Hi, Maya-
Hmm, that is surprising. What is the output of:
afni_system_check.py -check_all
?
Also note that the combine_method you are using, "tedana" is the older one from Kundu et al; that doesn't have a separate QC HTML block that is automatically created for the MEICA part. The newer MEICA from the 'tedana' group (Du Pre et al; here: [
tedana.readthedocs.io]) would be selected with "m_tedana". Note that the Kundu et al tedana can only run in Python 2.7; the developer of it doesn't update/maintain it. The Du Pre et al. version requires Python 3.*.
Part of the help in afni_proc.py relevant to this choice (there are a loooot of combine_method opts) is:
-combine_method METHOD : specify method for combining echoes
e.g. -combine_method OC
default: OC
When using the 'combine' block to combine echoes (for each run),
this option can be used to specify the method used. There are:
- basic methods
- methods using tedana.py (or similar) from Prantik
- methods using tedana from the MEICA group
---- basic combine methods (that do not use any tedana) ----
methods
-------
mean : simple mean of echoes
OC : optimally combined (via @compute_OC_weights)
(current default is OC_A)
OC_A : original log(mean()) regression method
OC_B : newer log() time series regression method
(there is little difference between OC_A
and OC_B)
---- combine methods that use Prantik's "original" tedana.py ----
Prantik's tedana.py is run using the 'tedana*' combine methods.
Prantik's tedana.py requires python 2.7.
By default, tedana.py will be applied from the AFNI
installation directory.
Alternatively, one can specify the location of a different
tedana.py using -combine_tedana_path. And if it is
preferable to run it as an executable (as opposed to running
it via 'python PATH/TO/tedana.py'), one can tell this to
tedana_wrapper.py by applying:
-combine_opts_tedwrap -tedana_is_exec
methods
-------
OC_tedort : OC, and pass tedana orts to regression
tedana : run tedana.py, using output dn_ts_OC.nii
tedana_OC : run tedana.py, using output ts_OC.nii
(i.e. use tedana.py for optimally combined)
tedana_OC_tedort : tedana_OC, and include tedana orts
---- combine methods that use tedana from the MEICA group ----
The MEICA group tedana is specified with 'm_tedana*' methods.
This tedana requires python 3.6+.
AFNI does not distribute this version of tedana, so it must
be in the PATH. For installation details, please see:
[tedana.readthedocs.io]
methods
-------
m_tedana : tedana from MEICA group (dn_ts_OC.nii.gz)
m_tedana_OC : tedana OC from MEICA group (ts_OC.nii.gz)
m_tedana_m_tedort: tedana from MEICA group (dn_ts_OC.nii.gz)
"tedort" from MEICA group
(--tedort: "good" projected from "bad")
The OC/OC_A combine method is from Posse et. al., 1999, and then
applied by Kundu et. al., 2011 and presented by Javier in a 2017
summer course.
The 'tedort' methods for Prantik's tedana.py are applied using
@extract_meica_ortvec, which projects the 'good' MEICA components
out of the 'bad' ones, and saves those as regressors to be applied
later. Otherwise, some of the 'good' components are removed with
the 'bad. The tedort method can be applied with either AFNI OC or
tedana OC (meaning the respective OC method would be applied to
combine the echoes, and the tedort components will be passed on to
the regress block).
The 'm_tedanam_m_tedort' method for the MEICA group's passes
option --tedort to 'tedana', and tedana does the "good" from "bad"
projection before projecting the modified "bad" components from the
time series.
Please see '@compute_OC_weights -help' for more information.
Please see '@extract_meica_ortvec -help' for more information.
See also -combine_tedana_path.
--pt
