Research course on functional magnetic resonance imaging

Lecture 2

Juha Salmitaival

Today’s lecture– Preprocessing• Motion correction• Slice timing correction• Spatial filtering• Temporal filtering• ICA denoising• Global intensity correction

– Registration– FSL demo• Things we have learned so far

Preprocessing – general things• Signal changes in BOLD are typically somewhere

between 0.1% and 5%• To enhance the signal and reduce the noise• To prepare the data for statistical analysis• Learn to know your data!

Preprocessing – motion correction• Padding around the head to avoid movement!• Head movements -> different tissue in same voxel

and artefactual signal changes

Preprocessing – motion correction• How much motion is too much?• Large jumps are more serious than slow drifts• Exclusion: outlier?, 1mm?• If you have stimulus correlated motion, you

probably need other methods (e.g., INRIAlign)

Preprocessing – slice timing correction

• Slices are scanned at a slightly different time (0,2,4,…1,3,5…)

Preprocessing – spatial filtering• How big are your blobs?• -> increases SNR• -> Gaussian distribution

(thresholding)• Typically 3-10 mm

Preprocessing – temporal filtering• Scanner-related and

physiological drifts• HP filter - usually, LP filter if

needed (MELODIC?)• Cycle length x 1.5

Preprocessing – ICA denoising• Need to know what the signal should look!– Non gray-matter?, weird time-series/frequency spectrum?

• Individual/group analysis?

Preprocessing – global intensity normalization

Registration of images – whole brain

• Standard spaces: MNI space, Talairach space/atlas (www.talairach.org)

• fMRI space -> perform analysis here if possible• fMRI to structural -> anatomical localization • fMRI to standard -> comparison of results

(between subjects and datasets)• Step 1 estimating transformation (transformation matrix)• Step 2 resampling (modified image)

Registration of images – parameters

• DOFS

• Cost function• correlation ratio (same session T1)• mutual info (T2 anatomical)

• Interpolation

FNIRT- Same modality- High quality

Registration of images• Always check the results visually!

• Two stage registration

• Field map correction

Registration of gyri and sulci

• Individual differences in cortical folding are huge!

Preprocessing & Registration demo• 1. Motion correction (fMRI image)• 2. Brain extraction (manual check!)• 3. FEAT preprocessing• (4. fMRI modeling/statistics (next weeks topic))• 5. FLIRT registration (manual check!)

Groups

• 1 GLM and ICA: music vs. speech, audiovisual interaction– Jussi, Onerva, Hanna, Olli-Pekka

• 2 artifacts and signals (ICA/GLM)– Dinos, Jari T., Juha P., Eero K, Timo

• 3 cross-sensory coherence (ISC)– Alexander, Anne, Jonathan, Jaakko

• Passwords / Computers

About the dataset– The data is not only for this course, but also for

scientific purposes– Original plan is not to use any of your work in

publication– If you think that your contribution is enough to be

author in the publication, please discuss with me!– If you want to publish something out of the data,

come to discuss with me!

References & Images

• FSL-course– http://www.fmrib.ox.ac.uk/fslcourse/

• SPM-course– http://www.fil.ion.ucl.ac.uk/spm/course/