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Data Acquisition and Preprocessing in fMRI: A Comprehensive Workshop Overview

This workshop, hosted by Dartmouth College's Department of Psychological and Brain Sciences in collaboration with Yale MR Imaging Center and Kennedy Krieger Institute, focuses on the essentials of fMRI data acquisition and preprocessing techniques. Participants will explore the anatomy of functional data, including slice orientations and localizer sequences, and learn critical preprocessing steps such as motion correction, spatial smoothing, and normalization to align brain images. The workshop also covers statistical analysis, noise reduction, and effective methods to identify brain structures, providing a foundational understanding for effective fMRI research.

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Data Acquisition and Preprocessing in fMRI: A Comprehensive Workshop Overview

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  1. Haskins fMRI WorkshopPart I:Data Acquisition & Preprocessing

  2. fMRI Setup

  3. Dartmouth College Department of Psychological and Brain Sciences Collaborations Yale University Yale MR Imaging Center Kennedy Krieger Institute F.M. Kirby Research Center for Functional Brain Imaging

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

  5. 3D space definitions 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 hemisphere Tal 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 • http://www.sph.sc.edu/comd/rorden/anatomy/home.html

  6. slice orientations sagittal coronal axial

  7. Typical Acquisition Sequence three-plane “localizer” sagittal “scout” axial T1 anatomic several functional runs... high-resolution anatomic (MP-RAGE) Diffusion Tensor Imaging....

  8. Slice Locations

  9. Simulated Hemodynamic Response Noise SD = 0 Noise SD = 10 Noise SD = 100

  10. kki0032 trial timecourse

  11. Preprocessing steps functional data: • adjust for slice acquisition time sinc interpolation; “temporal realignment” • adjust for motion “motion correction”; “(spatial) realignment” • apply spatial smoothing gaussian filter anatomic data: • strip skull from image • align with a common template “normalization”

  12. 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 acquisition order 2 1 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. stimulus onset at time 0

  13. motion parameters

  14. motion artefacts

  15. motion artefacts

  16. motion parameters

  17. motion processing

  18. smoothing -- 3.125 versus 6.25

  19. normalization Basic 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

  20. skull stripping...

  21. kki0032

  22. kki0032

  23. kki0032

  24. end of part 1.

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