Connectivity Toolbox - Revision history

Chris: /* Obtaining Denoised Time-Series Data */

2018-11-13T17:36:51Z

Obtaining Denoised Time-Series Data

← Older revision		Revision as of 13:36, 13 November 2018
Line 121:		Line 121:
	...		...

	If this is the case, you can fix it following the [[Freesurfer_BOLD_files#Setting_the_TR_in_the_Terminal_Using_3drefit \| standard procedure for setting your TR]].		If this is the case, you can fix it following the [[Freesurfer_BOLD_files#Setting_the_TR_in_the_Terminal_Using_3drefit \| standard procedure for setting your TR]] (none of our experiments have a 1-second TR; it is likely 2.047).

	When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:		When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:

Chris: /* Obtaining Denoised Time-Series Data */

2018-11-13T17:35:27Z

Obtaining Denoised Time-Series Data

← Older revision		Revision as of 13:35, 13 November 2018
Line 121:		Line 121:
	...		...

	If this is the case, you can fix it following the [Freesurfer_BOLD_files#Setting_the_TR_in_the_Terminal_Using_3drefit standard procedure for setting your TR].		If this is the case, you can fix it following the [[Freesurfer_BOLD_files#Setting_the_TR_in_the_Terminal_Using_3drefit \| standard procedure for setting your TR]].

	When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:		When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:

Chris: /* Obtaining Denoised Time-Series Data */

2018-11-13T17:34:57Z

Obtaining Denoised Time-Series Data

← Older revision		Revision as of 13:34, 13 November 2018
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	After you execute this command in MATLAB, you'll end up with a file with the same name, except with a .nii extension.		After you execute this command in MATLAB, you'll end up with a file with the same name, except with a .nii extension.
	Now, at this point, you probably started off with an f.nii.gz file, and now have a DATA_Subject'xxx'_Session'yyy'.nii file. In order to look at this newly denoised data in FreeSurfer, you will need to run it through the FS-FAST preproc-sess step. There's a good chance the source directory already has an f.nii.gz file, as well as a series of fmcpr.''${direction}''.sm''${smoothing}''.fsaverage.?h.nii.gz files. Assuming you want to hold on to these, I'd make a backup directory in each of the run subdirectories, and move all files to the backup directory (you can keep any .par files here). After you've backed everything up, move the new denoised files into the appropriate directories and rename them to f.nii. When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:		Now, at this point, you probably started off with an f.nii.gz file, and now have a DATA_Subject'xxx'_Session'yyy'.nii file. In order to look at this newly denoised data in FreeSurfer, you will need to run it through the FS-FAST preproc-sess step. There's a good chance the source directory already has an f.nii.gz file, as well as a series of fmcpr.''${direction}''.sm''${smoothing}''.fsaverage.?h.nii.gz files. Assuming you want to hold on to these, I'd make a backup directory in each of the run subdirectories, and move all files to the backup directory (you can keep any .par files here). After you've backed everything up, move the new denoised files into the appropriate directories and rename them to f.nii.

			We have also discovered that the denoised data may have been stripped of its TR information, and so you may have to put this back in. To check if this is the case:
			FILENAME=f.nii
			fslhd ${FILENAME}
			Running this command will spit out the NIfTI file header information. You are looking for the '''dt''' or '''pixdim4''' information:
			...
			pixdim3 4.100000
			'''pixdim4 1.000000''' <-- it says we have a 1-second TR!
			pixdim5 0.000000
			...

			If this is the case, you can fix it following the [Freesurfer_BOLD_files#Setting_the_TR_in_the_Terminal_Using_3drefit standard procedure for setting your TR].

			When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:

	preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold		preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold

	The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your later analysis or data processing scripts accordingly -- just be on the lookout for ''file not found'' errors, and if they pop up, the first thing you should look for is to see if your command or script was expecting a filename with the slice order). Of course, another option would be to manually rename the preprocessed data when preproc-sess is completed, so that the preprocessed denoised data still includes the sliceorder in the name. I'm not sure how big of a problem this minor change in filename is going to be for our various scripts.		The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your later analysis or data processing scripts accordingly -- just be on the lookout for ''file not found'' errors, and if they pop up, the first thing you should look for is to see if your command or script was expecting a filename with the slice order). Of course, another option would be to manually rename the preprocessed data when preproc-sess is completed, so that the preprocessed denoised data still includes the sliceorder in the name. I'm not sure how big of a problem this minor change in filename is going to be for our various scripts.

Erica: /* Processing options */

2018-11-07T17:46:45Z

Processing options

← Older revision		Revision as of 13:46, 7 November 2018
Line 60:		Line 60:
	===Enabled analyses===		===Enabled analyses===
	Check that we want to do Voxel-to-Voxel analyses		Check that we want to do Voxel-to-Voxel analyses
			Other analyses maybe checked by default, unless otherwise specified we only care about Voxel-to-Voxel.
	===Optional output files===		===Optional output files===
	check that we create confound-corrected beta-maps and confound-corrected time-series (our primary objective for using conn).		check that we create confound-corrected beta-maps and confound-corrected time-series (our primary objective for using conn).
Line 67:		Line 68:
	===Analysis mask (voxel-level)===		===Analysis mask (voxel-level)===
	Select Implicit mask (subject-specific) because our subjects voxels are not guaranteed to fall within the template brainmask.		Select Implicit mask (subject-specific) because our subjects voxels are not guaranteed to fall within the template brainmask.

			===Second_Level Analyses===
			Second level analyses is another option in the option menu. Unless otherwise specified you can ignore this option.

	===BOLD signal units===		===BOLD signal units===
	Let's use Raw signal.		Let's use Raw signal.

Erica: /* Structural data */

2018-11-07T17:41:41Z

Structural data

← Older revision		Revision as of 13:41, 7 November 2018
Line 33:		Line 33:

	==Structural data==		==Structural data==
	Here is where you have to find the T1 and surface files for your participants. They made the program clever enough to do pattern matching, so if you pick a root directory, and then indicate the file pattern for the structural data, it will find all the matching files. For example, if you left-click on your $SUBJECTS_DIR, type in T1.mgz and click the '''Find''' button , it will identify the paths to all the structural files generated by FreeSurfer. From there, you highlight the files you wish to work with and click the Select button (make sure the number of selected files matches the number of highlighted Subjects). If the T1 data have already been preprocessed with FreeSurfer, you should be asked if you wish to also import the segmentation files. Say '''Yes'''.		Here is where you have to find the T1 and surface files for your participants, which are found in the 'mri' directory for each participant. They made the program clever enough to do pattern matching, so if you pick a root directory, and then indicate the file pattern for the structural data, it will find all the matching files. For example, if you left-click on your $SUBJECTS_DIR, type in T1.mgz and click the '''Find''' button , it will identify the paths to all the structural files generated by FreeSurfer. From there, you highlight the files you wish to work with and click the Select button (make sure the number of selected files matches the number of highlighted Subjects). If the T1 data have already been preprocessed with FreeSurfer, you should be asked if you wish to also import the segmentation files. Say '''Yes'''.

	One thing I will point out is that our FreeSurfer analyses are done in surface space, which doesn't care about where the particular voxels sit in relation to the cube of voxels surrounding the standard MNI template brain. For that reason, your structural and functional data will seldom be even close to aligned with the MNI brain. This isn't usually a problem, but I'm now considering coregistration of the data (but not spatial normalization) as a routine preprocessing step. Stay tuned.		One thing I will point out is that our FreeSurfer analyses are done in surface space, which doesn't care about where the particular voxels sit in relation to the cube of voxels surrounding the standard MNI template brain. For that reason, your structural and functional data will seldom be even close to aligned with the MNI brain. This isn't usually a problem, but I'm now considering coregistration of the data (but not spatial normalization) as a routine preprocessing step. Stay tuned.

	==Functional data==		==Functional data==
	This works pretty much the same as selecting your structural data. Following our FreeSurfer conventions, you will be working with the f.nii.gz data (the zipped data will be automatically unzipped). Make sure that these data have already had the first 4 volumes dropped and that the slice timing and TR information has already been fixed in the header (see the page on [[Freesurfer BOLD files]]).		This works pretty much the same as selecting your structural data. Following our FreeSurfer conventions, you will be working with the f.nii.gz data (the zipped data will be automatically unzipped). Make sure that these data have already had the first 4 volumes dropped and that the slice timing and TR information has already been fixed in the header (see the page on [[Freesurfer BOLD files]]).

Chris: /* Covariates (1st-level) */

2018-11-01T23:07:18Z

Covariates (1st-level)

← Older revision		Revision as of 19:07, 1 November 2018
Line 50:		Line 50:

	==Covariates (1st-level)==		==Covariates (1st-level)==
	This would be timeseries related covariates, like motion parameters or perhaps if you wanted to exclude the onsets of button presses based on the runtime RT data.		This would be timeseries related covariates, like motion parameters or perhaps if you wanted to exclude the onsets of button presses based on the runtime RT data. We can leave this blank unless we have a reason to get fancy.

	==Covariates (2nd level)==		==Covariates (2nd level)==

Chris: /* ROIs */

2018-11-01T23:05:58Z

ROIs

← Older revision		Revision as of 19:05, 1 November 2018
Line 40:		Line 40:

	==ROIs==		==ROIs==
	Here we indicate regional sources of variance that will be used to denoise our data. By default conn has selected Grey and White matter, CSF, atlas and networks. We wish to extract the average timeseries for the Grey matter, the Principle Component Analysis signal from White matter and CSF. We can remove the atlas and networks ROIs.		Here we indicate regional sources of variance that will be used to denoise our data. By default conn has selected Grey and White matter, CSF, atlas and networks. We wish to extract the average timeseries for the Grey matter, the Principle Component Analysis signal from White matter and CSF. We can remove the atlas and networks ROIs from the list of ROIs we care about so that we only have the first 3.

	There's a checkbox for regressing out covariates before regressing out the PCA noise covariates, but I don't see any reason to use that option.		There's a checkbox for regressing out covariates before regressing out the PCA noise covariates, but I don't see any reason to use that option.

Chris: /* Obtaining Denoised Time-Series Data */

2018-11-01T23:02:43Z

Obtaining Denoised Time-Series Data

← Older revision		Revision as of 19:02, 1 November 2018
Line 103:		Line 103:

	After you execute this command in MATLAB, you'll end up with a file with the same name, except with a .nii extension.		After you execute this command in MATLAB, you'll end up with a file with the same name, except with a .nii extension.
	Now, at this point, you probably started off with an f.nii.gz file, and now have a DATA_Subject'xxx'_Session'yyy'.nii file. In order to look at this newly denoised data in FreeSurfer, you will need to run it through the FS-FAST preproc-sess step. There's a good chance the source directory already has an f.nii.gz file, as well as a series of fmcpr.''${direction}.sm${smoothing}.fsaverage.?h.nii.gz files. Assuming you want to hold on to these, I'd make a backup directory in each of the run subdirectories, and move all files to the backup directory (you can keep any .par files here). After you've backed everything up, move the new denoised files into the appropriate directories and rename them to f.nii. When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:		Now, at this point, you probably started off with an f.nii.gz file, and now have a DATA_Subject'xxx'_Session'yyy'.nii file. In order to look at this newly denoised data in FreeSurfer, you will need to run it through the FS-FAST preproc-sess step. There's a good chance the source directory already has an f.nii.gz file, as well as a series of fmcpr.''${direction}''.sm''${smoothing}''.fsaverage.?h.nii.gz files. Assuming you want to hold on to these, I'd make a backup directory in each of the run subdirectories, and move all files to the backup directory (you can keep any .par files here). After you've backed everything up, move the new denoised files into the appropriate directories and rename them to f.nii. When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:

	preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold		preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold

	The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your later analysis or data processing scripts accordingly -- just be on the lookout for ''file not found'' errors, and if they pop up, the first thing you should look for is to see if your command or script was expecting a filename with the slice order). Of course, another option would be to manually rename the preprocessed data when preproc-sess is completed, so that the preprocessed denoised data still includes the sliceorder in the name. I'm not sure how big of a problem this minor change in filename is going to be for our various scripts.		The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your later analysis or data processing scripts accordingly -- just be on the lookout for ''file not found'' errors, and if they pop up, the first thing you should look for is to see if your command or script was expecting a filename with the slice order). Of course, another option would be to manually rename the preprocessed data when preproc-sess is completed, so that the preprocessed denoised data still includes the sliceorder in the name. I'm not sure how big of a problem this minor change in filename is going to be for our various scripts.

Chris: /* Obtaining Denoised Time-Series Data */

2018-11-01T23:01:44Z

Obtaining Denoised Time-Series Data

← Older revision		Revision as of 19:01, 1 November 2018
Line 107:		Line 107:
	preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold		preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold

	The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your scripts accordingly).		The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your later analysis or data processing scripts accordingly -- just be on the lookout for ''file not found'' errors, and if they pop up, the first thing you should look for is to see if your command or script was expecting a filename with the slice order). Of course, another option would be to manually rename the preprocessed data when preproc-sess is completed, so that the preprocessed denoised data still includes the sliceorder in the name. I'm not sure how big of a problem this minor change in filename is going to be for our various scripts.

Chris: /* Obtaining Denoised Time-Series Data */

2018-11-01T22:57:51Z

Obtaining Denoised Time-Series Data

← Older revision		Revision as of 18:57, 1 November 2018
Line 102:		Line 102:
	>> %the second parameter is optional and indicates whether to display a waitbar. By default, this is set to false.		>> %the second parameter is optional and indicates whether to display a waitbar. By default, this is set to false.

	After you execute this command in MATLAB, you'll end up with a file with the same name, except with a .nii extension.		After you execute this command in MATLAB, you'll end up with a file with the same name, except with a .nii extension.
			Now, at this point, you probably started off with an f.nii.gz file, and now have a DATA_Subject'xxx'_Session'yyy'.nii file. In order to look at this newly denoised data in FreeSurfer, you will need to run it through the FS-FAST preproc-sess step. There's a good chance the source directory already has an f.nii.gz file, as well as a series of fmcpr.''${direction}.sm${smoothing}.fsaverage.?h.nii.gz files. Assuming you want to hold on to these, I'd make a backup directory in each of the run subdirectories, and move all files to the backup directory (you can keep any .par files here). After you've backed everything up, move the new denoised files into the appropriate directories and rename them to f.nii. When you redo the preproc-sess step, make sure you do not apply slice-time correction, because this has already been applied to the denoised data:

			preproc-sess -s FS_0231 -per-run -surface fsaverage lhrh -mni305 -fwhm 4 -fsd bold

			The departure from the other wiki entry on preproc-sess is that we do not use the -sliceorder flag on the denoised data. Other than that, just process the denoised functional data like you would any other data. When done, you'll have a set of fmcpr.${smooth}.fsaverage.?h.nii.gz (they will no longer have the word 'down' in the filename, so you may have to modify some of your scripts accordingly).