistics 6 0 1 8 1 16 1 24 1 32 1 40 1 48 1 56 1 64 1 72 1 4 0 2 8 2 16 2 24 2 32 2 40 2 48 2 56 2 64 2 72 2 2 0 0 3 8 3 16 3 24 3 32 3 40 3 48 3 56 3 64 3 72 3 -2 CMRO kinetic smoothed 16 mm,“safe” analysis of task 3 - base Unsmoothed sd, 12 df Sd smoothed 26 mm, 100 df Unsmoothed sd, 12 df T = 6.79 Sd smoothed 26 mm, 100 df T = 4.14 Pooled sd, infinite df T = 3.93

  20. Stat_summarytask 3 – base CLUSTERS: clus vol resel Pval (one) 1 927 0.25 0.179 (0.121) 2 211 0.06 0.485 (0.409) 3 138 0.05 0.545 (0.485) 4 266 0.04 0.554 (0.498) 40 Effective FWHM: 30 PEAKS: clus peak Pval (one) Qval (i j k) ( x y z ) 1 4.42 0.065 (0.034) 0.651 (37 107 40) (-36.2 58 22.5) 1 4.41 0.068 (0.036) 0.651 (35 106 39) (-38.9 56.2 21) 1 4.41 0.068 (0.036) 0.651 (36 106 40) (-37.5 56.2 22.5) 1 4.37 0.077 (0.041) 0.651 (37 106 42) (-36.2 56.2 25.5) 1 4.32 0.089 (0.047) 0.651 (36 107 38) (-37.5 58 19.5) . . . 4 3.44 1.072 ( 0.54) 1.003 (83 75 21) ( 25.5 2.9 -6) 4 3.44 1.091 (0.549) 1.003 (82 75 22) ( 24.1 2.9 -4.5) 20 10 0

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