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| ["selxavg3-sess"] sf <subjectfilename> df <srchdirfile> analysis <sem_assoc> [options] | [[selxavg3-sess]] sf <subjectfilename> df <srchdirfile> analysis <sem_assoc> [options] |
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| ||-analysis <analysisname> || name of functional analysis that you created under the analysis flag in ["mkanalysis-sess.gui"]|| | ||-analysis <analysisname> || name of functional analysis that you created under the analysis flag in [[mkanalysis-sess.gui]]|| |
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| ["selxavg3-sess"] computes the average signal intensity maps for each condition for each individual subject. This program separately analyzes the data in each session indicated in the sessid file, then computes the average signal intensity maps for each condition. This average data can be further processed on an individual basis and/or can be used for group analyses. This also compute contrasts for testing hypotheses based on a GeneralLinearModel (GLM), including t and F statistics, significances of those statistics, and contrast effects sizes (ces).This is the new version of stxgrinder, implicit intensity normalization, better whitening | [[selxavg3-sess]] computes the average signal intensity maps for each condition for each individual subject. This program separately analyzes the data in each session indicated in the sessid file, then computes the average signal intensity maps for each condition. This average data can be further processed on an individual basis and/or can be used for group analyses. This also compute contrasts for testing hypotheses based on a GeneralLinearModel (GLM), including t and F statistics, significances of those statistics, and contrast effects sizes (ces).This is the new version of stxgrinder, implicit intensity normalization, better whitening |
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| ["mkanalysis-sess.new"] | [[mkanalysis-sess.new]] |
Index
Contents
Name
Synopsis
selxavg3-sess sf <subjectfilename> df <srchdirfile> analysis <sem_assoc> [options]
Arguments
Required Arguments:
-analysis <analysisname> |
name of functional analysis that you created under the analysis flag in mkanalysis-sess.gui |
-sf <sessidfile> |
text file list of subjects |
-df <srchdirfile> |
text file list of directories where subjects can be found |
-d <srchdir> |
use instead of df if specifying only one dir |
Optional Arguments
-skip |
skip session of already analyzed |
-overwrite |
delete analysis if session of already analyzed |
-svres |
saves residuals (usually not needed) |
-perrun |
analyze each run separately |
-no-fwhm |
don't compute FWHM |
-float |
use single precision float instead of double |
-outparent dir |
save output to this dir instead of in session |
-version |
print version and exit |
Outputs
This will create a subdirectory with the same name as your analysisname under the bold directory in subjects directory. This folder has all of the results for this analysis, including:
- beta.nii - regression coefficients
- rvar.nii - residual error variance
- mask.nii - mask (copy of bold/masks/brain.nii)
- meanfunc.nii - mean functional image
- fsnr.nii - functional SNR map
- X.mat - design matrix (in matlab format)
- dof - text file with degrees of freedom
- fwhm.dat - text file with smoothness estimate (Full-Width/Half-Max)
- contrast folders:
- Each contrast folder contains:
- ces.nii - contrast effect size (contrast matrix * regression coef)
- cesvar.nii - variance of contrast effect size
- sig.nii - significance map (-log10(p))
- Each contrast folder contains:
Description
General Description
selxavg3-sess computes the average signal intensity maps for each condition for each individual subject. This program separately analyzes the data in each session indicated in the sessid file, then computes the average signal intensity maps for each condition. This average data can be further processed on an individual basis and/or can be used for group analyses. This also compute contrasts for testing hypotheses based on a GeneralLinearModel (GLM), including t and F statistics, significances of those statistics, and contrast effects sizes (ces).This is the new version of stxgrinder, implicit intensity normalization, better whitening
Bugs
none
See Also
Links
Methods Description
??
References
none
Reporting Bugs
Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>