Create a STC from ECoG, sEEG and DBS sensor data.
Evoked
The evoked data. Must contain ECoG, sEEG or DBS channels.
dict
| instance of Transform
| None
If str, the path to the head<->MRI transform *-trans.fif
file 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.
str
The subject name.
float
Distance (m) defining the activation “ball” of the sensor.
str
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 'pial
surface
vertex before computing distances. Only used when doing a
surface projection.
None
The path to the directory containing the FreeSurfer subjects
reconstructions. If None
, defaults to the SUBJECTS_DIR
environment
variable.
SourceSpaces
The source space.
Warning
If a surface source space is used, make sure that
surface='pial'
was used during construction,
or that you set surface='pial'
here.
str
| list
| slice
| None
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.
str
| None
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.
str
| int
| None
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.
SourceEstimate
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).
Notes
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:
'sum'
Activation is the sum across each sensor weighted by the fractional
distance
from each sensor. A sensor with zero distance gets weight
1 and a sensor at distance
meters away (or larger) gets weight 0.
If distance
is less than half the distance between any two
sensors, this will be the same as 'single'
.
'single'
Same as 'sum'
except that only the nearest sensor is used,
rather than summing across sensors within the distance
radius.
As 'nearest'
for vertices with distance zero to the projected
sensor.
'nearest'
The value is given by the value of the nearest sensor, up to a
distance
(beyond which it is zero).
'weighted'
The value is given by the same as sum
but the total weight for
each vertex is 1. (i.e., it’s a weighted sum based on proximity).
If creating a Volume STC, src
must 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.
mne.stc_near_sensors
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