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
• filtering

Detrending - scanner drift removal.

Filtering [0.01-0.1]

6. First level analysis (GLM)

Block design (3 blocks)

Even-related design (3 events)