- mne.stc_near_sensors(evoked, trans, subject, distance=0.01, mode='sum', project=True, subjects_dir=None, src=None, picks=None, surface='pial', verbose=None)[source]#
Create a STC from ECoG, sEEG and DBS sensor data.
- evokedinstance of
The evoked data. Must contain ECoG, sEEG or DBS channels.
- transpath-like |
dict| instance of
If str, the path to the head<->MRI transform
*-trans.fiffile produced during coregistration. Can also be
'fsaverage'to use the built-in fsaverage transformation. If trans is None, an identity matrix is assumed.
Changed in version 0.19: Support for ‘fsaverage’ argument.
The subject name.
Distance (m) defining the activation “ball” of the sensor.
Can be “sum” to do a linear sum of weights, “weighted” to make this a weighted sum, “nearest” to use only the weight of the nearest sensor, or “single” to do a distance-weight of the nearest sensor. Default is “sum”. See Notes.
Changed in version 0.24: Added “weighted” option.
If True, project the sensors to the nearest
'pialsurface vertex before computing distances. Only used when doing a surface projection.
- subjects_dirpath-like |
The path to the directory containing the FreeSurfer subjects reconstructions. If
None, defaults to the
- srcinstance of
The source space.
If a surface source space is used, make sure that
surface='pial'was used during construction, or that you set
str| array_like |
Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g.,
['meg', 'eeg']) will pick channels of those types, channel name strings (e.g.,
['MEG0111', 'MEG2623']will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick good sEEG, ECoG, and DBS channels.
New in version 0.24.
The surface to use if
src=None. Default is the pial surface. If None, the source space surface will be used.
New in version 0.24.1.
Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation and
mne.verbose()for details. Should only be passed as a keyword argument.
- evokedinstance of
- stcinstance of
The surface source estimate. If src is None, a surface source estimate will be produced, and the number of vertices will equal the number of pial-surface vertices that were close enough to the sensors to take on a non-zero volue. If src is not None, a surface, volume, or mixed source estimate will be produced (depending on the kind of source space passed) and the vertices will match those of src (i.e., there may be me many all-zero values in stc.data).
- stcinstance of
For surface projections, this function projects the ECoG sensors to the pial surface (if
project), then the activation at each pial surface vertex is given by the mode:
Activation is the sum across each sensor weighted by the fractional
distancefrom each sensor. A sensor with zero distance gets weight 1 and a sensor at
distancemeters away (or larger) gets weight 0. If
distanceis less than half the distance between any two sensors, this will be the same as
'sum'except that only the nearest sensor is used, rather than summing across sensors within the
'nearest'for vertices with distance zero to the projected sensor.
The value is given by the value of the nearest sensor, up to a
distance(beyond which it is zero).
The value is given by the same as
sumbut the total weight for each vertex is 1. (i.e., it’s a weighted sum based on proximity).
If creating a Volume STC,
srcmust be passed in, and this function will project sEEG and DBS sensors to nearby surrounding vertices. Then the activation at each volume vertex is given by the mode in the same way as ECoG surface projections.
New in version 0.22.