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

Reader for Brain Vision EEG file.

Parameters:

vhdr_fnamepath-like

Path to the EEG header file.

eoglist or tuple of str

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').

misclist or tuple of str | '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'.

scalefloat

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 is False.

preloadbool or str (default False)

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 and mne.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.

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

Working with sensor locations

Working with sensor locations

Importing data from EEG devices

Importing data from EEG devices

Frequency-tagging: Basic analysis of an SSVEP/vSSR dataset

Frequency-tagging: Basic analysis of an SSVEP/vSSR dataset