Examples of GLM reports¶
First level report¶
ADHD¶
Adapted from Default Mode Network extraction of ADHD dataset
Statistical Report - First Level Model
ADHD DMN Report
Implement the General Linear Model for single run :term:`fMRI` data.
Description
Data were analyzed using Nilearn (version= 0.11.2.dev245+geee20d69f; RRID:SCR_001362).
At the subject level, a mass univariate analysis was performed with a linear regression at each voxel of the brain, using generalized least squares with a global ar1 noise model to account for temporal auto-correlation and a cosine drift model (high pass filter=0.01 Hz).
Model details
| Value | |
|---|---|
| Parameter | |
| drift_model | cosine |
| high_pass (Hertz) | 0.01 |
| hrf_model | glover |
| noise_model | ar1 |
| signal_scaling | 0 |
| slice_time_ref | 0.0 |
| standardize | False |
| t_r (seconds) | 2.0 |
Design Matrix
run 0
correlation matrix
Contrasts
Mask
Statistical Maps
seed_based_glm
Cluster Table
| Height control | bonferroni |
|---|---|
| α | 9.00E-4 |
| Threshold (computed) | 5.669 |
| Cluster size threshold (voxels) | 15 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|---|---|---|---|---|
| 1 | 3.0 | -54.0 | 18.0 | 13.01 | 12393 |
| 1a | 0.0 | -57.0 | 30.0 | 12.68 | |
| 1b | 0.0 | -48.0 | 30.0 | 11.96 | |
| 1c | -3.0 | -51.0 | 18.0 | 11.91 | |
| 2 | 0.0 | 51.0 | -6.0 | 11.08 | 5562 |
| 2a | 3.0 | 69.0 | 3.0 | 10.62 | |
| 2b | 0.0 | 57.0 | 3.0 | 10.31 | |
| 2c | 0.0 | 63.0 | 15.0 | 10.12 | |
| 3 | 57.0 | -66.0 | 27.0 | 10.91 | 1188 |
| 3a | 48.0 | -57.0 | 30.0 | 8.99 | |
| 3b | 51.0 | -69.0 | 27.0 | 8.51 | |
| 4 | 6.0 | -84.0 | -18.0 | 10.68 | 756 |
| 4a | -3.0 | -87.0 | -15.0 | 7.59 | |
| 5 | 18.0 | 42.0 | 51.0 | 9.99 | 513 |
| 6 | -63.0 | -12.0 | -9.0 | 9.20 | 540 |
| 6a | -63.0 | -18.0 | -15.0 | 9.05 | |
| 7 | -48.0 | -69.0 | 42.0 | 8.93 | 486 |
| 7a | -54.0 | -66.0 | 36.0 | 8.71 | |
| 8 | -42.0 | -72.0 | 33.0 | 8.72 | 729 |
| 9 | -12.0 | 39.0 | 54.0 | 8.52 | 432 |
| 9a | -15.0 | 30.0 | 51.0 | 7.87 | |
| 10 | -24.0 | 30.0 | 48.0 | 8.51 | 648 |
| 10a | -18.0 | 30.0 | 42.0 | 8.39 | |
| 11 | -36.0 | -54.0 | -24.0 | 8.04 | 756 |
| 11a | -45.0 | -54.0 | -21.0 | 7.61 | |
| 12 | -51.0 | -60.0 | 24.0 | 7.50 | 837 |
About
- Date preprocessed:
BIDS features¶
Adapted from First level analysis of a complete BIDS dataset from openneuro
Statistical Report - First Level Model
FLM Bids Features Stat maps
Implement the General Linear Model for single run :term:`fMRI` data.
Description
Data were analyzed using Nilearn (version= 0.11.2.dev245+geee20d69f; RRID:SCR_001362).
At the subject level, a mass univariate analysis was performed with a linear regression at each voxel of the brain, using generalized least squares with a global ar1 noise model to account for temporal auto-correlation and a cosine drift model (high pass filter=0.01 Hz).
Input images were smoothed with gaussian kernel (full-width at half maximum=5.0 mm).
The following contrasts were computed using a fixed-effect approach across runs :
- StopSuccess - Go
Model details
| Value | |
|---|---|
| Parameter | |
| drift_model | cosine |
| high_pass (Hertz) | 0.01 |
| hrf_model | glover |
| noise_model | ar1 |
| signal_scaling | 0 |
| slice_time_ref | 0.0 |
| smoothing_fwhm (mm) | 5.0 |
| standardize | False |
| subject_label | 10159 |
| t_r (seconds) | 2 |
Design Matrix
run 0
correlation matrix
Contrasts
Mask
Statistical Maps
StopSuccess - Go
Cluster Table
| Height control | fpr |
|---|---|
| α | 0.001 |
| Threshold (computed) | 3.291 |
| Cluster size threshold (voxels) | 3 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|---|---|---|---|---|
| 1 | -66.0 | -45.0 | 22.0 | 5.31 | 4176 |
| 1a | -66.0 | -33.0 | 18.0 | 4.67 | |
| 1b | -48.0 | -36.0 | 14.0 | 4.53 | |
| 1c | -60.0 | -30.0 | 10.0 | 4.11 | |
| 2 | -42.0 | 15.0 | 26.0 | 4.92 | 2196 |
| 2a | -51.0 | 9.0 | 34.0 | 4.72 | |
| 2b | -42.0 | 9.0 | 30.0 | 4.68 | |
| 2c | -57.0 | 12.0 | 38.0 | 4.59 | |
| 3 | -45.0 | -12.0 | 26.0 | 4.84 | 144 |
| 4 | 57.0 | -27.0 | 2.0 | 4.69 | 324 |
| 4a | 66.0 | -27.0 | 2.0 | 3.66 | |
| 5 | 54.0 | 9.0 | 14.0 | 4.65 | 144 |
| 6 | -66.0 | -30.0 | 6.0 | 4.51 | 144 |
| 7 | -6.0 | -15.0 | 34.0 | 4.47 | 108 |
| 8 | 42.0 | 9.0 | 34.0 | 4.46 | 324 |
| 9 | 36.0 | 15.0 | 10.0 | 4.32 | 216 |
| 10 | -60.0 | -27.0 | -2.0 | 4.32 | 108 |
| 11 | 6.0 | 18.0 | 34.0 | 4.26 | 1116 |
| 12 | -57.0 | -48.0 | 10.0 | 4.25 | 828 |
| 13 | 6.0 | 6.0 | 54.0 | 4.21 | 180 |
| 14 | -45.0 | 21.0 | 2.0 | 4.19 | 216 |
| 14a | -54.0 | 21.0 | 6.0 | 3.39 | |
| 15 | 45.0 | -21.0 | 42.0 | 4.16 | 288 |
| 16 | 63.0 | -9.0 | 2.0 | 4.16 | 180 |
| 17 | 63.0 | -24.0 | 30.0 | 4.08 | 288 |
| 18 | -3.0 | 15.0 | 46.0 | 4.08 | 432 |
| 18a | 3.0 | 9.0 | 50.0 | 3.80 | |
| 19 | -12.0 | 6.0 | 6.0 | 4.06 | 540 |
| 19a | -9.0 | -3.0 | 10.0 | 3.73 | |
| 19b | -9.0 | 6.0 | 14.0 | 3.71 | |
| 20 | -30.0 | 24.0 | 2.0 | 4.05 | 216 |
| 21 | 6.0 | -3.0 | 74.0 | 4.05 | 108 |
| 22 | -27.0 | 45.0 | 18.0 | 4.04 | 216 |
| 23 | 54.0 | -39.0 | 34.0 | 4.02 | 108 |
| 24 | -15.0 | -66.0 | 38.0 | 3.99 | 252 |
| 25 | -18.0 | -63.0 | 6.0 | 3.99 | 144 |
| 26 | 3.0 | -24.0 | 30.0 | 3.95 | 288 |
| 27 | 12.0 | -72.0 | 22.0 | 3.94 | 216 |
| 28 | 36.0 | -48.0 | -26.0 | 3.93 | 108 |
| 29 | 33.0 | 42.0 | 34.0 | 3.91 | 504 |
| 29a | 30.0 | 45.0 | 26.0 | 3.88 | |
| 30 | 9.0 | 6.0 | 6.0 | 3.88 | 108 |
| 31 | -12.0 | -24.0 | 10.0 | 3.82 | 144 |
| 32 | 0.0 | 0.0 | 38.0 | 3.82 | 108 |
| 33 | 51.0 | -30.0 | 14.0 | 3.78 | 252 |
| 34 | -54.0 | -57.0 | -2.0 | 3.77 | 108 |
| 35 | -9.0 | 15.0 | 34.0 | 3.67 | 144 |
| 36 | 51.0 | -24.0 | 10.0 | 3.65 | 108 |
| 37 | 15.0 | -30.0 | 2.0 | 3.39 | 144 |
About
- Date preprocessed:
FIAC¶
Adapted from Simple example of two-runs fMRI model fitting
Statistical Report - First Level Model Implement the General Linear Model for single run :term:`fMRI` data.
Description
Data were analyzed using Nilearn (version= 0.11.2.dev245+geee20d69f; RRID:SCR_001362).
At the subject level, a mass univariate analysis was performed with a linear regression at each voxel of the brain, using generalized least squares with a global ar1 noise model to account for temporal auto-correlation and a cosine drift model (high pass filter=0.01 Hz).
Model details
| Value | |
|---|---|
| Parameter | |
| drift_model | cosine |
| high_pass (Hertz) | 0.01 |
| hrf_model | glover |
| noise_model | ar1 |
| signal_scaling | 0 |
| slice_time_ref | 0.0 |
| standardize | False |
Design Matrix
run 0
correlation matrix
run 1
correlation matrix
Contrasts
Mask
Statistical Maps
SStSSp_minus_DStDSp
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | inf |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|
DStDSp_minus_SStSSp
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | inf |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|
DSt_minus_SSt
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | 5.612 |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|
DSp_minus_SSp
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | inf |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|
DSt_minus_SSt_for_DSp
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | inf |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|
DSp_minus_SSp_for_DSt
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | inf |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|
Deactivation
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | 4.9 |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|---|---|---|---|---|
| 1 | -39.0 | -114.0 | 60.0 | 6.01 | 36 |
| 2 | -51.0 | -57.0 | 56.0 | 5.39 | 36 |
| 3 | -51.0 | -96.0 | 64.0 | 5.38 | 36 |
| 4 | -42.0 | -93.0 | 64.0 | 5.36 | 72 |
| 5 | -126.0 | -108.0 | 60.0 | 5.35 | 36 |
| 6 | -45.0 | -93.0 | 52.0 | 5.23 | 36 |
| 7 | -135.0 | -111.0 | 60.0 | 5.21 | 36 |
| 8 | -45.0 | -60.0 | 60.0 | 5.21 | 36 |
| 9 | -57.0 | -57.0 | 60.0 | 5.00 | 36 |
Effects_of_interest
Cluster Table
| Height control | fdr |
|---|---|
| α | 0.001 |
| Threshold (computed) | 4.164 |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|---|---|---|---|---|
| 1 | -33.0 | -111.0 | 56.0 | 16.62 | 6408 |
| 1a | -45.0 | -99.0 | 64.0 | 13.71 | |
| 1b | -42.0 | -111.0 | 56.0 | 13.50 | |
| 1c | -33.0 | -96.0 | 56.0 | 12.10 | |
| 2 | -45.0 | -75.0 | 56.0 | 13.99 | 1188 |
| 2a | -42.0 | -66.0 | 52.0 | 10.15 | |
| 2b | -51.0 | -84.0 | 56.0 | 9.47 | |
| 3 | -138.0 | -111.0 | 56.0 | 13.17 | 5220 |
| 3a | -126.0 | -117.0 | 56.0 | 11.96 | |
| 3b | -141.0 | -105.0 | 48.0 | 11.50 | |
| 3c | -135.0 | -96.0 | 48.0 | 11.43 | |
| 4 | -57.0 | -90.0 | 48.0 | 9.65 | 540 |
| 4a | -57.0 | -78.0 | 40.0 | 9.43 | |
| 5 | -60.0 | -72.0 | 36.0 | 8.94 | 72 |
| 6 | -48.0 | -57.0 | 56.0 | 8.58 | 1224 |
| 6a | -45.0 | -60.0 | 68.0 | 6.97 | |
| 6b | -57.0 | -57.0 | 60.0 | 5.11 | |
| 7 | -123.0 | -84.0 | 32.0 | 8.47 | 36 |
| 8 | -126.0 | -150.0 | 56.0 | 8.13 | 324 |
| 9 | -141.0 | -126.0 | 36.0 | 8.04 | 108 |
| 10 | -135.0 | -126.0 | 76.0 | 7.95 | 468 |
| 11 | -135.0 | -84.0 | 44.0 | 7.85 | 180 |
| 12 | -87.0 | -111.0 | 88.0 | 7.73 | 360 |
| 13 | -99.0 | -141.0 | 20.0 | 7.63 | 36 |
| 14 | -96.0 | -138.0 | 104.0 | 7.43 | 108 |
| 15 | -144.0 | -108.0 | 64.0 | 7.05 | 36 |
| 16 | -60.0 | -30.0 | 48.0 | 6.70 | 144 |
| 17 | -90.0 | -150.0 | 92.0 | 6.68 | 936 |
| 18 | -114.0 | -135.0 | 20.0 | 6.64 | 36 |
| 19 | -90.0 | -129.0 | 100.0 | 6.63 | 360 |
| 20 | -117.0 | -111.0 | 56.0 | 6.57 | 72 |
| 21 | -90.0 | -114.0 | 112.0 | 6.49 | 36 |
| 22 | -126.0 | -150.0 | 80.0 | 6.45 | 288 |
| 23 | -138.0 | -117.0 | 40.0 | 6.43 | 108 |
| 24 | -120.0 | -48.0 | 68.0 | 6.43 | 72 |
| 25 | -117.0 | -114.0 | 60.0 | 6.34 | 144 |
| 26 | -117.0 | -69.0 | 80.0 | 6.34 | 36 |
| 27 | -57.0 | -75.0 | 88.0 | 6.33 | 72 |
| 28 | -138.0 | -87.0 | 48.0 | 6.31 | 36 |
| 29 | -84.0 | -135.0 | 100.0 | 6.29 | 540 |
| 30 | -57.0 | -78.0 | 16.0 | 6.29 | 72 |
| 31 | -54.0 | -72.0 | 16.0 | 6.28 | 144 |
| 32 | -93.0 | -135.0 | 108.0 | 6.26 | 72 |
| 33 | -93.0 | -147.0 | 4.0 | 6.23 | 108 |
| 34 | -108.0 | -141.0 | 0.0 | 6.19 | 252 |
| 35 | -51.0 | -63.0 | 76.0 | 6.19 | 288 |
| 35a | -60.0 | -63.0 | 72.0 | 4.47 | |
| 36 | -99.0 | -141.0 | 60.0 | 6.17 | 36 |
| 37 | -81.0 | -132.0 | 60.0 | 6.17 | 468 |
| 37a | -84.0 | -126.0 | 52.0 | 6.11 | |
| 37b | -84.0 | -123.0 | 60.0 | 4.66 | |
| 38 | -45.0 | -108.0 | 36.0 | 6.14 | 36 |
| 39 | -60.0 | -36.0 | 52.0 | 6.12 | 72 |
| 40 | -69.0 | -108.0 | 112.0 | 6.09 | 72 |
| 41 | -126.0 | -150.0 | 48.0 | 6.08 | 36 |
| 42 | -129.0 | -60.0 | 48.0 | 6.07 | 108 |
| 43 | -117.0 | -90.0 | 104.0 | 6.05 | 72 |
| 44 | -93.0 | -150.0 | 80.0 | 6.05 | 72 |
| 45 | -126.0 | -45.0 | 72.0 | 6.04 | 108 |
| 46 | -141.0 | -102.0 | 40.0 | 6.01 | 72 |
| 47 | -51.0 | -63.0 | 44.0 | 6.01 | 72 |
| 48 | -93.0 | -69.0 | 80.0 | 6.00 | 72 |
| 49 | -48.0 | -60.0 | 44.0 | 5.96 | 36 |
| 50 | -144.0 | -99.0 | 44.0 | 5.94 | 72 |
| 51 | -126.0 | -54.0 | 80.0 | 5.94 | 72 |
| 52 | -66.0 | -24.0 | 52.0 | 5.92 | 72 |
| 53 | -48.0 | -78.0 | 92.0 | 5.92 | 72 |
| 54 | -141.0 | -99.0 | 56.0 | 5.91 | 36 |
| 55 | -60.0 | -99.0 | 64.0 | 5.86 | 72 |
| 56 | -120.0 | -132.0 | 24.0 | 5.86 | 36 |
| 57 | -120.0 | -36.0 | 56.0 | 5.86 | 36 |
| 58 | -60.0 | -51.0 | 56.0 | 5.82 | 36 |
| 59 | -75.0 | -57.0 | 76.0 | 5.78 | 144 |
| 60 | -72.0 | -147.0 | 8.0 | 5.77 | 36 |
| 61 | -123.0 | -90.0 | 36.0 | 5.76 | 36 |
| 62 | -78.0 | -144.0 | 96.0 | 5.74 | 288 |
| 63 | -138.0 | -78.0 | 64.0 | 5.74 | 72 |
| 64 | -132.0 | -69.0 | 88.0 | 5.73 | 36 |
| 65 | -114.0 | -144.0 | 8.0 | 5.71 | 180 |
| 66 | -102.0 | -144.0 | 80.0 | 5.70 | 36 |
| 67 | -42.0 | -120.0 | 24.0 | 5.68 | 36 |
| 68 | -141.0 | -78.0 | 56.0 | 5.68 | 36 |
| 69 | -96.0 | -60.0 | 72.0 | 5.67 | 468 |
| 70 | -48.0 | -114.0 | 64.0 | 5.67 | 72 |
| 71 | -96.0 | -45.0 | 60.0 | 5.64 | 72 |
| 72 | -126.0 | -72.0 | 88.0 | 5.61 | 72 |
| 73 | -102.0 | -75.0 | 104.0 | 5.61 | 108 |
| 74 | -120.0 | -66.0 | 96.0 | 5.61 | 36 |
| 75 | -48.0 | -108.0 | 32.0 | 5.60 | 108 |
| 76 | -102.0 | -33.0 | 56.0 | 5.59 | 108 |
| 77 | -87.0 | -42.0 | 88.0 | 5.57 | 72 |
| 78 | -96.0 | -42.0 | 92.0 | 5.55 | 36 |
| 79 | -99.0 | -75.0 | 108.0 | 5.53 | 36 |
| 80 | -108.0 | -30.0 | 80.0 | 5.52 | 36 |
| 81 | -78.0 | -51.0 | 76.0 | 5.50 | 36 |
| 82 | -135.0 | -105.0 | 88.0 | 5.49 | 72 |
| 83 | -93.0 | -87.0 | 84.0 | 5.48 | 36 |
| 84 | -111.0 | -120.0 | 32.0 | 5.48 | 180 |
| 85 | -123.0 | -153.0 | 68.0 | 5.47 | 36 |
| 86 | -123.0 | -84.0 | 100.0 | 5.47 | 108 |
| 87 | -120.0 | -24.0 | 60.0 | 5.47 | 72 |
| 88 | -78.0 | -117.0 | 84.0 | 5.47 | 144 |
| 89 | -72.0 | -156.0 | 20.0 | 5.46 | 36 |
| 90 | -99.0 | -108.0 | 80.0 | 5.40 | 36 |
| 91 | -87.0 | -138.0 | 64.0 | 5.39 | 36 |
| 92 | -135.0 | -60.0 | 72.0 | 5.36 | 36 |
| 93 | -69.0 | -84.0 | 24.0 | 5.36 | 72 |
| 94 | -114.0 | -48.0 | 88.0 | 5.33 | 36 |
| 95 | -90.0 | -126.0 | 84.0 | 5.32 | 108 |
| 96 | -63.0 | -147.0 | 12.0 | 5.28 | 36 |
| 97 | -51.0 | -114.0 | 28.0 | 5.26 | 144 |
| 98 | -105.0 | -147.0 | 92.0 | 5.25 | 108 |
| 99 | -51.0 | -78.0 | 88.0 | 5.22 | 72 |
| 100 | -54.0 | -69.0 | 48.0 | 5.21 | 36 |
| 101 | -54.0 | -120.0 | 24.0 | 5.21 | 36 |
| 102 | -120.0 | -60.0 | 56.0 | 5.19 | 72 |
| 103 | -93.0 | -150.0 | 24.0 | 5.16 | 36 |
| 104 | -90.0 | -117.0 | 92.0 | 5.16 | 72 |
| 105 | -90.0 | -123.0 | 112.0 | 5.16 | 36 |
| 106 | -138.0 | -81.0 | 60.0 | 5.15 | 36 |
| 107 | -81.0 | -30.0 | 72.0 | 5.14 | 72 |
| 108 | -102.0 | -36.0 | 84.0 | 5.14 | 72 |
| 109 | -60.0 | -90.0 | 56.0 | 5.14 | 36 |
| 110 | -90.0 | -132.0 | 64.0 | 5.13 | 108 |
| 111 | -111.0 | -123.0 | 108.0 | 5.12 | 36 |
| 112 | -123.0 | -102.0 | 64.0 | 5.11 | 36 |
| 113 | -120.0 | -36.0 | 72.0 | 5.09 | 36 |
| 114 | -105.0 | -141.0 | 24.0 | 5.06 | 108 |
| 115 | -132.0 | -141.0 | 32.0 | 5.05 | 36 |
| 116 | -87.0 | -18.0 | 60.0 | 5.03 | 36 |
| 117 | -132.0 | -102.0 | 96.0 | 5.03 | 36 |
| 118 | -90.0 | -96.0 | 112.0 | 5.03 | 36 |
| 119 | -93.0 | -42.0 | 56.0 | 5.02 | 36 |
| 120 | -99.0 | -33.0 | 84.0 | 5.01 | 36 |
| 121 | -96.0 | -147.0 | 16.0 | 5.01 | 36 |
| 122 | -114.0 | -150.0 | 88.0 | 5.00 | 72 |
| 123 | -75.0 | -108.0 | 112.0 | 4.98 | 108 |
| 124 | -51.0 | -75.0 | 44.0 | 4.98 | 72 |
| 125 | -126.0 | -138.0 | 92.0 | 4.97 | 72 |
| 126 | -45.0 | -81.0 | 64.0 | 4.97 | 36 |
| 127 | -135.0 | -54.0 | 36.0 | 4.94 | 36 |
| 128 | -93.0 | -78.0 | 84.0 | 4.94 | 108 |
| 129 | -81.0 | -84.0 | 24.0 | 4.94 | 36 |
| 130 | -117.0 | -114.0 | 104.0 | 4.92 | 72 |
| 131 | -57.0 | -75.0 | 96.0 | 4.92 | 36 |
| 132 | -123.0 | -87.0 | 40.0 | 4.91 | 36 |
| 133 | -78.0 | -48.0 | 80.0 | 4.91 | 72 |
| 134 | -45.0 | -117.0 | 24.0 | 4.90 | 36 |
| 135 | -54.0 | -93.0 | 56.0 | 4.89 | 72 |
| 136 | -48.0 | -135.0 | 12.0 | 4.88 | 36 |
| 137 | -60.0 | -57.0 | 52.0 | 4.87 | 36 |
| 138 | -51.0 | -42.0 | 64.0 | 4.86 | 36 |
| 139 | -48.0 | -102.0 | 96.0 | 4.85 | 36 |
| 140 | -51.0 | -138.0 | 80.0 | 4.85 | 72 |
| 141 | -129.0 | -63.0 | 84.0 | 4.84 | 36 |
| 142 | -51.0 | -141.0 | 88.0 | 4.84 | 36 |
| 143 | -99.0 | -51.0 | 96.0 | 4.83 | 36 |
| 144 | -102.0 | -144.0 | 12.0 | 4.82 | 108 |
| 145 | -90.0 | -141.0 | 96.0 | 4.82 | 36 |
| 146 | -138.0 | -132.0 | 88.0 | 4.81 | 36 |
| 147 | -90.0 | -69.0 | 96.0 | 4.80 | 72 |
| 148 | -135.0 | -126.0 | 64.0 | 4.80 | 36 |
| 149 | -87.0 | -33.0 | 52.0 | 4.79 | 36 |
| 150 | -51.0 | -66.0 | 36.0 | 4.78 | 72 |
| 151 | -51.0 | -78.0 | 16.0 | 4.77 | 36 |
| 152 | -93.0 | -72.0 | 96.0 | 4.75 | 36 |
| 153 | -96.0 | -72.0 | 84.0 | 4.75 | 72 |
| 154 | -129.0 | -57.0 | 64.0 | 4.74 | 36 |
| 155 | -72.0 | -132.0 | 64.0 | 4.71 | 36 |
| 156 | -63.0 | -78.0 | 40.0 | 4.71 | 36 |
| 157 | -60.0 | -90.0 | 64.0 | 4.71 | 36 |
| 158 | -63.0 | -57.0 | 48.0 | 4.69 | 36 |
| 159 | -60.0 | -75.0 | 40.0 | 4.68 | 36 |
| 160 | -105.0 | -93.0 | 112.0 | 4.68 | 36 |
| 161 | -114.0 | -123.0 | 104.0 | 4.67 | 36 |
| 162 | -87.0 | -42.0 | 64.0 | 4.67 | 36 |
| 163 | -51.0 | -75.0 | 52.0 | 4.65 | 36 |
| 164 | -93.0 | -60.0 | 100.0 | 4.60 | 36 |
| 165 | -75.0 | -39.0 | 80.0 | 4.60 | 36 |
| 166 | -63.0 | -54.0 | 92.0 | 4.60 | 36 |
| 167 | -84.0 | -126.0 | 64.0 | 4.59 | 36 |
| 168 | -48.0 | -99.0 | 80.0 | 4.59 | 36 |
| 169 | -90.0 | -141.0 | 104.0 | 4.58 | 36 |
| 170 | -72.0 | -33.0 | 48.0 | 4.58 | 36 |
| 171 | -99.0 | -45.0 | 92.0 | 4.57 | 36 |
| 172 | -114.0 | -147.0 | 92.0 | 4.57 | 36 |
| 173 | -102.0 | -120.0 | 28.0 | 4.56 | 36 |
| 174 | -138.0 | -135.0 | 48.0 | 4.55 | 72 |
| 175 | -114.0 | -111.0 | 108.0 | 4.55 | 72 |
| 176 | -129.0 | -105.0 | 88.0 | 4.55 | 36 |
| 177 | -60.0 | -72.0 | 96.0 | 4.54 | 36 |
| 178 | -93.0 | -150.0 | 72.0 | 4.54 | 36 |
| 179 | -57.0 | -33.0 | 48.0 | 4.54 | 36 |
| 180 | -81.0 | -120.0 | 52.0 | 4.53 | 36 |
| 181 | -96.0 | -138.0 | 96.0 | 4.53 | 36 |
| 182 | -84.0 | -147.0 | 100.0 | 4.52 | 36 |
| 183 | -117.0 | -147.0 | 88.0 | 4.52 | 36 |
| 184 | -123.0 | -144.0 | 72.0 | 4.52 | 36 |
| 185 | -48.0 | -78.0 | 24.0 | 4.50 | 36 |
| 186 | -111.0 | -93.0 | 108.0 | 4.49 | 36 |
| 187 | -51.0 | -135.0 | 16.0 | 4.49 | 36 |
| 188 | -135.0 | -48.0 | 44.0 | 4.49 | 36 |
| 189 | -126.0 | -63.0 | 52.0 | 4.48 | 36 |
| 190 | -54.0 | -63.0 | 48.0 | 4.46 | 36 |
| 191 | -87.0 | -36.0 | 48.0 | 4.45 | 36 |
| 192 | -111.0 | -108.0 | 112.0 | 4.45 | 36 |
| 193 | -63.0 | -114.0 | 28.0 | 4.44 | 36 |
| 194 | -84.0 | -153.0 | 80.0 | 4.44 | 36 |
| 195 | -33.0 | -108.0 | 72.0 | 4.43 | 72 |
| 196 | -93.0 | -108.0 | 72.0 | 4.43 | 36 |
| 197 | -141.0 | -90.0 | 56.0 | 4.42 | 36 |
| 198 | -84.0 | -150.0 | 16.0 | 4.41 | 36 |
| 199 | -75.0 | -147.0 | 4.0 | 4.40 | 36 |
| 200 | -48.0 | -57.0 | 76.0 | 4.40 | 36 |
| 201 | -132.0 | -129.0 | 92.0 | 4.39 | 36 |
| 202 | -78.0 | -60.0 | 80.0 | 4.38 | 36 |
| 203 | -72.0 | -78.0 | 96.0 | 4.38 | 36 |
| 204 | -54.0 | -39.0 | 48.0 | 4.37 | 36 |
| 205 | -96.0 | -144.0 | 12.0 | 4.37 | 72 |
| 206 | -123.0 | -33.0 | 56.0 | 4.37 | 72 |
| 207 | -69.0 | -132.0 | 68.0 | 4.36 | 36 |
| 208 | -111.0 | -114.0 | 112.0 | 4.35 | 36 |
| 209 | -81.0 | -126.0 | 104.0 | 4.35 | 36 |
| 210 | -117.0 | -54.0 | 72.0 | 4.35 | 36 |
| 211 | -75.0 | -150.0 | 20.0 | 4.35 | 36 |
| 212 | -72.0 | -141.0 | 96.0 | 4.33 | 36 |
| 213 | -96.0 | -63.0 | 80.0 | 4.33 | 36 |
| 214 | -60.0 | -87.0 | 100.0 | 4.32 | 36 |
| 215 | -90.0 | -147.0 | 56.0 | 4.32 | 36 |
| 216 | -60.0 | -78.0 | 100.0 | 4.32 | 36 |
| 217 | -63.0 | -72.0 | 40.0 | 4.32 | 36 |
| 218 | -81.0 | -144.0 | 100.0 | 4.31 | 36 |
| 219 | -126.0 | -69.0 | 92.0 | 4.30 | 36 |
| 220 | -141.0 | -120.0 | 68.0 | 4.30 | 36 |
| 221 | -117.0 | -30.0 | 68.0 | 4.29 | 36 |
| 222 | -120.0 | -147.0 | 72.0 | 4.28 | 36 |
| 223 | -48.0 | -120.0 | 24.0 | 4.28 | 36 |
| 224 | -78.0 | -111.0 | 80.0 | 4.27 | 36 |
| 225 | -135.0 | -132.0 | 40.0 | 4.27 | 36 |
| 226 | -90.0 | -123.0 | 68.0 | 4.26 | 36 |
| 227 | -102.0 | -78.0 | 108.0 | 4.26 | 36 |
| 228 | -45.0 | -66.0 | 64.0 | 4.25 | 36 |
| 229 | -135.0 | -129.0 | 36.0 | 4.24 | 36 |
| 230 | -66.0 | -105.0 | 24.0 | 4.23 | 36 |
| 231 | -129.0 | -48.0 | 72.0 | 4.23 | 36 |
| 232 | -126.0 | -48.0 | 76.0 | 4.22 | 36 |
| 233 | -99.0 | -147.0 | 12.0 | 4.22 | 36 |
| 234 | -60.0 | -60.0 | 60.0 | 4.22 | 36 |
| 235 | -99.0 | -144.0 | 76.0 | 4.22 | 36 |
| 236 | -126.0 | -81.0 | 96.0 | 4.21 | 36 |
| 237 | -138.0 | -129.0 | 84.0 | 4.21 | 36 |
| 238 | -39.0 | -75.0 | 72.0 | 4.21 | 36 |
| 239 | -102.0 | -111.0 | 80.0 | 4.20 | 36 |
| 240 | -72.0 | -78.0 | 104.0 | 4.20 | 36 |
| 241 | -99.0 | -48.0 | 60.0 | 4.19 | 36 |
| 242 | -135.0 | -78.0 | 44.0 | 4.19 | 36 |
| 243 | -129.0 | -81.0 | 48.0 | 4.18 | 36 |
| 244 | -102.0 | -135.0 | 28.0 | 4.18 | 36 |
| 245 | -123.0 | -108.0 | 84.0 | 4.18 | 36 |
| 246 | -114.0 | -150.0 | 28.0 | 4.18 | 36 |
| 247 | -57.0 | -132.0 | 68.0 | 4.17 | 36 |
| 248 | -66.0 | -126.0 | 108.0 | 4.16 | 36 |
About
- Date preprocessed:
Surface GLM¶
Statistical Report - First Level Model Implement the General Linear Model for single run :term:`fMRI` data.
WARNING
- The model has not been fit yet.
Description
Data were analyzed using Nilearn (version= 0.11.2.dev245+geee20d69f; RRID:SCR_001362).
At the subject level, a mass univariate analysis was performed with a linear regression at each voxel of the brain, using generalized least squares with a global ar1 noise model to account for temporal auto-correlation .
Model details
| Value | |
|---|---|
| Parameter | |
| drift_model | cosine |
| high_pass (Hertz) | 0.01 |
| hrf_model | glover |
| noise_model | ar1 |
| signal_scaling | 0 |
| slice_time_ref | 0.0 |
| standardize | False |
Design Matrix
No design matrix was provided.
Contrasts
No contrast was provided.
Mask
No mask was provided.
Statistical Maps
No statistical map was provided.
About
- Date preprocessed:
Second level report¶
Volume GLM¶
Adapted from Voxel-Based Morphometry on OASIS dataset
Statistical Report - Second Level Model Implement the :term:`General Linear Model<GLM>` for multiple subject :term:`fMRI` data.
Description
Data were analyzed using Nilearn (version= 0.11.2.dev245+geee20d69f; RRID:SCR_001362).
At the group level, a mass univariate analysis was performed with a linear regression at each voxel of the brain.
Input images were smoothed with gaussian kernel (full-width at half maximum=2.0 mm).
The following contrasts were computed :
- age
- sex
Model details
| Value | |
|---|---|
| Parameter | |
| smoothing_fwhm (mm) | 2.0 |
Design Matrix
run 0
correlation matrix
Contrasts
Mask
Statistical Maps
age
Cluster Table
| Height control | None |
|---|---|
| Threshold Z | 3.09 |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|---|---|---|---|---|
| 1 | -10.0 | -66.0 | -4.0 | 4.53 | 8 |
| 2 | -2.0 | -2.0 | -8.0 | 4.46 | 8 |
| 3 | -14.0 | -54.0 | 48.0 | 4.25 | 8 |
| 4 | -20.0 | -6.0 | -34.0 | 4.25 | 8 |
| 5 | 6.0 | 48.0 | 34.0 | 4.14 | 8 |
| 6 | 50.0 | 16.0 | -4.0 | 4.09 | 8 |
| 7 | -8.0 | -18.0 | -2.0 | 3.89 | 8 |
| 8 | 18.0 | 26.0 | -20.0 | 3.88 | 8 |
| 9 | -2.0 | 26.0 | 32.0 | 3.87 | 8 |
| 10 | -44.0 | 28.0 | 0.0 | 3.86 | 8 |
| 11 | 60.0 | -4.0 | -8.0 | 3.79 | 8 |
| 12 | 0.0 | 32.0 | -2.0 | 3.78 | 8 |
| 13 | 32.0 | 46.0 | -18.0 | 3.78 | 8 |
| 14 | -42.0 | -64.0 | -8.0 | 3.76 | 8 |
| 15 | -26.0 | -34.0 | 14.0 | 3.75 | 8 |
| 16 | -6.0 | 40.0 | -8.0 | 3.71 | 8 |
| 17 | -8.0 | -58.0 | 22.0 | 3.69 | 8 |
| 18 | -42.0 | 12.0 | 26.0 | 3.69 | 8 |
| 19 | 26.0 | -32.0 | -10.0 | 3.68 | 8 |
| 20 | 46.0 | -26.0 | -8.0 | 3.68 | 8 |
| 21 | -30.0 | 18.0 | -42.0 | 3.67 | 8 |
| 22 | 20.0 | 66.0 | 4.0 | 3.66 | 8 |
| 23 | -48.0 | 8.0 | 40.0 | 3.65 | 8 |
| 24 | -44.0 | 16.0 | 40.0 | 3.65 | 8 |
| 25 | -62.0 | -8.0 | 28.0 | 3.65 | 8 |
| 26 | -60.0 | -56.0 | 20.0 | 3.64 | 8 |
| 27 | -16.0 | -48.0 | 70.0 | 3.62 | 8 |
| 28 | -16.0 | 70.0 | 12.0 | 3.62 | 8 |
| 29 | 38.0 | -74.0 | -44.0 | 3.62 | 8 |
| 30 | -2.0 | 24.0 | -12.0 | 3.60 | 8 |
| 31 | -4.0 | -6.0 | 24.0 | 3.60 | 8 |
| 32 | -8.0 | 52.0 | 34.0 | 3.58 | 8 |
| 33 | 64.0 | -50.0 | 32.0 | 3.57 | 8 |
| 34 | -2.0 | 10.0 | 28.0 | 3.57 | 8 |
| 35 | 64.0 | -26.0 | 24.0 | 3.57 | 8 |
| 36 | -4.0 | -28.0 | -2.0 | 3.57 | 8 |
| 37 | 56.0 | -8.0 | 40.0 | 3.56 | 8 |
| 38 | 16.0 | 0.0 | 16.0 | 3.56 | 8 |
| 39 | 0.0 | -16.0 | -36.0 | 3.55 | 8 |
| 40 | -36.0 | 34.0 | 50.0 | 3.55 | 8 |
| 41 | 6.0 | -58.0 | 0.0 | 3.54 | 8 |
| 42 | 22.0 | 34.0 | -24.0 | 3.54 | 8 |
| 43 | -16.0 | 32.0 | -24.0 | 3.54 | 8 |
| 44 | 54.0 | -44.0 | 52.0 | 3.53 | 8 |
| 45 | 12.0 | -8.0 | 14.0 | 3.53 | 8 |
| 46 | -58.0 | -14.0 | 46.0 | 3.52 | 8 |
| 47 | -10.0 | 6.0 | 12.0 | 3.51 | 16 |
| 48 | 46.0 | -48.0 | -20.0 | 3.50 | 8 |
| 49 | -20.0 | 38.0 | -16.0 | 3.49 | 8 |
| 50 | 12.0 | 14.0 | 2.0 | 3.48 | 8 |
| 51 | 0.0 | 0.0 | 36.0 | 3.48 | 8 |
| 52 | 2.0 | -48.0 | 66.0 | 3.47 | 8 |
| 53 | 2.0 | -40.0 | 60.0 | 3.47 | 8 |
| 54 | 26.0 | 64.0 | 16.0 | 3.47 | 8 |
| 55 | -8.0 | -14.0 | 26.0 | 3.46 | 8 |
| 56 | -46.0 | -66.0 | -18.0 | 3.46 | 8 |
| 57 | -52.0 | -34.0 | 44.0 | 3.45 | 8 |
| 58 | 56.0 | -14.0 | -32.0 | 3.45 | 8 |
| 59 | 2.0 | 4.0 | 52.0 | 3.44 | 8 |
| 60 | 12.0 | -22.0 | 4.0 | 3.44 | 8 |
| 61 | 66.0 | -6.0 | 18.0 | 3.44 | 8 |
| 62 | 62.0 | -10.0 | 8.0 | 3.44 | 8 |
| 63 | 4.0 | 22.0 | 22.0 | 3.44 | 8 |
| 64 | 64.0 | 2.0 | -16.0 | 3.43 | 8 |
| 65 | 6.0 | -46.0 | 38.0 | 3.42 | 8 |
| 66 | 4.0 | -56.0 | 22.0 | 3.42 | 8 |
| 67 | -10.0 | -18.0 | 40.0 | 3.41 | 8 |
| 68 | 6.0 | -58.0 | 28.0 | 3.41 | 8 |
| 69 | 8.0 | -2.0 | 56.0 | 3.41 | 8 |
| 70 | 2.0 | 0.0 | -2.0 | 3.41 | 8 |
| 71 | 56.0 | -4.0 | -32.0 | 3.41 | 8 |
| 72 | -18.0 | 24.0 | 52.0 | 3.41 | 8 |
| 73 | 0.0 | 26.0 | 56.0 | 3.40 | 8 |
| 74 | 6.0 | -76.0 | -2.0 | 3.39 | 8 |
| 75 | -12.0 | 42.0 | -20.0 | 3.38 | 8 |
| 76 | -4.0 | -54.0 | -8.0 | 3.38 | 8 |
| 77 | -26.0 | -30.0 | 60.0 | 3.37 | 8 |
| 78 | 32.0 | -22.0 | -28.0 | 3.37 | 8 |
| 79 | -6.0 | 2.0 | -16.0 | 3.36 | 8 |
| 80 | -18.0 | 28.0 | -2.0 | 3.36 | 8 |
| 81 | 24.0 | 34.0 | 40.0 | 3.36 | 8 |
| 82 | 30.0 | -32.0 | -14.0 | 3.35 | 8 |
| 83 | 2.0 | 32.0 | -18.0 | 3.35 | 8 |
| 84 | -26.0 | 32.0 | -16.0 | 3.35 | 8 |
| 85 | -18.0 | -28.0 | -26.0 | 3.34 | 8 |
| 86 | -6.0 | -10.0 | 12.0 | 3.34 | 8 |
| 87 | 10.0 | -76.0 | -48.0 | 3.34 | 8 |
| 88 | 34.0 | -56.0 | -50.0 | 3.33 | 8 |
| 89 | 2.0 | -34.0 | 58.0 | 3.33 | 8 |
| 90 | 52.0 | -18.0 | -8.0 | 3.33 | 8 |
| 91 | -2.0 | 46.0 | 38.0 | 3.32 | 8 |
| 92 | -2.0 | -4.0 | 14.0 | 3.32 | 8 |
| 93 | 60.0 | -50.0 | 2.0 | 3.32 | 8 |
| 94 | 42.0 | 16.0 | -46.0 | 3.32 | 8 |
| 95 | 30.0 | -30.0 | -4.0 | 3.31 | 8 |
| 96 | 28.0 | 40.0 | 42.0 | 3.31 | 8 |
| 97 | -40.0 | 30.0 | 42.0 | 3.31 | 8 |
| 98 | 2.0 | -32.0 | -22.0 | 3.30 | 8 |
| 99 | 24.0 | 44.0 | 28.0 | 3.30 | 8 |
| 100 | -4.0 | -30.0 | -8.0 | 3.30 | 8 |
| 101 | -20.0 | 58.0 | 18.0 | 3.30 | 8 |
| 102 | 6.0 | -92.0 | 32.0 | 3.29 | 8 |
| 103 | -28.0 | -38.0 | 16.0 | 3.29 | 8 |
| 104 | 12.0 | 48.0 | 10.0 | 3.29 | 8 |
| 105 | -6.0 | 38.0 | 4.0 | 3.29 | 8 |
| 106 | 4.0 | -20.0 | 22.0 | 3.29 | 8 |
| 107 | -6.0 | -80.0 | 36.0 | 3.28 | 8 |
| 108 | -12.0 | -44.0 | 68.0 | 3.28 | 8 |
| 109 | 62.0 | 6.0 | -22.0 | 3.28 | 8 |
| 110 | 64.0 | 2.0 | 26.0 | 3.28 | 8 |
| 111 | 8.0 | 54.0 | -22.0 | 3.27 | 8 |
| 112 | -34.0 | 12.0 | -46.0 | 3.27 | 8 |
| 113 | -4.0 | -12.0 | 26.0 | 3.27 | 8 |
| 114 | 28.0 | -38.0 | -26.0 | 3.27 | 8 |
| 115 | -2.0 | -18.0 | 54.0 | 3.27 | 8 |
| 116 | 10.0 | -16.0 | 16.0 | 3.27 | 8 |
| 117 | -64.0 | -20.0 | 20.0 | 3.27 | 8 |
| 118 | 2.0 | 34.0 | 20.0 | 3.26 | 8 |
| 119 | -2.0 | 20.0 | 26.0 | 3.26 | 8 |
| 120 | -10.0 | -86.0 | 28.0 | 3.25 | 8 |
| 121 | 20.0 | -24.0 | -4.0 | 3.25 | 8 |
| 122 | 0.0 | 42.0 | 12.0 | 3.25 | 8 |
| 123 | 42.0 | -10.0 | 20.0 | 3.24 | 8 |
| 124 | 24.0 | 0.0 | 56.0 | 3.24 | 8 |
| 125 | 18.0 | -26.0 | 12.0 | 3.23 | 8 |
| 126 | 8.0 | 12.0 | 62.0 | 3.23 | 8 |
| 127 | 4.0 | -16.0 | -18.0 | 3.22 | 8 |
| 128 | -16.0 | 10.0 | 10.0 | 3.22 | 8 |
| 129 | -24.0 | -42.0 | 70.0 | 3.22 | 8 |
| 130 | 52.0 | -36.0 | -4.0 | 3.21 | 8 |
| 131 | -18.0 | 66.0 | 8.0 | 3.21 | 8 |
| 132 | 22.0 | -38.0 | -2.0 | 3.21 | 8 |
| 133 | 12.0 | 70.0 | 6.0 | 3.21 | 8 |
| 134 | 24.0 | 4.0 | 66.0 | 3.21 | 8 |
| 135 | -66.0 | -20.0 | 32.0 | 3.20 | 8 |
| 136 | 44.0 | -2.0 | 56.0 | 3.20 | 8 |
| 137 | -58.0 | 4.0 | -18.0 | 3.20 | 8 |
| 138 | -4.0 | -48.0 | -8.0 | 3.20 | 8 |
| 139 | 54.0 | -18.0 | 28.0 | 3.20 | 8 |
| 140 | -10.0 | 4.0 | 66.0 | 3.19 | 8 |
| 141 | 8.0 | 14.0 | -12.0 | 3.19 | 8 |
| 142 | 6.0 | -58.0 | -16.0 | 3.19 | 8 |
| 143 | 10.0 | 10.0 | 12.0 | 3.19 | 8 |
| 144 | -50.0 | -8.0 | -12.0 | 3.19 | 8 |
| 145 | 54.0 | -16.0 | 34.0 | 3.19 | 8 |
| 146 | -40.0 | -66.0 | 50.0 | 3.19 | 8 |
| 147 | -2.0 | -46.0 | 66.0 | 3.18 | 8 |
| 148 | -42.0 | 16.0 | -12.0 | 3.18 | 8 |
| 149 | -14.0 | -38.0 | 14.0 | 3.18 | 8 |
| 150 | 66.0 | -10.0 | 18.0 | 3.18 | 8 |
| 151 | -24.0 | -44.0 | -2.0 | 3.18 | 8 |
| 152 | 42.0 | 24.0 | -6.0 | 3.18 | 8 |
| 153 | -60.0 | -14.0 | 36.0 | 3.18 | 8 |
| 154 | 56.0 | -4.0 | -8.0 | 3.18 | 8 |
| 155 | -20.0 | -26.0 | 14.0 | 3.17 | 8 |
| 156 | 30.0 | -40.0 | 8.0 | 3.17 | 8 |
| 157 | 6.0 | 8.0 | 30.0 | 3.17 | 8 |
| 158 | 4.0 | -40.0 | 78.0 | 3.17 | 8 |
| 159 | 16.0 | 34.0 | 56.0 | 3.17 | 8 |
| 160 | 68.0 | -4.0 | 14.0 | 3.17 | 8 |
| 161 | 24.0 | -74.0 | 44.0 | 3.17 | 8 |
| 162 | 32.0 | -38.0 | -28.0 | 3.17 | 8 |
| 163 | -36.0 | -62.0 | 38.0 | 3.16 | 8 |
| 164 | 34.0 | 34.0 | 46.0 | 3.16 | 8 |
| 165 | -16.0 | -40.0 | 8.0 | 3.16 | 8 |
| 166 | 10.0 | -86.0 | 34.0 | 3.16 | 8 |
| 167 | 10.0 | -32.0 | 18.0 | 3.15 | 8 |
| 168 | -6.0 | -46.0 | 28.0 | 3.15 | 8 |
| 169 | -42.0 | -30.0 | 46.0 | 3.15 | 8 |
| 170 | -36.0 | 6.0 | 44.0 | 3.15 | 8 |
| 171 | 58.0 | -52.0 | 4.0 | 3.15 | 8 |
| 172 | 10.0 | 0.0 | 14.0 | 3.15 | 8 |
| 173 | -38.0 | -14.0 | -42.0 | 3.15 | 8 |
| 174 | 2.0 | -54.0 | 32.0 | 3.15 | 8 |
| 175 | 16.0 | 58.0 | 32.0 | 3.15 | 8 |
| 176 | -8.0 | -10.0 | 26.0 | 3.14 | 8 |
| 177 | 56.0 | -18.0 | 34.0 | 3.14 | 8 |
| 178 | 40.0 | 22.0 | -6.0 | 3.14 | 8 |
| 179 | 40.0 | -28.0 | 40.0 | 3.14 | 8 |
| 180 | 54.0 | -14.0 | -14.0 | 3.14 | 8 |
| 181 | 44.0 | 14.0 | 44.0 | 3.14 | 8 |
| 182 | -28.0 | -76.0 | -58.0 | 3.13 | 8 |
| 183 | 14.0 | -28.0 | 14.0 | 3.13 | 8 |
| 184 | 36.0 | 24.0 | 4.0 | 3.13 | 8 |
| 185 | -2.0 | 12.0 | 30.0 | 3.13 | 8 |
| 186 | 48.0 | -42.0 | 24.0 | 3.13 | 8 |
| 187 | -46.0 | -24.0 | 10.0 | 3.13 | 8 |
| 188 | -42.0 | 4.0 | -6.0 | 3.13 | 8 |
| 189 | -32.0 | -34.0 | 46.0 | 3.13 | 8 |
| 190 | -14.0 | -10.0 | 10.0 | 3.13 | 8 |
| 191 | -26.0 | -10.0 | -46.0 | 3.12 | 8 |
| 192 | -42.0 | 10.0 | -8.0 | 3.12 | 8 |
| 193 | 44.0 | -40.0 | 50.0 | 3.11 | 8 |
| 194 | -60.0 | -40.0 | -26.0 | 3.11 | 8 |
| 195 | 2.0 | 10.0 | 56.0 | 3.11 | 8 |
| 196 | 32.0 | 34.0 | -14.0 | 3.11 | 8 |
| 197 | -42.0 | -66.0 | 54.0 | 3.11 | 8 |
| 198 | -22.0 | -46.0 | 70.0 | 3.11 | 8 |
| 199 | -28.0 | -34.0 | -10.0 | 3.10 | 8 |
| 200 | 6.0 | 26.0 | 54.0 | 3.10 | 8 |
| 201 | 14.0 | -48.0 | -6.0 | 3.10 | 8 |
| 202 | -28.0 | 30.0 | -22.0 | 3.10 | 8 |
| 203 | 2.0 | -34.0 | 2.0 | 3.10 | 8 |
| 204 | -10.0 | -54.0 | 68.0 | 3.10 | 8 |
| 205 | -58.0 | -2.0 | 8.0 | 3.10 | 8 |
| 206 | 16.0 | -6.0 | -34.0 | 3.10 | 8 |
| 207 | 14.0 | -28.0 | -22.0 | 3.09 | 8 |
| 208 | 10.0 | 34.0 | 42.0 | 3.09 | 8 |
| 209 | 34.0 | -94.0 | 6.0 | 3.09 | 8 |
| 210 | 18.0 | -6.0 | 22.0 | 3.09 | 8 |
| 211 | 14.0 | -76.0 | -36.0 | 3.09 | 8 |
sex
Cluster Table
| Height control | None |
|---|---|
| Threshold Z | 3.09 |
| Cluster size threshold (voxels) | 0 |
| Minimum distance (mm) | 8.0 |
| Cluster ID | X | Y | Z | Peak Stat | Cluster Size (mm3) |
|---|---|---|---|---|---|
| 1 | -34.0 | -10.0 | -18.0 | 4.73 | 8 |
| 2 | -4.0 | -22.0 | 18.0 | 4.62 | 8 |
| 3 | 52.0 | 32.0 | 0.0 | 4.27 | 8 |
| 4 | -40.0 | -76.0 | -24.0 | 4.20 | 8 |
| 5 | 38.0 | -74.0 | -44.0 | 4.14 | 16 |
| 6 | 24.0 | -74.0 | -48.0 | 4.10 | 8 |
| 7 | 2.0 | -44.0 | -56.0 | 3.98 | 8 |
| 8 | -24.0 | -90.0 | 8.0 | 3.89 | 8 |
| 9 | -30.0 | -72.0 | -24.0 | 3.87 | 8 |
| 10 | -24.0 | -78.0 | -38.0 | 3.86 | 8 |
| 11 | -4.0 | 46.0 | -26.0 | 3.80 | 8 |
| 12 | -12.0 | 8.0 | 20.0 | 3.78 | 8 |
| 13 | 32.0 | 6.0 | 32.0 | 3.75 | 8 |
| 14 | -20.0 | -78.0 | -44.0 | 3.73 | 8 |
| 15 | -58.0 | -8.0 | 48.0 | 3.72 | 8 |
| 16 | 10.0 | -34.0 | -28.0 | 3.72 | 8 |
| 17 | 44.0 | -66.0 | -40.0 | 3.72 | 8 |
| 18 | -36.0 | -76.0 | -28.0 | 3.71 | 8 |
| 19 | -2.0 | -44.0 | -54.0 | 3.68 | 8 |
| 20 | 8.0 | -82.0 | -36.0 | 3.67 | 8 |
| 21 | -12.0 | -34.0 | -28.0 | 3.67 | 8 |
| 22 | -14.0 | -74.0 | -46.0 | 3.66 | 8 |
| 23 | 64.0 | -32.0 | -24.0 | 3.66 | 8 |
| 24 | 20.0 | -70.0 | -52.0 | 3.65 | 8 |
| 25 | -38.0 | 2.0 | 30.0 | 3.65 | 8 |
| 26 | -16.0 | -74.0 | -48.0 | 3.64 | 8 |
| 27 | -40.0 | 32.0 | -8.0 | 3.62 | 8 |
| 28 | -2.0 | -32.0 | -20.0 | 3.62 | 8 |
| 29 | 2.0 | 52.0 | 18.0 | 3.60 | 8 |
| 30 | -46.0 | -64.0 | -34.0 | 3.59 | 8 |
| 31 | -24.0 | -72.0 | -36.0 | 3.59 | 16 |
| 32 | -18.0 | -80.0 | -42.0 | 3.59 | 8 |
| 33 | -16.0 | -28.0 | 36.0 | 3.59 | 8 |
| 34 | -24.0 | -94.0 | 10.0 | 3.59 | 8 |
| 35 | 16.0 | 64.0 | -14.0 | 3.59 | 8 |
| 36 | 24.0 | -68.0 | -40.0 | 3.58 | 16 |
| 37 | -58.0 | -2.0 | 48.0 | 3.58 | 8 |
| 38 | 10.0 | -76.0 | -48.0 | 3.58 | 8 |
| 39 | -6.0 | -52.0 | -56.0 | 3.57 | 8 |
| 40 | 40.0 | -70.0 | -32.0 | 3.56 | 8 |
| 41 | 30.0 | -80.0 | -36.0 | 3.56 | 8 |
| 42 | 40.0 | -66.0 | -38.0 | 3.53 | 8 |
| 43 | -36.0 | -8.0 | -26.0 | 3.51 | 8 |
| 44 | -48.0 | -52.0 | 56.0 | 3.50 | 8 |
| 45 | -34.0 | -38.0 | -14.0 | 3.50 | 8 |
| 46 | 0.0 | -2.0 | 18.0 | 3.50 | 8 |
| 47 | 42.0 | -60.0 | -42.0 | 3.50 | 8 |
| 48 | 34.0 | -62.0 | -40.0 | 3.48 | 8 |
| 49 | -6.0 | -18.0 | 62.0 | 3.48 | 8 |
| 50 | 22.0 | -64.0 | -28.0 | 3.48 | 8 |
| 51 | -4.0 | -8.0 | 20.0 | 3.47 | 8 |
| 52 | -16.0 | -74.0 | -42.0 | 3.46 | 8 |
| 53 | -8.0 | 0.0 | 40.0 | 3.46 | 8 |
| 54 | -38.0 | -74.0 | -28.0 | 3.46 | 8 |
| 55 | -40.0 | 34.0 | 28.0 | 3.46 | 8 |
| 56 | 28.0 | -70.0 | -36.0 | 3.45 | 8 |
| 57 | 42.0 | -46.0 | -22.0 | 3.45 | 8 |
| 58 | -10.0 | -8.0 | 38.0 | 3.44 | 8 |
| 59 | -16.0 | -74.0 | -32.0 | 3.44 | 8 |
| 60 | 54.0 | 36.0 | -10.0 | 3.43 | 8 |
| 61 | -32.0 | -66.0 | -38.0 | 3.43 | 8 |
| 62 | 26.0 | 2.0 | 12.0 | 3.43 | 8 |
| 63 | -16.0 | -34.0 | -46.0 | 3.42 | 8 |
| 64 | -10.0 | -76.0 | -38.0 | 3.42 | 16 |
| 65 | 36.0 | -54.0 | 40.0 | 3.42 | 8 |
| 66 | 38.0 | -52.0 | -46.0 | 3.42 | 8 |
| 67 | -16.0 | -78.0 | 44.0 | 3.41 | 8 |
| 68 | -34.0 | -76.0 | 36.0 | 3.41 | 8 |
| 69 | -8.0 | 34.0 | 46.0 | 3.41 | 8 |
| 70 | -10.0 | 20.0 | 8.0 | 3.41 | 8 |
| 71 | -36.0 | -66.0 | -56.0 | 3.40 | 8 |
| 72 | -26.0 | -2.0 | -12.0 | 3.40 | 8 |
| 73 | 32.0 | -92.0 | -8.0 | 3.39 | 8 |
| 74 | -22.0 | -72.0 | -44.0 | 3.39 | 8 |
| 75 | -58.0 | 0.0 | 38.0 | 3.39 | 8 |
| 76 | 34.0 | -34.0 | -38.0 | 3.37 | 8 |
| 77 | -34.0 | -54.0 | -48.0 | 3.37 | 8 |
| 78 | 38.0 | -18.0 | 46.0 | 3.36 | 8 |
| 79 | 20.0 | -74.0 | -44.0 | 3.36 | 8 |
| 80 | 34.0 | -72.0 | -36.0 | 3.36 | 8 |
| 81 | 20.0 | 50.0 | 46.0 | 3.36 | 8 |
| 82 | -30.0 | -58.0 | -28.0 | 3.35 | 8 |
| 83 | 60.0 | -36.0 | -2.0 | 3.34 | 8 |
| 84 | 10.0 | -70.0 | -46.0 | 3.34 | 16 |
| 85 | 38.0 | 38.0 | 6.0 | 3.33 | 8 |
| 86 | 34.0 | -60.0 | -30.0 | 3.33 | 8 |
| 87 | 24.0 | -52.0 | 10.0 | 3.33 | 8 |
| 88 | 18.0 | -80.0 | -26.0 | 3.32 | 8 |
| 89 | -14.0 | 2.0 | 24.0 | 3.32 | 8 |
| 90 | -40.0 | -20.0 | 48.0 | 3.31 | 8 |
| 91 | 12.0 | -78.0 | -48.0 | 3.30 | 8 |
| 92 | 32.0 | -78.0 | -36.0 | 3.30 | 8 |
| 93 | -34.0 | -68.0 | -28.0 | 3.30 | 8 |
| 94 | 30.0 | -64.0 | -4.0 | 3.29 | 8 |
| 95 | 2.0 | -80.0 | -10.0 | 3.29 | 16 |
| 96 | 42.0 | -50.0 | -44.0 | 3.29 | 8 |
| 97 | 8.0 | -84.0 | -12.0 | 3.29 | 8 |
| 98 | 16.0 | -70.0 | -52.0 | 3.27 | 8 |
| 99 | -38.0 | 24.0 | -24.0 | 3.26 | 8 |
| 100 | -26.0 | 4.0 | 48.0 | 3.26 | 8 |
| 101 | 28.0 | -84.0 | 22.0 | 3.26 | 8 |
| 102 | -16.0 | -82.0 | -28.0 | 3.24 | 8 |
| 103 | -36.0 | -40.0 | 58.0 | 3.23 | 8 |
| 104 | -44.0 | -10.0 | 6.0 | 3.23 | 8 |
| 105 | -14.0 | -44.0 | -46.0 | 3.23 | 8 |
| 106 | 14.0 | -72.0 | -46.0 | 3.23 | 8 |
| 107 | 34.0 | -48.0 | 0.0 | 3.22 | 8 |
| 108 | -14.0 | 42.0 | 20.0 | 3.21 | 8 |
| 109 | 48.0 | -18.0 | 58.0 | 3.21 | 8 |
| 110 | -10.0 | 10.0 | 18.0 | 3.20 | 8 |
| 111 | 16.0 | -66.0 | -46.0 | 3.20 | 8 |
| 112 | -40.0 | -48.0 | -36.0 | 3.20 | 8 |
| 113 | 2.0 | -82.0 | -16.0 | 3.20 | 8 |
| 114 | -46.0 | -6.0 | 0.0 | 3.19 | 8 |
| 115 | 36.0 | 34.0 | 12.0 | 3.19 | 8 |
| 116 | 20.0 | -86.0 | -14.0 | 3.19 | 8 |
| 117 | -42.0 | -4.0 | 56.0 | 3.19 | 8 |
| 118 | -10.0 | -24.0 | 20.0 | 3.18 | 8 |
| 119 | 34.0 | -56.0 | -50.0 | 3.18 | 8 |
| 120 | 0.0 | -24.0 | 46.0 | 3.17 | 8 |
| 121 | -16.0 | -70.0 | -30.0 | 3.17 | 8 |
| 122 | 18.0 | -66.0 | -32.0 | 3.17 | 8 |
| 123 | 38.0 | -44.0 | -16.0 | 3.17 | 8 |
| 124 | -32.0 | -70.0 | -56.0 | 3.17 | 8 |
| 125 | 40.0 | -60.0 | 44.0 | 3.16 | 8 |
| 126 | 34.0 | 12.0 | 34.0 | 3.16 | 8 |
| 127 | 62.0 | -38.0 | 4.0 | 3.16 | 8 |
| 128 | 36.0 | -66.0 | -42.0 | 3.15 | 8 |
| 129 | 40.0 | -64.0 | -44.0 | 3.15 | 8 |
| 130 | -6.0 | -42.0 | 8.0 | 3.15 | 8 |
| 131 | -28.0 | -8.0 | -12.0 | 3.15 | 8 |
| 132 | -14.0 | 16.0 | 34.0 | 3.15 | 8 |
| 133 | 32.0 | -58.0 | -44.0 | 3.15 | 8 |
| 134 | -22.0 | -94.0 | -10.0 | 3.14 | 8 |
| 135 | 22.0 | -80.0 | -50.0 | 3.14 | 8 |
| 136 | 54.0 | -4.0 | 50.0 | 3.14 | 8 |
| 137 | 12.0 | -58.0 | -34.0 | 3.13 | 8 |
| 138 | 40.0 | -64.0 | -36.0 | 3.13 | 8 |
| 139 | -6.0 | -14.0 | 22.0 | 3.13 | 8 |
| 140 | -48.0 | -8.0 | 54.0 | 3.13 | 8 |
| 141 | 12.0 | -78.0 | 10.0 | 3.13 | 8 |
| 142 | 2.0 | -44.0 | -44.0 | 3.13 | 8 |
| 143 | 24.0 | -16.0 | 12.0 | 3.12 | 8 |
| 144 | -16.0 | -70.0 | -6.0 | 3.12 | 8 |
| 145 | -28.0 | -22.0 | 58.0 | 3.11 | 8 |
| 146 | -34.0 | -76.0 | -36.0 | 3.11 | 16 |
| 147 | -36.0 | -60.0 | -56.0 | 3.11 | 8 |
| 148 | -46.0 | -8.0 | 34.0 | 3.11 | 8 |
| 149 | 18.0 | -50.0 | -62.0 | 3.11 | 8 |
| 150 | -20.0 | -42.0 | -10.0 | 3.11 | 8 |
| 151 | -18.0 | -32.0 | -28.0 | 3.10 | 8 |
| 152 | -52.0 | -4.0 | -38.0 | 3.10 | 8 |
| 153 | 28.0 | -56.0 | 10.0 | 3.10 | 8 |
| 154 | 44.0 | -62.0 | -42.0 | 3.10 | 8 |
| 155 | -32.0 | -68.0 | -58.0 | 3.10 | 8 |
| 156 | -40.0 | -66.0 | -26.0 | 3.10 | 8 |
| 157 | 40.0 | -64.0 | 10.0 | 3.10 | 8 |
| 158 | 24.0 | -80.0 | -38.0 | 3.09 | 8 |
| 159 | 34.0 | -76.0 | -24.0 | 3.09 | 8 |
About
- Date preprocessed:
Surface GLM¶
Statistical Report - Second Level Model Implement the :term:`General Linear Model<GLM>` for multiple subject :term:`fMRI` data.
WARNING
- The model has not been fit yet.
Description
Data were analyzed using Nilearn (version= 0.11.2.dev245+geee20d69f; RRID:SCR_001362).
At the group level, a mass univariate analysis was performed with a linear regression at each voxel of the brain.
Model details
Design Matrix
No design matrix was provided.
Contrasts
No contrast was provided.
Mask
No mask was provided.
Statistical Maps
No statistical map was provided.
About
- Date preprocessed: