haskins fmri workshop part i: data acquisition & preprocessing

Haskins fMRI WorkshopPart I:

Data Acquisition & Preprocessing

fMRI Setup

Collaborations

Yale UniversityYale MR Imaging Center

Dartmouth CollegeDepartment of Psychological

and Brain Sciences

Kennedy Krieger InstituteF.M. Kirby Research Center for Functional Brain Imaging

Magnet...

Source: www.howstuffworks.com Source: http://www.simplyphysics.com/flying_objects.html

3D space definitions

• http://www.sph.sc.edu/comd/rorden/anatomy/home.html

Standard coordinates are listed as mm distances from the origin (the anterior commisure) along the x/y/z dimensions.

some examples:

Broca’s area, left hemisphereTal x=-54 y=27 z=9

right cerebellum:Tal x=33 y=-45 z=-39

left occipitotemporal region:Tal x=-39 y=-45 z=-19

slice orientations

axial

sagittal coronal

Typical Acquisition Sequence

1) three-plane “localizer”

2) sagittal “scout”

3) axial T1 anatomic

4) several functional runs...

5) high-resolution anatomic (MP-RAGE)

6) Diffusion Tensor Imaging....

Slice Locations

Simulated Hemodynamic Response

Noise SD = 0

Noise SD = 10

Noise SD = 100

kki0032 trial timecourse

Preprocessing steps

functional data:• adjust for slice acquisition time

sinc interpolation; “temporal realignment”• adjust for motion

“motion correction”; “(spatial) realignment”

• apply spatial smoothinggaussian filter

anatomic data:• strip skull from image• align with a common template

“normalization”

slice acquisition time...

We typically acquire 20 (functional) slices in each 2-second interval. Each one takes 100 msec. Must account for this in analysis...

functional data:• adjust for slice acquisition time

stimulus onset at time 0

slice #1 (circles) is acquired at times 0/2/4/6/8... seconds exactly.

slice #2 (diamonds) is acquired 100msec later, at times 0.1/2.1/4.1/6.1/8.1... seconds post-stimulus.

12

acquisitionorder

motion parameters

motion artefacts

motion artefacts

motion parameters

motion processing

smoothing -- 3.125 versus 6.25

normalizationBasic idea: find a transformation that will spatially shift this subject’s brain to

align with a template, so that subjects can be averaged together. This also allows us to use a pre-labelled atlas to identify structures.

important concepts:• spatial transformations:

linear: translation, rotation, scaling; nonlinear: warps• degrees of freedom (DOF)

6: Rigid Body; 7: adds global rescale; 12: affine (adds shear)• similarity functions; search & optimization; resolutions• skull stripping

skull stripping...

kki0032

kki0032

kki0032

end of part 1.