The EYE-EEG toolbox allows researchers to synchronize and integrate eye-tracking and EEG data, detect eye movements and correct for ocular artifacts. However, analyses of the EEG during free viewing also require users
to deal with two additional analysis problems: The temporal overlap between the neural responses produced by each eye fixation (which often differs systematically between conditions) and the fact that many low-level properties of the eye movement and the viewed
stimulus also strongly modulate this neural response. Fortunately, EYE-EEG now has a new "sister" toolbox that elegantly deals with both problems: unfold, a toolbox for (non)linear deconvolution modelling that is fully compatible with EYE-EEG and can directly read EYE-EEG datasets for further processing.
The EYE-EEG toolbox is an extension for the open-source MATLAB toolbox EEGLAB developed to facilitate integrated analyses of electrophysiological
and oculomotor data . The toolbox parses, imports, and synchronizes simultaneously recorded eye tracking data and adds it as extra channels to the EEG.
Saccades and fixations can be imported from the eye tracking raw data or detected with an adaptive velocity-based algorithm .
Eye movements are then added as new time-locking events to EEGLAB's event structure, allowing easy saccade- and fixation-related EEG analysis (e.g., fixation-related potentials, FRPs).
Alternatively, EEG data can be aligned to stimulus onsets and analyzed according to oculomotor behavior (e.g. pupil size, microsaccades) in a given trial.
Saccade-related ICA components can be objectively identified based on their covariance with the electrically independent eye tracker .
EYE-EEG adds a top-level menu called Eyetracker to EEGLAB. All functions can be accessed via this menu and are
saved in EEGLAB's command history. Alternatively, functions can be called from the command line, providing advanced
users with the option to use them in custom scripts. Using EEGLAB's export functions, integrated datasets may also be
exported to other free toolboxes like Fieldtrip or Brainstorm.
Everyday vision is an active process that involves making several saccades per second. In contrast, most EEG data is recorded during prolonged visual fixation.
An alternative approach to signal analysis (for an overview see ), is to time-lock the EEG not to passive stimulus presentations, but to the
on- or offsets of saccadic eye movements in more natural viewing situations (yielding saccade- and fixation-related potentials, SRPs/FRPs).
However, recording precise eye movements together with the EEG is also useful for many other purposes. These include controlling fixation, detecting signal distortions from
microsaccades (e.g., ), improving ocular artifact correction [1, 3], measuring saccadic reaction times,
presenting stimuli gaze-contingently [5, 6], simultaneous pupillometry, or improving brain-computer interfaces.
Overview over functions
parse raw eye tracking data, store it in MATLAB format
Import & synchronize
synchronize eye track & EEG data based on common events
add gaze position & pupil size as extra channels
import saccades/fixations/blinks detected online by the eye tracker
Reject data based on eye position
remove continuous or epoched data with out-of-range values in eye track
control fixation, objectively reject blink artifacts
Apply functions to selected channels
apply existing EEGLAB functions (e.g. filters) only to EEG or eye track
Detect saccades & fixations
velocity-based (micro)saccade detection with relative thresholds (Engbert & Mergenthaler, 2006)
add saccades & fixations as time-locking events to EEG.event
plot eye movement properties
Improve ICA and classify independent components
create "optimized" ICA training data (with overweighted spike potentials) for better artifact correction (Dimigen, 2018)
automatically reject ocular ICs that covary with the electrically independent eye track
use variance ratio criterion proposed by Plöchl et al. (2012)
Eye-movement related potentials
analyze fixation-related potentials (FRPs) in time or frequency domain
directly relate EEG and oculomotor behavior (e.g., pupil size)
Currently, the toolbox reads text-converted raw data from eye trackers by SR Research
(e.g., EyeLink™-series), Sensomotoric Instruments (e.g., iView X™ and RED™-series) and Tobii Pro (e.g. Tobii Pro TX-300 or Pro Spectrum). If EEG and eye track are already synchronized (see Tutorial:
How to connect eye tracker & EEG), the toolbox can also be used to further process
data recorded with other eye tracking hardware. There are no known limitations regarding EEG hardware, since EEGLAB imports most EEG formats.
Download & Installation
Disclaimer: The current version of the EYE-EEG toolbox is version 0.85 (i.e. Beta).
Not all functions of future releases are guaranteed to be backwards compatible with this version and function inputs and data
formats may undergo some changes and improvements in future version, meaning that you may have to slightly update your scripts if a future
version comes out. Versions following 1.00 will be guaranteed backwards compatibility.
This is free software distributed under the GNU General Public License.
However, we do ask those who use this program or adapt its functions to cite it in their work. Please refer to it as the "EYE-EEG toolbox" (or "EYE-EEG extension") and cite reference  below.
Please also include the URL of this website (www2.hu-berlin.de/eyetracking-eeg) if possible. If you use the saccade detection, please additionally cite reference  (note that EYE-EEG contains modifications and additional options for the saccade detection procedures, which go beyond those proposed in the original paper. It is therefore helpful if you clarify that you have used the implementations of these methods in EYE-EEG).
If you select independent components based on the variance ratio criterion, please make sure to cite references  and . The reference for the optimized ICA (OPTICAT), is reference 
For bug reports, feature requests, and all other feedback please email us.
We'd be happy to hear of any papers you have written or insights you have gained using EYE-EEG.
We also welcome any collaboration in improving the tools, adding features, or supporting additional eye trackers.
The initial development of this software was made possible by a German Research Foundation grant to DFG Research Group 868, project A2: The timeline of word recognition and oculomotor control in reading.
Project publications using combined eye tracking and EEG can be found here.
Dimigen, O., Sommer, W., Hohlfeld, A., Jacobs, A., & Kliegl, R. (2011). Coregistration of eye movements and EEG in natural reading:
Analyses & Review. Journal of Experimenta Psychology: General, 140 (4), 552-572 [toolbox reference paper, PDF]
Engbert, R., & Mergenthaler, K. (2006). Microsaccades are triggered by low retinal image slip. PNAS, 103 (18), 7192-7197
Plöchl, M., Ossandon, J.P., & König, P. (2012). Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data. Frontiers in Human Neuroscience, doi: 10.3389/fnhum.2012.00278
Dimigen, O., Valsecchi, M., Sommer, W., & Kliegl, R. (2009). Human microsaccade-related visual brain responses. J Neurosci, 29, 12321-31
Dimigen, O., Kliegl, R., & Sommer, W. (2012). Trans-saccadic parafoveal preview benefits in fluent reading: a study with fixation-related brain potentials. Neuroimage, 62 (1), 381-393
Kornrumpf, B., Niefind, F., Sommer, W., & Dimigen, O. (2016). Neural correlates of word recognition: A systematic comparison of natural reading and RSVP. Journal of Cognitive Neuroscience, 28:9, 1374-1391
Dimigen, O. (2018). Optimized ICA-based removal of ocular EEG artifacts from free viewing experiments. BioRxiv doi: 10.1101/446955
Total downloads via this website (since Jan 2013, downloads via the EEGLAB extension manager are not counted):