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Abstract
The co-registration of eye tracking and electroencephalography provides a holistic measure of ongoing cognitive processes. Recently, fixation-related potentials have been introduced to quantify the neural activity in such bi-modal recordings. Fixation-related potentials are time-locked to fixation onsets, just like event-related potentials are locked to stimulus onsets. Compared to existing electroencephalography-based brain-machine interfaces that depend on visual stimuli, fixation-related potentials have the advantages that they can be used in free, unconstrained viewing conditions and can also be classified on a single-trial level. Thus, fixation-related potentials have the potential to allow for conceptually different brain-machine interfaces that directly interpret cortical activity related to the visual processing of specific objects. However, existing research has investigated fixation-related potentials only with very restricted and highly unnatural stimuli in simple search tasks while participant’s body movements were restricted. We present a study where we relieved many of these restrictions while retaining some control by using a gaze-contingent visual search task. In our study, participants had to find a target object out of 12 complex and everyday objects presented on a screen while the electrical activity of the brain and eye movements were recorded simultaneously. Our results show that our proposed method for the classification of fixation-related potentials can clearly discriminate between fixations on relevant, non-relevant and background areas. Furthermore, we show that our classification approach generalizes not only to different test sets from the same participant, but also across participants. These results promise to open novel avenues for exploiting fixation-related potentials in electroencephalography-based brain-machine interfaces and thus providing a novel means for intuitive human-machine interaction.
Highlights
Brain-machine interfaces (BMI) based on the electroencephalogram (EEG) have been around for more than two decades
In order to overcome the limitations of existing EEG-based BMI systems described above, we present a novel and conceptually different approach based on fixation-related potentials (FRPs)
Our results show that the detection of FRPs in a more complex and less constrained task is possible on a single-trial level
Summary
Brain-machine interfaces (BMI) based on the electroencephalogram (EEG) have been around for more than two decades now. Among the two most prominent components are the P300 event-related potential (ERP) and steady-state visually evoked potentials (SSVEP). BMI systems usually implement the oddball paradigm by sequentially highlighting symbols or icons on the computer screen in a random sequence for a short period of time (e.g., 100 ms). SSVEPs are elicited by stimuli flickering at a particular frequency [3]. SSVEP-based BMI systems are usually rather fast and reliable, due to the simple, frequency-based structure of the cortical response and the option to flicker several stimuli simultaneously [6]. In contrast to SSVEPs, the neural responses to stimuli in cVEPs depend non-linearly on flickering patterns specified by binary codebook vectors. Please refer to Bin et al [8] for a concise comparison of SSVEPs and cVEPs for BMI
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