Group level analyses

An analysis of the spatial distribution of significant clusters resulting from group level analyses with assumed true designs (Figures 3.13-3.16) reveals similar patterns as from first level analyses. Importantly, for the event-related design dataset, the addition of the derivatives led to much higher amount of significant activation, but only for the F-test. For the t-test, sensitivity deteriorated when the partial derivatives were added to the model. Across the different datasets, the use of the flexible HRF models led to many significant clusters scattered across the brain. The “CRIC checkerboard” dataset was not investigated, as the corresponding group mask did not cover visual cortex. For the subjects from this dataset, some brains were deformed and registrations to MNI space were imperfect.

An investigation of the percentage of significant voxels (Figures 3.17-3.18) confirmed that the addition of the derivatives for an event-related design dataset can only increase sensitivity if statistical inference is conducted with an F-test. Figure 3.18 showed that the flexible HRF models: tent, csplin, FIR and the Fourier set, often displayed much significant activation for the true design, but also displayed much significant activation for the wrong designs. This suggests problems with specificity, though these problems might be related to the employed random effects model.

AFNI with t-test FSL with t-test SPM with t-test

AFNI with F-test FSL with F-test SPM with F-test

Figure 3.13: Group level analyses: spatial distribution of significant clusters for the “CamCAN sen- sorimotor” dataset, HRF models from AFNI, FSL and SPM and the true experimental design. At the top there are results for t-test on the canonical function and at the bottom there are results for F-test on all HRF-related covariates. Four exemplary MNI axial slices from the bottom to the top of the head were selected (left to right).

AFNI with t-test FSL with t-test SPM with t-test

AFNI with F-test FSL with F-test SPM with F-test

Figure 3.14: Group level analyses: spatial distribution of significant clusters for the “NKI checker- board (TR=1.4s)” dataset, HRF models from AFNI, FSL and SPM and the true experimental design. At the top there are results for t-test on the canonical function and at the bottom there are results for F-test on all HRF-related covariates. Four exemplary MNI axial slices from the bottom to the top of the head were selected (left to right).

AFNI with t-test FSL with t-test SPM with t-test

AFNI with F-test FSL with F-test SPM with F-test

Figure 3.15: Group level analyses: spatial distribution of significant clusters for the “NKI checker- board (TR=0.645s)” dataset, HRF models from AFNI, FSL and SPM and the true experimental design. At the top there are results for t-test on the canonical function and at the bottom there are results for F-test on all HRF-related covariates. Four exemplary MNI axial slices from the bottom to the top of the head were selected (left to right).

AFNI with t-test FSL with t-test SPM with t-test

AFNI with F-test FSL with F-test SPM with F-test

Figure 3.16: Group level analyses: spatial distribution of significant clusters for the “BMMR checker- board” dataset, HRF models from AFNI, FSL and SPM and the true experimental design. At the top there are results for t-test on the canonical function and at the bottom there are results for F-test on all HRF-related covariates. Four exemplary MNI axial slices from the bottom to the top of the head were selected (left to right).

gam2 gam2+T gam2+TD AFNI 0 20 40 60 80 % of sig vo xels gam2 gam2+T FSL CamCAN sensorimotor (TR=1.97s)

gam2 gam2+T gam2+TD

SPM

gam2 gam2+T gam2+TD

0 5 10 15 20 % of sig vo xels gam2 gam2+T NKI checkerboard (TR=1.4s)

gam2 gam2+T gam2+TD

gam2 gam2+T gam2+TD

0 5 10 15 20 25 30 % of sig vo xels gam2 gam2+T NKI checkerboard (TR=0.645s)

gam2 gam2+T gam2+TD

boxcar 12s off + 12s on boxcar 16s off + 16s on

boxcar 20s off + 20s on CamCAN event-related design

~U(3,6)s off + 0.1s on True experimental design gam2 gam2+T gam2+TD

0 20 40 60 80 % of sig vo xels gam2 gam2+T BMMR checkerboard (TR=3s)

gam2 gam2+T gam2+TD

boxcar 12s off + 12s on boxcar 16s off + 16s on

boxcar 20s off + 20s on CamCAN event-related design

~U(3,6)s off + 0.1s on True experimental design

Figure 3.17: Group level analyses: percentage of significant voxels resulting from t-test on the canonical function only. For each dataset, five designs were assumed, one of which was the true design. For the “CRIC checkerboard” dataset, several of the subjects had deformed brains, which led to the group brain mask not covering the primary visual cortex. Thus, I excluded this dataset from the group analyses.

gam2 gam2+T gam2+TD tent csplin AFNI 0 20 40 60 80 % of sig vo xels

gam2 gam2+T gam1 gam1+T FIR

FSL

CamCAN sensorimotor (TR=1.97s)

gam2 gam2+T gam2+TD Fourier FIR

SPM

gam2 gam2+T gam2+TD tent csplin

0 5 10 15 20 % of sig vo xels

gam2 gam2+T gam1 gam1+T FIR

NKI checkerboard (TR=1.4s)

gam2 gam2+T gam2+TD Fourier FIR

gam2 gam2+T gam2+TD tent csplin

0 5 10 15 20 25 30 % of sig vo xels

gam2 gam2+T gam1 gam1+T FIR

NKI checkerboard (TR=0.645s)

gam2 gam2+T gam2+TD Fourier FIR

boxcar 12s off + 12s on boxcar 16s off + 16s on

boxcar 20s off + 20s on CamCAN event-related design

~U(3,6)s off + 0.1s on True experimental design gam2 gam2+T gam2+TD tent csplin

0 20 40 60 80 % of sig vo xels

gam2 gam2+T gam1 gam1+T FIR

BMMR checkerboard (TR=3s)

gam2 gam2+T gam2+TD Fourier FIR

boxcar 12s off + 12s on boxcar 16s off + 16s on

boxcar 20s off + 20s on CamCAN event-related design

~U(3,6)s off + 0.1s on True experimental design

Figure 3.18: Group level analyses: percentage of significant voxels resulting from F-test on all HRF- related covariates. For each dataset, five designs were assumed, one of which was the true design. For the “CRIC checkerboard” dataset, several of the subjects had deformed brains, which led to the group brain mask not covering the primary visual cortex. Thus, I excluded this dataset from the group analyses.