Archived FMRI pipeline: Difference between revisions
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==About fMRI data and file types== | ==About fMRI data and file types== | ||
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Note that, when handling neuroimaging data, you need to take special care that the orientation of the images is correct. | Note that, when handling neuroimaging data, you need to take special care that the orientation of the images is correct. | ||
==Standard Preprocessing Steps== | ==Standard Preprocessing Steps & The Pipeline== | ||
In what follows, we describe the broad stages of fMRI preprocessing. Note that | In what follows, we describe the broad stages of fMRI preprocessing. Note that the pipeline saves the data after each intermediate step in newly created files with relevant prefixes. | ||
====Slice-timing Correction==== | ====Slice-timing Correction==== | ||
This step corrects for the time-delay between the acquisition of different slices. | This step corrects for the time-delay between the acquisition of different slices. | ||
====Rigid body Correction==== | ====Rigid body Correction==== | ||
This step estimates, characterises and broadly corrects for the effect of head-motion. It is also the step at which one can exclude subjects with excessive head-motion (e.g. more than a voxel size). | This step estimates, characterises and broadly corrects for the effect of head-motion. It is also the step at which one can exclude subjects with excessive head-motion (e.g. more than a voxel size). | ||
====Registration to Standard Space==== | ====Registration to Standard Space==== | ||
Chose source image, template (EPI), method, image size, voxel size (2x2x2). (This is the 'Normalize' option in SPM. ) | |||
====Regressing out head motion, CSF, white matter & physiological signals==== | ====Regressing out head motion, CSF, white matter & physiological signals==== | ||
In SPM, this is done under '1st level analysis' -> 'Data and design' -> 'Multiple regression'. | (In SPM, this is done under '1st level analysis' -> 'Data and design' -> 'Multiple regression'.) | ||
==Parcellation== | ==Parcellation== | ||
Revision as of 14:37, 23 April 2012
NOTE: THIS PAGE NEEDS FILLING IN!
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.
Standard Preprocessing Steps & The Pipeline
In what follows, we describe the broad stages of fMRI preprocessing. Note that the pipeline saves the data after each intermediate step in newly created files with relevant prefixes.
Slice-timing Correction
This step corrects for the time-delay between the acquisition of different slices.
Rigid body Correction
This step estimates, characterises and broadly corrects for the effect of head-motion. It is also the step at which one can exclude subjects with excessive head-motion (e.g. more than a voxel size).
Registration to Standard Space
Chose source image, template (EPI), method, image size, voxel size (2x2x2). (This is the 'Normalize' option in SPM. )
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
A very basic tutorial on wavelets can be found here: [[1]]
For details on the wavelet toolbox in MATLAB, read: [[2]]
The question of smoothing
Required before VBM. Important for finding activations regions. Not used when parcellating (for network analysis).
DVARS and the motion problem
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