fmri data analysis at ccbi vladimir cherkassky. detection of activated voxels always performed on a...

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fMRI data analysis at CCBI Vladimir Cherkassky

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Page 1: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

fMRI data analysis at CCBI

Vladimir Cherkassky

Page 2: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Detection of Activated Voxels

• Always performed on a voxel-to-voxel basis

• T-test comparing mean values during two experimental conditions (FIASCO)

• Covariance of the time course with the paradigm function (SPM, Voxcor.id, etc.)

• Threshold estimation and selection

Page 3: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

FIASCO data preprocessing

• Baseline correction

• de-ghosting

• mean correction

• motion correction

• outlier detection and removal

• Trend correction

• T-map computation

Page 4: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Processing steps (single subject)

• Fiasco processing (active voxel detection)

• Co-registration of functional and anatomical data.

• Subject-specific ROI definition

• Volume and distribution of activation

• Functional connectivity

• Morphing into standard space

Page 5: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Activated voxels detected at t=6

Page 6: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Probability map thresholding

• Correction for multiple comparisons

• Scanner-specific data properties

• Spatial correlation among voxels

• Additional considerations

• Comparing groups:– “High activators” and “low activators”– Normalization (selecting most activated voxels)– FDR (false discovery rate) method

Page 7: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Co-registration of functional and anatomical data

Page 8: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Brain areas

Page 9: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Regions Of Inerest (ROI)

Page 10: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Activation at t=6 and ROIs defined on the basis of subject-specific anatomical landmarks

Number of activated voxels per ROI

Page 11: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Processing steps (group analysis)

• ANOVA analysis of volume of activation

• ANOVA analysis of location of activation (centroids in standard space)

• ANOVA analysis of functional connectivity

• Standard space averaging (“hit” maps)

• Additional analyses:– Factor analysis, MDS, ...

Page 12: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Average volume of activation per ROI for the two groups of subjects:

autistic participants and matched control participants.

Sentence comprehension task.

Highlighted areas show statistically significant group difference.

Normalization thresholds used for between-group analysis.

Page 13: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Difference in the distribution of activation in the main language areas for the two groups

Page 14: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Averaged group activation

Page 15: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Overall pattern of activation:similar pattern for three groups of subjects

Page 16: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Functional connectivity

• FC is measured as a correlation between averaged time courses (tc) of activated voxels for the two brain areas (ROIs)

• Synchronization can be induced by the connection (direct or indirect) between areas or some common input.

• We interpret FC as a measure of interaction between brain areas working together on the same task.

Page 17: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Time course of activated voxels

• Useful signal is ~2%

• As a result, single voxel tc is extremely noisy

• Averaged tc of all activated voxels within an ROI (min number of voxels we use is 3)

• Most of the ROIs consist of more than one slice

• Correction for the slice acquisition sequence is necessary for proper connectivity estimation

• Images to include in time course calculation

Page 18: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Averaged tc for the two areas involved in thelanguage task.

Note the scale (% signal change from fixation) andthe images included in theanalysis.

Page 19: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

LB

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Averaged tc with differentmethods of interpolation(correction for slice acquisition time)

Though the differences lookminor, linear interpolationintroduces considerably largerlevel of correlation betweenthe time courses.

Page 20: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

SYNAM2 cond 5 LT (normalized to15 voxels) 10 items averaged across subjects

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2945 14 2953 15

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Between subjects variability of the averaged tc (event-related

study)

Page 21: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Functional connectivity within thelanguage network for autistic andcontrol groups.

Note the systematically higherconnectivity level for the controlgroup.

Page 22: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Pairs of areas with statisticallysignificant differences in functional connectivity for thetwo groups of participants

Page 23: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Overall connectivity pattern:

1. Note the high levelof similarity for the twogroups (r=0.69 for allmeasured connections;r=0.95 for the connectionswith significant differences)

2. Note the systematicallyhigher connectivity for thecontrol group

Page 24: FMRI data analysis at CCBI Vladimir Cherkassky. Detection of Activated Voxels Always performed on a voxel-to-voxel basis T-test comparing mean values

Conclusions

• Our approach provides accurate measures of activation volume and location, as well as functional connectivity between the brain areas.

• These measures can be used for testing the effects of experimental manipulations for single subject, group, and between-group analyses.