Selxavg3-sess: Difference between revisions
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== Running selxavg3-sess == | == Running selxavg3-sess == | ||
This command runs a GLM regression on the BOLD time series for each run separately. This creates a 3D file that stores a statistic for each voxel for each experimental run that indicates how well the activity for that voxel conformed with a predicted time series associated with each of your experimental conditions. Assuming you have run all the previous steps in the [[FreeSurfer#FS-FAST_Setup_Overview | FS-FAST overview]], there will be one, two or three analysis directories in your $SUBJECTS_DIR, generated by [[Configure_mkanalysis-sess|mkanalysis-sess]]. These directories will contain all the information to perform surface-space analyses in your left/right or mni305 (voxel-space, for subcortical regions which are not included in the surface models) models. If you have configured contrasts using [[Configure_mkcontrast-sess|mkcontrast-sess]], then this step will perform the statistical condition contrasts you | This command runs a GLM regression on the BOLD time series for each run separately. This creates a 3D file that stores a statistic for each voxel for each experimental run that indicates how well the activity for that voxel conformed with a predicted time series associated with each of your experimental conditions. Assuming you have run all the previous steps in the [[FreeSurfer#FS-FAST_Setup_Overview | FS-FAST overview]], there will be one, two or three analysis directories in your $SUBJECTS_DIR, generated by [[Configure_mkanalysis-sess|mkanalysis-sess]]. These directories will contain all the information to perform surface-space analyses in your left/right or mni305 (voxel-space, for subcortical regions which are not included in the surface models) models. If you have configured contrasts using [[Configure_mkcontrast-sess|mkcontrast-sess]], then this step will perform the statistical condition contrasts you had specified in that step. | ||
=== Batch mode === | === Batch mode === | ||
Revision as of 12:00, 21 April 2016
Before you begin
Ensure that your BOLD data has the correct timing info. See Freesurfer BOLD files for information on changing the TR for your data. If your BOLD data files are not named 'f.nii', you likely have missed a step.
Running selxavg3-sess
This command runs a GLM regression on the BOLD time series for each run separately. This creates a 3D file that stores a statistic for each voxel for each experimental run that indicates how well the activity for that voxel conformed with a predicted time series associated with each of your experimental conditions. Assuming you have run all the previous steps in the FS-FAST overview, there will be one, two or three analysis directories in your $SUBJECTS_DIR, generated by mkanalysis-sess. These directories will contain all the information to perform surface-space analyses in your left/right or mni305 (voxel-space, for subcortical regions which are not included in the surface models) models. If you have configured contrasts using mkcontrast-sess, then this step will perform the statistical condition contrasts you had specified in that step.
Batch mode
If you want to run the same analysis on multiple participants in batch mode, you must first create a plain text file containing all the participant IDs (i.e., the folder names) for those you wish to analyze. If you ran preproc-sess in batch mode, then you can simply reuse the sessid file you created for that purpose. See the preproc-sess instructions for creating that file. Batch mode uses the -sf switch, which is the same as the switch used for running preproc-sess in batch mode.
selxavg3-sess -sf <sessid_file> -analysis <analysis_dir>
Individual mode
Alternatively, you may run the analysis on one participant at the time using the -s switch, and providing a single participant ID name.
selxavg3-sess -s <sessid> -analysis <analysis_dir>
Example
selxavg3-sess -s FS_T1_501 -analysis booth500.sm6.lh