23.04.2025
UNLOCKING DEEPER INSIGHTS: The Power of Combining EEG and Eye Tracking in Research
by Mirta Ivanek, Product Manager
Understanding human cognition requires more than just isolated measurements of brain activity or visual attention. To truly capture the complexities of perception, decision-making, and cognitive load, researchers are increasingly turning to multimodal approaches. Among the most powerful combinations is electroencephalography (EEG) and eye tracking – two complementary technologies that, when integrated, offer unparalleled insights into the intricate relationship between where we look and how our brain processes information.
In this post, we explore why EEG and eye tracking are a natural fit, how their combination enhances research, and the technical considerations that come with integrating these technologies.
The Science Behind EEG and Eye Tracking
EEG is a non-invasive method that records electrical activity in the brain through electrodes placed on the scalp. With its high temporal resolution, EEG captures rapid neural responses, making it an essential tool for studying cognitive functions such as attention, memory, and decision-making.
Eye tracking, on the other hand, monitors gaze direction, pupil dilation, and saccadic movements using specialized cameras. It provides precise information on where, when, and for how long an individual fixates on specific stimuli, making it invaluable for understanding visual attention and engagement.
Individually, both technologies offer deep insights into cognition. Together, they bridge the gap between attention and brain activity, providing a holistic view of human thought processes.
Why Combine EEG and Eye Tracking?
While EEG and eye tracking are powerful tools on their own, integrating them enhances research in several key areas:
- Contextualizing brain activity: EEG data alone can indicate cognitive states, but it does not reveal what external stimuli triggered those states. Eye tracking fills this gap by pinpointing where a participant is looking at any given moment, allowing researchers to correlate brain responses with visual input.
- Understanding attention and cognitive load: Eye tracking tells us where someone is looking, but not how their brain processes what they see. EEG provides this missing piece by measuring neural activity in response to visual stimuli, offering deeper insights into cognitive load and attentional processes.
- Improving decision-making analysis: In fields such as marketing research, usability testing, and psychology, EEG-eye tracking integration helps uncover not just what captures attention but also how the brain reacts to it. This leads to richer data on consumer behavior, learning processes, and human-computer interaction.
- Enhancing emotional and cognitive state measurements: Combining EEG and eye tracking allows researchers to distinguish between states such as interest, confusion, and fatigue with greater accuracy. This is particularly useful in education research, where student engagement can be analyzed to improve teaching methods.
Application Across Disciplines
The combination of EEG and eye tracking is being utilized across multiple research fields:
- Neuroscience & Cognitive Psychology1: Researchers can study how visual attention translates to brain activity, gaining insights into perception, decision-making, and cognitive processing.
- Marketing & Consumer Behavior2: Businesses can evaluate how advertisements, product packaging, and digital content engage consumers, identifying what captures attention and elicits emotional responses.
- Education & Learning3: Eye tracking and EEG help researchers understand how students interact with digital learning materials, leading to improved instructional design.
- Human-Computer Interaction (HCI)4: UX designers assess how users engage with digital interfaces, improving accessibility and usability by analyzing gaze behavior and cognitive effort.
- Medical & Clinical Research5: This combination is used to study neurological disorders, assess cognitive impairments, and develop brain-computer interface (BCI) applications for patients with disabilities.
Key Methodological Considerations
While integrating EEG and eye tracking offers significant advantages, researchers must account for several methodological challenges:
- Synchronization6: Aligning EEG and eye tracking data with millisecond precision is critical. Many modern systems include software that synchronizes these data streams for accurate analysis.
- Artifact Management7: Eye movements, particularly blinks, can introduce artifacts in EEG recordings. Robust preprocessing techniques are necessary to distinguish meaningful neural signals from noise.
- Stimulus Design6,8: To elicit reliable gaze and neural responses, experimental stimuli should be carefully designed to maintain participant engagement and minimize confounding factors.
The Future of EEG and Eye Tracking Research
The integration of EEG and eye tracking is revolutionizing research across multiple disciplines. By simultaneously capturing „where“ a person looks and „why“ their brain reacts in a particular way, this multimodal approach provides richer, more comprehensive insights into human cognition and behavior. As technology continues to advance, we can expect even greater precision, automation, and real-time analysis capabilities, opening new frontiers in neuroscience, psychology, HCI, and beyond.
Are you interested in leveraging EEG and eye tracking for your research? Contact us to learn how these powerful tools can enhance your studies.
1
Plöchl, M., Ossandon, J.P., & König, P. (2012). Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data. Front. Hum. Neurosci., doi: 10.3389/fnhum.2012.00278
2
Pšurný, M., Mokrý, S., & Stavkova, J. (2024). Exploring consumers ‘perceptions of online purchase decision factors: electroencephalography and eye-tracking evidence. Front. Hum. Neurosci., doi: 10.3389/fnhum.2024.1411685
3
Keskin, M., Ooms, K., Dogru, A. O., & De Maeyer, P. (2020). Exploring the Cognitive Load of Expert and Novice Map Users Using EEG and Eye Tracking. ISPRS International Journal of Geo-Information, doi: 10.3390/ijgi9070429
4
Zhu, L., & Lv, J. (2023). Review of Studies on User Research Based on EEG and Eye Tracking. Appl. Sci., doi: 10.3390/app13116502
5
Christoforou, C., Fella, A., Leppänen, P.H.T., Georgiou, G.K., & Papadopoulos, T.C. (2021). Fixation-related potentials in naming speed: A combined EEG and eye-tracking study on children with dyslexia. Clin Neurophysiol., doi:10.1016/j.clinph.2021.08.013.
6
Dimigen, O., & Ehinger, B.V. (2021). Regression-based analysis of combined EEG and eye-tracking data: Theory and applications. J Vis., doi:10.1167/jov.21.1.3
7
Plöchl, M., Ossandon, J.P., & König, P. (2012). Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data. Front. Hum. Neurosci., doi: 10.3389/fnhum.2012.00278
8
Brouwer, A.-M., Hogervorst, M.A., Oudejans, B., Ries, A.J., & Touryan, J. (2017). EEG and Eye Tracking Signatures of Target Encoding during Structured Visual Search. Front. Hum. Neurosci., doi:10.3389/fnhum.2017.00264