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[wiki:Self:FsTutorial top] | [wiki:Self:FsTutorial/FslFeatFreeSurfer previous]
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== FreeSurfer Tutorial: Applying FreeSurfer Tools to SPM fMRI Analysis ==
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The purpose of these series of exercises is to give you some familiarity with integrating FreeSurfer and SPM's functional analysis. The main challenge in the integration is getting a subject's anatomical data properly registered with their functional data. Once registered, you can use FreeSurfer display tools to visualize your SPM functional activation maps on the subject's anatomical volume and on the surface. You can also convert to the common surface space for group analysis with mris_glm, GFEAT, or FSL's randomise.

For structural data, we will use ${SUBJECTS_DIR}/bert and ${SUBJECTS_DIR}/average7. For functional data, we will use fbert.img. The functional data set consists of 85 volumes, each 64 x 64 x 35 voxels, with size 3.4375 x 3.4375 x 4.0 mm^3. TR = 3 sec. The experiment a periodic block design with 15 sec ON blocks of simultaneous finger tapping, flashing checker board, and auditory tone. The OFF blocks are rest periods. The paradigm starts with an OFF block. The functional analysis has been precomputed for this data by running Feat. Feat was set up using the Simple Model Setup, ABAB..., A = 15 sec, B = 15 sec; and a Full analysis was performed to create fbert.feat.

=== 1.0 Registration ===

The registration process computes a matrix that maps the FEAT example_func to the subject's anatomical using FLIRT. This matrix can then be used in later steps to display functional maps on the anatomical volume and the surface.
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=== 2.0 Overlaying ===

The statistical maps from Feat may be overlaid onto the subject's anatomical volume, the surface derived from the anatomical volume, or the FSL's standard volume. All these options are described in the following exercise.
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=== 3.0 Mapping automatic segmentations ===

FreeSurfer automatically generates cortical and subcortical segmentations from the subject's anatomical data. These segmentations can be mapped into the functional space for performing region of interest (ROI) analysis. Then, the segmentation for a particular structure can be extracted to create a binary mask. Go through the following exercise for details.

 * [wiki:Self:FsTutorial/MapSegmentationsToFunctionalSpace Exercise C. Mapping automatic segmentations to the functional space]

=== 4.0 Preparing functional data for group analysis on the surface ===

For group analysis of functional data (which won't be covered in this exercise), make sure the following files can be found inside each feat directory:
 * fbert.feat/reg_surf-lh-average7/stats/cope1.img if using '''GFEAT'''
 * fbert.feat/reg_surf-lh/stats/cope1.img if using '''mris_glm'''
For mris_glm, you can use the reg_surf-lh/stats/cope1.img for all the subjects in the analysis as the argument to the --i flag. We're still working on getting a nice GFEAT interface to the surface analysis.

=== 5.0 Troubleshooting ===

If the registration has catastrophically failed, then check that the registration to standard space did not fail:
{{{
tkregister2 --targ $FSLDIR/etc/standard/avg152T1_brain.img \
            --mov fbert.feat/example_func.img \
            --fslreg fbert.feat/reg/example_func2standard.mat \
            --reg /tmp/tmp.reg.dat
}}}

[wiki:FsTutorial top] | [wiki:FsTutorial/FslFeatFreeSurfer previous]

FreeSurfer Tutorial: Applying FreeSurfer Tools to SPM fMRI Analysis

The purpose of these series of exercises is to give you some familiarity with integrating FreeSurfer and SPM's functional analysis. The main challenge in the integration is getting a subject's anatomical data properly registered with their functional data. Once registered, you can use FreeSurfer display tools to visualize your SPM functional activation maps on the subject's anatomical volume and on the surface. You can also convert to the common surface space for group analysis with mris_glm, GFEAT, or FSL's randomise.

For structural data, we will use ${SUBJECTS_DIR}/bert and ${SUBJECTS_DIR}/average7. For functional data, we will use fbert.img. The functional data set consists of 85 volumes, each 64 x 64 x 35 voxels, with size 3.4375 x 3.4375 x 4.0 mm^3. TR = 3 sec. The experiment a periodic block design with 15 sec ON blocks of simultaneous finger tapping, flashing checker board, and auditory tone. The OFF blocks are rest periods. The paradigm starts with an OFF block. The functional analysis has been precomputed for this data by running Feat. Feat was set up using the Simple Model Setup, ABAB..., A = 15 sec, B = 15 sec; and a Full analysis was performed to create fbert.feat.

1.0 Registration

The registration process computes a matrix that maps the FEAT example_func to the subject's anatomical using FLIRT. This matrix can then be used in later steps to display functional maps on the anatomical volume and the surface.

2.0 Overlaying

The statistical maps from Feat may be overlaid onto the subject's anatomical volume, the surface derived from the anatomical volume, or the FSL's standard volume. All these options are described in the following exercise.

3.0 Mapping automatic segmentations

FreeSurfer automatically generates cortical and subcortical segmentations from the subject's anatomical data. These segmentations can be mapped into the functional space for performing region of interest (ROI) analysis. Then, the segmentation for a particular structure can be extracted to create a binary mask. Go through the following exercise for details.

4.0 Preparing functional data for group analysis on the surface

For group analysis of functional data (which won't be covered in this exercise), make sure the following files can be found inside each feat directory:

  • fbert.feat/reg_surf-lh-average7/stats/cope1.img if using GFEAT

  • fbert.feat/reg_surf-lh/stats/cope1.img if using mris_glm

For mris_glm, you can use the reg_surf-lh/stats/cope1.img for all the subjects in the analysis as the argument to the --i flag. We're still working on getting a nice GFEAT interface to the surface analysis.

5.0 Troubleshooting

If the registration has catastrophically failed, then check that the registration to standard space did not fail:

tkregister2 --targ $FSLDIR/etc/standard/avg152T1_brain.img \
            --mov fbert.feat/example_func.img \
            --fslreg fbert.feat/reg/example_func2standard.mat \
            --reg /tmp/tmp.reg.dat

FsTutorial/SpmFreeSurfer (last edited 2021-09-22 11:41:09 by DevaniCordero)