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Simultaneous EEG and eye-movement recording in a visual scanning task

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Flad,  N
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83861

Chuang,  LL
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Flad, N., Bülthoff, H., & Chuang, L. (2015). Simultaneous EEG and eye-movement recording in a visual scanning task. Poster presented at 57th Conference of Experimental Psychologists (TeaP 2015), Hildesheim, Germany.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002A-4738-7
Abstract
Eye-movements can result in large artifacts in the EEG signal that could potentially obscure weaker cortically-based signals. Therefore, EEG studies are typically designed to minimize eye-movements [although see, Plöchl et al., 2012; Dimigen et al., 2011]. We present methods for simultaneous EEG and eye-tracking recordings in a visual scanning task. Participants were required to serially attend to four area-of-interests to detect a visual target. We compare EEG results, which were recorded either in the presence or absence of natural eye-movements. Furthermore, we demonstrate how natural eye-movement fixations can be reconstructed from the EOG signal, in a way that is comparable to the input from a simultaneous video-based eye-tracker. Based on these fixations, we address how EEG data can be segmented according to eye-movements (as opposed to experimentally timed stimuli). Finally, we explain how eye-movement induced artifacts can be effectively removed via independent component analysis (ICA), which allows EEG components to be classified as having either a 'cortical' or 'non-cortical' origin. These methods offer the potential of measuring robust EEG signals even in the presence of natural eye-movements.