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resources afni
Under construction. A description of afni resources.
The sub-package afni contains a number of modules:
- copy
- deconvolve
- group
- masks
- motion
- process
- submit
These modules are organized, largely, according to the type of work performed. That is, any functions that deal with mask generation are located in the module masks. Together, these modules are capable of conducting resting state and task-based analyses.
copy contains a single function, copy_data. It is the role of this module to (a) copy structural, functional, and motion files needed by AFNI, and (b) to start and populate the afni_data dictionary that will be used to pass files to various modules.
The `deconvolve module currently contains four functions used for preparing and conducting deconvolutions of the EPI time series:
- write_decon
- run_reml
- timing_files
- regress_resting
write_decon constructs a 3dDeconvolve command that incorporates censor files, motion (mean and derivative) baseline regressors, and task timing files for the various pre-processed (scaled) EPI runs.
Currently, only a two gamma basis function is supported, AFNI is allowed to determine the number of polynomial regressors (using local times), and output names follow traditional AFNI formatting. The AFNI naming convention is due to the fact that 3dDeconvolve is employed to generate (a) the deconvolution matrices and (b) the 3dREMLfit command.
The generated 3dDeconvolve command is saved to a script in the subject's func directory, for review, and then the command is executed in order to generate the files listed above.
run_reml has two parts. First, a white matter time series is constructed from an eroded white matter mask. Then the foo.REML_cmd generated by write_decon is executed with the addition of the white matter time series as a nuissance regressor.
The timing_files function is specific to the EMU project, but could easily be updated for other projects. When user-specified timing files/deconvolution are supplied, the timing_files module is not used. timing_files will orient to the foo_events.tsv BIDS files that accompany each EPI run in func. From these events file all unique behaviors will be identified (ref. "trial_type"). These unique behaviors will then be used to construct AFNI-styeld timing files using onset times only, with the asterisk "*" holding for runs in which a certain behavior does not occur.
The decon_plan nested dictionary is constructed by the timing_files module, where the parent key is the deconvolution name, child key is the behavior (<8 characters!), and value is the path to the timing file. The behavior name is embedded in the file name as a description. For example:
{
"UniqueBehs": {
"behA": "/path/to/foo_desc-behA_events.1D",
"behB": "/path/to/foo_desc-behB_events.1D",
"behC": "/path/to/foo_desc-behC_events.1D",
}
}
With the decon_plan above, an output file "decon_task-foo_UniqueBehs_stats_REML+tlrc" will be generated by modeling three behaviors, behA-C, and "behA" etc will be used to label the sub-brick of the deconvolved file for the coefficients and test statistics.