TY - JOUR A1 - Lugo, Zulay R. A1 - Quitadamo, Lucia R. A1 - Bianchi, Luigi A1 - Pellas, Fréderic A1 - Veser, Sandra A1 - Lesenfants, Damien A1 - Real, Ruben G. L. A1 - Herbert, Cornelia A1 - Guger, Christoph A1 - Kotchoubey, Boris A1 - Mattia, Donatella A1 - Kübler, Andrea A1 - Laureys, Steven A1 - Noirhomme, Quentin T1 - Cognitive Processing in Non-Communicative Patients: What Can Event-Related Potentials Tell Us? JF - Frontiers in Human Neuroscience N2 - Event-related potentials (ERP) have been proposed to improve the differential diagnosis of non-responsive patients. We investigated the potential of the P300 as a reliable marker of conscious processing in patients with locked-in syndrome (LIS). Eleven chronic LIS patients and 10 healthy subjects (HS) listened to a complex-tone auditory oddball paradigm, first in a passive condition (listen to the sounds) and then in an active condition (counting the deviant tones). Seven out of nine HS displayed a P300 waveform in the passive condition and all in the active condition. HS showed statistically significant changes in peak and area amplitude between conditions. Three out of seven LIS patients showed the P3 waveform in the passive condition and five of seven in the active condition. No changes in peak amplitude and only a significant difference at one electrode in area amplitude were observed in this group between conditions. We conclude that, in spite of keeping full consciousness and intact or nearly intact cortical functions, compared to HS, LIS patients present less reliable results when testing with ERP, specifically in the passive condition. We thus strongly recommend applying ERP paradigms in an active condition when evaluating consciousness in non-responsive patients. KW - P300 KW - event-related potentials KW - locked-in syndrome KW - vegetative state KW - unresponsive wakefulness syndrome KW - minimally conscious state Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-165165 VL - 10 IS - 569 ER - TY - JOUR A1 - Zhou, Sijie A1 - Allison, Brendan Z. A1 - Kübler, Andrea A1 - Cichocki, Andrzej A1 - Wang, Xingyu A1 - Jin, Jing T1 - Effects of Background Music on Objective and Subjective Performance Measures in an Auditory BCI JF - Frontiers in Computational Neuroscience N2 - Several studies have explored brain computer interface (BCI) systems based on auditory stimuli, which could help patients with visual impairments. Usability and user satisfaction are important considerations in any BCI. Although background music can influence emotion and performance in other task environments, and many users may wish to listen to music while using a BCI, auditory, and other BCIs are typically studied without background music. Some work has explored the possibility of using polyphonic music in auditory BCI systems. However, this approach requires users with good musical skills, and has not been explored in online experiments. Our hypothesis was that an auditory BCI with background music would be preferred by subjects over a similar BCI without background music, without any difference in BCI performance. We introduce a simple paradigm (which does not require musical skill) using percussion instrument sound stimuli and background music, and evaluated it in both offline and online experiments. The result showed that subjects preferred the auditory BCI with background music. Different performance measures did not reveal any significant performance effect when comparing background music vs. no background. Since the addition of background music does not impair BCI performance but is preferred by users, auditory (and perhaps other) BCIs should consider including it. Our study also indicates that auditory BCIs can be effective even if the auditory channel is simultaneously otherwise engaged. KW - brain computer interface KW - event-related potentials KW - auditory KW - music background KW - audio stimulus Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-165101 VL - 10 IS - 105 ER - TY - JOUR A1 - Acqualagna, Laura A1 - Botrel, Loic A1 - Vidaurre, Carmen A1 - Kübler, Andrea A1 - Blankertz, Benjamin T1 - Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface JF - PLoS ONE N2 - In the last years Brain Computer Interface (BCI) technology has benefited from the development of sophisticated machine leaning methods that let the user operate the BCI after a few trials of calibration. One remarkable example is the recent development of co-adaptive techniques that proved to extend the use of BCIs also to people not able to achieve successful control with the standard BCI procedure. Especially for BCIs based on the modulation of the Sensorimotor Rhythm (SMR) these improvements are essential, since a not negligible percentage of users is unable to operate SMR-BCIs efficiently. In this study we evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session. Different psychological interventions were performed prior the BCI session in order to investigate how motor coordination training and relaxation could influence BCI performance. A neurophysiological indicator based on the Power Spectral Density (PSD) was extracted by the recording of few minutes of resting state brain activity and tested as predictor of BCI performances. Results show that high accuracies in operating the BCI could be reached by the majority of the participants before the end of the session. BCI performances could be significantly predicted by the neurophysiological indicator, consolidating the validity of the model previously developed. Anyway, we still found about 22% of users with performance significantly lower than the threshold of efficient BCI control at the end of the session. Being the inter-subject variability still the major problem of BCI technology, we pointed out crucial issues for those who did not achieve sufficient control. Finally, we propose valid developments to move a step forward to the applicability of the promising co-adaptive methods. KW - large-scale assessment KW - Brain Computer Interface KW - machine leaning KW - fully automatic KW - co-adaptive Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-167230 VL - 11 IS - 2 ER -