fMRI preprocessing and functional connectivity
I. fMRI preprocessing
a) Acquisition and Quality control
b) What do we measure?
c) General preprocessing (RS-fMRI, taks fMRI)
d) RS-fMRI additional steps
e) GLM for task-fMRI
II. Functional connectivity
a) seed-based connectivity
b) ROI-based connectivity
c) ICA
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I. fMRI preprocessing
Toolboxes for preprocessing: SPM, FSL, AFNI
Toolboxes for functional connecitivity: REST, GIFT, CONN.
SPM is widely used, a lot of documentation, wikibook, tutorials, datasets etc.
SPM is based on Matlab scripts and compatible with Windows, Mac and Linux.
User inteface: GUI or command line (also Batch).
1. How to start?
Install Matlab and SPM8 toolbox.
Reference:
2. Imaging data provided in DICOM format
● SPM uses the NIFTI (.nii) format
● conversion to NIFTI from DICOM
Matlab has a function:
SPM -> Import dicom
MRIcro http://www.mccauslandcenter.sc.edu/mricro (dcm2niigui)
3. Read header information
repetition time (TR)
number of slice in a volume
Order of the scanning sequence (ascending, descending, interleaved)
4. fMRI analysis is performed in 3 steps:
- Preprocessing
- 1st level analysis
- 2nd level analysis
Preprocessing:
◼ slice timing
◼ realign
◼ coregister
◼ segment
◼ normalize
◼ smooth
Slice timing -
Realigment = motion correction
Coregister two modalities: T1 and T2
Segmentation (AC/PC), GM, WM
Normalization to MNI space
Smoothing -
5. Resting state fMRI
Detrending - scanner drift removal.
Filtering [0.01-0.1]
6. First level analysis (GLM)
Block design (3 blocks)
Even-related design (3 events)
