group.morph.agg.standard.vertex | R Documentation |
Aggregate vertex-wise values over subjects, leading to one aggregated measure per vertex.
group.morph.agg.standard.vertex(
subjects_dir,
subjects_list,
measure,
hemi,
fwhm,
agg_fun = mean,
template_subject = "fsaverage",
format = "mgh",
cortex_only = FALSE,
agg_fun_extra_params = NULL,
split_by_hemi = FALSE
)
subjects_dir |
string. The FreeSurfer SUBJECTS_DIR, i.e., a directory containing the data for all your subjects, each in a subdir named after the subject identifier. |
subjects_list |
string vector. A vector of subject identifiers that match the directory names within subjects_dir. |
measure |
string. Name of the vertex-wise measure of morphometry data file. E.g., "area" or "thickness". Used to construct the name of the morphometry file to be loaded. |
hemi |
string, one of 'lh', 'rh' or 'both'. The hemisphere name. Used to construct the names of the annotation and morphometry data files to be loaded. |
fwhm |
string. Smoothing as string, e.g. '10' or '25'. |
agg_fun |
function. An R function that aggregates data, typically |
template_subject |
string. Template subject name, defaults to 'fsaverage'. |
format |
string. One of 'mgh', 'mgz', 'curv'. Defaults to 'mgh'. |
cortex_only |
logical, whether to mask the medial wall, i.e., whether the morphometry data for all vertices which are *not* part of the cortex (as defined by the label file ‘label/?h.cortex.label') should be replaced with NA values. In other words, setting this to TRUE will ignore the values of the medial wall between the two hemispheres. If set to true, the mentioned label file needs to exist for the subjects. Also not that the aggregation function will need to be able to cope with NA values if you set this to TRUE. You can use ’agg_fun_extra_params' if needed to achieve that, depending on the function. Foe example, if you use the |
agg_fun_extra_params |
named list, extra parameters to pass to the aggregation function 'agg_fun' besides the loaded morphometry data. This is useful if you have masked the data and need to ignore NA values in the agg_fun. |
split_by_hemi |
logical, whether to return a hemilist |
Other aggregation functions:
group.agg.atlas.native()
,
group.agg.atlas.standard()
,
subject.atlas.agg()
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