This S4 class represents a four-dimensional brain image, which is used to store
and process time series neuroimaging data such as fMRI or 4D functional
connectivity maps. The class extends the basic functionality of NeuroObj.
The NeuroVec class represents a vectorized form of neuroimaging data, supporting both in-memory
and file-backed data modes. It provides efficient data storage and access methods and integrates with
the spatial reference system provided by NeuroSpace.
Arguments
- data
The image data. This can be:
A matrix (voxels x time points)
A 4D array
A list of
NeuroVolobjects
If a list of NeuroVol objects is provided, the geometric space (
NeuroSpace) will be inferred from the constituent volumes, which must all be identical.- space
An optional
NeuroSpaceobject defining the spatial properties of the image. Not required ifdatais a list of NeuroVol objects.- mask
An optional logical array specifying which voxels to include. If provided, a SparseNeuroVec object will be created.
- label
A character string providing a label for the NeuroVec object. Default is an empty string.
Value
A concrete instance of the NeuroVec class:
If
maskis provided: aSparseNeuroVecobjectOtherwise: a
DenseNeuroVecobject
Details
NeuroVec objects are designed to handle 4D neuroimaging data, where the first three dimensions represent spatial coordinates, and the fourth dimension typically represents time or another series dimension. This structure is particularly useful for storing and analyzing functional MRI data, time series of brain states, or multiple 3D volumes in a single object.
The function performs several operations:
If
datais a list of NeuroVol objects, it combines them into a single 4D array.It checks that the dimensions of
datamatch the providedspace.Depending on whether a
maskis provided, it creates either a DenseNeuroVec or a SparseNeuroVec object.
Slots
- space
A
NeuroSpaceobject defining the spatial properties of the image.- label
A character string providing a label for the NeuroVec object.
Methods
Methods specific to NeuroVec objects may include operations for time series analysis, 4D data manipulation, and extraction of 3D volumes or time courses.
Usage
To create a NeuroVec object, use the constructor function NeuroVec().
This function should handle the appropriate initialization of the 4D data
structure and associated spatial information.
See also
NeuroObj-class for the parent class.
DenseNeuroVec-class and SparseNeuroVec-class for specific implementations.
NeuroSpace for spatial information,
sub_vector for subsetting routines, and
index_to_coord for coordinate conversion.
DenseNeuroVec-class, SparseNeuroVec-class for the
specific NeuroVec types.
NeuroVol-class for 3D volumetric data.