group.multimorph.agg.native: Aggregate native space morphometry data for multiple measures...

In fsbrain: Managing and Visualizing Brain Surface Data

Aggregate native space morphometry data for multiple measures over hemispheres for a group of subjects.

Description

Compute the mean (or other aggregates) over all vertices of a subject from native space morphometry data (like 'surf/lh.area'). You can specify several measures and hemispheres. Uses knowledge about the FreeSurfer directory structure to load the correct files.

Usage

group.multimorph.agg.native(
  subjects_dir,
  subjects_list,
  measures,
  hemis,
  agg_fun = mean,
  format = "curv",
  cast = TRUE,
  cortex_only = FALSE,
  agg_fun_extra_params = NULL
)

Arguments

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.
measures	vector of strings. Names of the vertex-wise morphometry measures. E.g., c("area", "thickness"). Used to construct the names of the morphometry file to be loaded.
hemis	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.
agg_fun	function. An R function that aggregates data, typically max, mean, min or something similar. Note: this is NOT a string, put the function name without quotes. Defaults to mean.
format	string. One of 'mgh', 'mgz', 'curv'. Defaults to 'mgh'.
cast	Whether a separate 'hemi' column should exist.
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 mean function, you could set agg_fun_extra_params=list("na.rm"=TRUE) to get the mean of the vertices which are not masked. Defaults to FALSE.
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.

Value

dataframe with aggregated values over all measures and hemis for all subjects, with m columns and n rows, where n is the number of subjects. The m columns are 'subject_id' and '<hemi>.<measure>' (e.g., "lh.thickness") for all combinations of hemi and measure, the latter contains the aggregated data.

See Also

Other global aggregation functions: group.morph.agg.native(), group.morph.agg.standard(), group.multimorph.agg.standard()

Examples

## Not run: 
    subjects_dir = fsbrain::get_optional_data_filepath("subjects_dir");
    subjects_list = c("subject1", "subject2")
    data = group.multimorph.agg.native(subjects_dir, subjects_list, c("thickness", "area"),
     c("lh", "rh"), cast=FALSE, cortex_only=TRUE, agg_fun=mean,
     agg_fun_extra_params=list("na.rm"=TRUE));
    head(data);

## End(Not run)

fsbrain documentation built on Aug. 23, 2026, 5:06 p.m.