Importing data from EEG devices¶
MNE includes various functions and utilities for reading EEG data and electrode locations.
The BrainVision file format consists of three separate files:
A text header file (
.vhdr) containing meta data
A text marker file (
.vmrk) containing information about events in the data
A binary data file (
.eeg) containing the voltage values of the EEG
Both text files are based on the Microsoft Windows INI format consisting of:
sections marked as
comments marked as
key-value pairs marked as
A documentation for core BrainVision file format is provided by Brain Products. You can view the specification hosted on the Brain Products website
BrainVision EEG files can be read in using
.vhdr header file as an input.
Renaming BrainVision files can be problematic due to their multifile structure. See this example for an instruction.
For writing BrainVision files, you can use the Python package pybv.
EDF and EDF+ files can be read using
The EDF+ files may contain an annotation channel which can be used to store
trigger information. These annotations are available in
Saving EDF files is not supported natively yet. This gist can be used to save any mne.io.Raw into EDF/EDF+/BDF/BDF+.
BioSemi amplifiers do not perform “common mode noise rejection” automatically. The signals in the EEG file are the voltages between each electrode and CMS active electrode, which still contain some CM noise (50 Hz, ADC reference noise, etc., see the BioSemi FAQ for further detail). Thus, it is advisable to choose a reference (e.g., a single channel like Cz, average of linked mastoids, average of all electrodes, etc.) on import of BioSemi data to avoid losing signal information. The data can be re-referenced later after cleaning if desired.
The data samples in a BDF file are represented in a 3-byte (24-bit) format. Since 3-byte raw data buffers are not presently supported in the fif format these data will be changed to 4-byte integers in the conversion.
GDF files can be read in using
GDF (General Data Format) is a flexible format for biomedical signals that overcomes some of the limitations of the EDF format. The original specification (GDF v1) includes a binary header and uses an event table. An updated specification (GDF v2) was released in 2011 and adds fields for additional subject-specific information (gender, age, etc.) and allows storing several physical units and other properties. Both specifications are supported in MNE.
CNT files can be read in using
The channel locations can be read from a montage or the file header. If read
from the header, the data channels (channels that are not assigned to EOG, ECG,
EMG or misc) are fit to a sphere and assigned a z-value accordingly. If a
non-data channel does not fit to the sphere, it is assigned a z-value of 0.
Reading channel locations from the file header may be dangerous, as the x_coord and y_coord in ELECTLOC section of the header do not necessarily translate to absolute locations. Furthermore, EEG-electrode locations that do not fit to a sphere will distort the layout when computing the z-values. If you are not sure about the channel locations in the header, use of a montage is encouraged.
EGI simple binary files can be read in using
The EGI raw files are simple binary files with a header and can be exported
from using the EGI Netstation acquisition software.
EEG data from the Nexstim eXimia system can be read in using the
The preferred method for applying an EEG reference in MNE is
mne.set_eeg_reference(), or equivalent instance methods like
raw.set_eeg_reference(). By default,
the data are assumed to already be properly referenced. See
Setting the EEG reference for more information.
Some EEG formats (EGI, EDF/EDF+, BDF) neither contain electrode location
information nor head shape digitization information. Therefore, this
information has to be provided separately. For that purpose all raw instances
mne.io.Raw.set_montage() method to set electrode locations.
When using the locations of the fiducial points the digitization data are converted to the MEG head coordinate system employed in the MNE software, see MEG/EEG and MRI coordinate systems.
Estimated memory usage: 8 MB