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

fMRI data analysis at CCBI

Vladimir Cherkassky

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

FIASCO data preprocessing

• Baseline correction

• de-ghosting

• mean correction

• motion correction

• outlier detection and removal

• Trend correction

• T-map computation

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

Activated voxels detected at t=6

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

Co-registration of functional and anatomical data

Brain areas

Regions Of Inerest (ROI)

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

Number of activated voxels per ROI

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, ...

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.

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

Averaged group activation

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

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.

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

Averaged tc for the two areas involved in thelanguage task.

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

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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.

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

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Between subjects variability of the averaged tc (event-related

study)

Functional connectivity within thelanguage network for autistic andcontrol groups.

Note the systematically higherconnectivity level for the controlgroup.

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

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

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.