Archived FMRI pipeline: Difference between revisions
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=== | ==About fMRI data and file types== | ||
=== | Raw fMRI data is saved in .dcm (dicom) files. Typically these .dcm files correspond to individual slices, and the resulting 3D image (or a time-series of 3D images) is saved in a .nii (nifti) file. Raw dicom files can be transformed into nifti format using SPM (a MATLAB software package implementing Statistical Parametric Mapping for neuroimaging data) or other software such as MRIcro. | ||
Note that, when handling neuroimaging data, you need to take special care that the orientation of the images is correct. | |||
==Preprocessing in SPM== | |||
In what follows, we describe the broad stages of fMRI preprocessing, and how they are implemented in SPM: | |||
===Load the data=== | |||
===Slice-timing Correction=== | |||
===Rigid body Correction=== | |||
===Registration to Standard Space=== | ===Registration to Standard Space=== | ||
=== | This is the 'Normalize' option in SPM. Chose source image, template (EPI), method, image size, voxel size (2x2x2). | ||
===Wavelet Decomposition=== | ===Regressing out head motion, CSF, white matter & physiological signals=== | ||
In SPM, this is done under '1st level analysis' -> 'Data and design' -> 'Multiple regression'. | |||
==Parcellation== | |||
==Wavelet Decomposition== | |||
==The question of smoothing== | |||
Required before VBM. Important for finding activations regions. Not used when parcellating (for network analysis). | |||
===Back To Main Page=== | ===Back To Main Page=== | ||
[[Main Page]] | [[Main Page]] | ||
Revision as of 11:08, 23 October 2011
About fMRI data and file types
Raw fMRI data is saved in .dcm (dicom) files. Typically these .dcm files correspond to individual slices, and the resulting 3D image (or a time-series of 3D images) is saved in a .nii (nifti) file. Raw dicom files can be transformed into nifti format using SPM (a MATLAB software package implementing Statistical Parametric Mapping for neuroimaging data) or other software such as MRIcro.
Note that, when handling neuroimaging data, you need to take special care that the orientation of the images is correct.
Preprocessing in SPM
In what follows, we describe the broad stages of fMRI preprocessing, and how they are implemented in SPM:
Load the data
Slice-timing Correction
Rigid body Correction
Registration to Standard Space
This is the 'Normalize' option in SPM. Chose source image, template (EPI), method, image size, voxel size (2x2x2).
Regressing out head motion, CSF, white matter & physiological signals
In SPM, this is done under '1st level analysis' -> 'Data and design' -> 'Multiple regression'.
Parcellation
Wavelet Decomposition
The question of smoothing
Required before VBM. Important for finding activations regions. Not used when parcellating (for network analysis).
