mne.io.read_raw_brainvision#
- mne.io.read_raw_brainvision(vhdr_fname, eog=('HEOGL', 'HEOGR', 'VEOGb'), misc='auto', scale=1.0, ignore_marker_types=False, preload=False, verbose=None) RawBrainVision [source]#
Reader for Brain Vision EEG file.
- Parameters:
- vhdr_fnamepath-like
Path to the EEG header file.
- eog
list
ortuple
ofstr
Names of channels or list of indices that should be designated EOG channels. Values should correspond to the header file Default is
('HEOGL', 'HEOGR', 'VEOGb')
.- misc
list
ortuple
ofstr
|'auto'
Names of channels or list of indices that should be designated MISC channels. Values should correspond to the electrodes in the header file. If
'auto'
, units in header file are used for inferring misc channels. Default is'auto'
.- scale
float
The scaling factor for EEG data. Unless specified otherwise by header file, units are in microvolts. Default scale factor is 1.
- ignore_marker_typesbool
If
True
, ignore marker types and only use marker descriptions. Default isFalse
.- preloadbool or
str
(defaultFalse
) Preload data into memory for data manipulation and faster indexing. If True, the data will be preloaded into memory (fast, requires large amount of memory). If preload is a string, preload is the file name of a memory-mapped file which is used to store the data on the hard drive (slower, requires less memory).
- verbosebool |
str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- Returns:
- rawinstance of
RawBrainVision
A Raw object containing BrainVision data. See
mne.io.Raw
for documentation of attributes and methods.
- rawinstance of
See also
mne.io.Raw
Documentation of attributes and methods of RawBrainVision.
Notes
If the BrainVision header file contains impedance measurements, these may be accessed using
raw.impedances
after reading using this function. However, this attribute will NOT be available after a save and re-load of the data. That is, it is only available when reading data directly from the BrainVision header file.BrainVision markers consist of a type and a description (in addition to other fields like onset and duration). In contrast, annotations in MNE only have a description. Therefore, a BrainVision marker of type “Stimulus” and description “S 1” will be converted to an annotation “Stimulus/S 1” by default. If you want to ignore the type and instead only use the description, set
ignore_marker_types=True
, which will convert the same marker to an annotation “S 1”.
Examples using mne.io.read_raw_brainvision
#
Importing data from EEG devices
Frequency-tagging: Basic analysis of an SSVEP/vSSR dataset