Abstract
Objective. One of the main goals of brain-computer interfaces (BCI) is to restore communication abilities in patients. BCIs often use event-related potentials (ERPs) like the P300 which signals the presence of a target in a stream of stimuli. The P300 and related approaches, however, are inherently limited, as they require many stimulus presentations to obtain a usable control signal. Many approaches depend on gaze direction to focus the target, which is also not a viable approach in many cases, because eye movements might be impaired in potential users. Here we report on a BCI that avoids both shortcomings by decoding spatial target information, independent of gaze shifts. Approach. We present a new method to decode from the electroencephalogram (EEG) covert shifts of attention to one out of four targets simultaneously presented in the left and right visual field. The task is designed to evoke the N2pc component—a hemisphere lateralized response, elicited over the occipital scalp contralateral to the attended target. The decoding approach involves decoding of the N2pc based on data-driven estimation of spatial filters and a correlation measure. Main results. Despite variability of decoding performance across subjects, 22 out of 24 subjects performed well above chance level. Six subjects even exceeded 80% (cross-validated: 89%) correct predictions in a four-class discrimination task. Hence, the single-trial N2pc proves to be a component that allows for reliable BCI control. An offline analysis of the EEG data with respect to their dependence on stimulation time and number of classes demonstrates that the present method is also a workable approach for two-class tasks. Significance. Our method extends the range of strategies for gaze-independent BCI control. The proposed decoding approach has the potential to be efficient in similar applications intended to decode ERPs.
Highlights
Brain-computer interfaces (BCI) are designed to restore severely paralyzed people’s ability to communicate directly with their environment or to control assistive devices
To discriminate four different colors, we presented all of them simultaneously in the visual search display but each color was associated with a unique sequence of left/right presentations, to the principle in P300-based brain-computer interfaces (BCI) where each symbol is associated with a unique sequence of intensifications
We show that the features, extracted from training data and driving the BCI control, clearly represent characteristics of the N2pc, confirming that the BCI was driven by this marker of spatial attention
Summary
Brain-computer interfaces (BCI) are designed to restore severely paralyzed people’s ability to communicate directly with their environment or to control assistive devices. The modulation of oscillatory brain signals due to motor imagery is widely used to control a BCI [1, 2]. A second group of gaze-independent BCIs are those that are controlled by stimulus-evoked brain activity modulations. Shifts of attention to one or the other peripheral location are decoded from power changes of the steady-state visual evoked potential (SSVEP) [7]. A fourth approach is to use auditory stimulation aiming at decoding event-related potentials (ERPs) [8, 9] or steady state responses [10]. An alternative channel to deliver stimuli is tactile stimulation, which has been used to decode BCI commands from P300 responses [12] and somatosensory steady-state evoked potentials [13]. In the latter study only 50% of participants could achieve control
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