AUTHOR=Fernandez-Vargas Jacobo , Pfaff Hanns U., Rodriguez Francisco B., Varona Pablo 

TITLE=Assisted closed-loop optimization of SSVEP-BCI efficiency

JOURNAL=Frontiers in Neural Circuits

VOLUME=7

YEAR=2013

URL=https://www.frontiersin.org/journals/neural-circuits/articles/10.3389/fncir.2013.00027

DOI=10.3389/fncir.2013.00027

ISSN=1662-5110

ABSTRACT=<p>We designed a novel <italic>assisted closed-loop optimization protocol</italic> to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol <italic>both</italic> the subject and the machine share information and control over the BCI goal. Generally, the innovative <italic>assistance</italic> consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a <italic>closed-loop search</italic> for the best set of <italic>SSVEP</italic> flicker frequencies and (2) feedback of actual <italic>SSVEP</italic> magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in <italic>real-time</italic> by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with <italic>N</italic> = 18 subjects, we found significant evidence that our protocol <italic>outperformed</italic> classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of <italic>assisted closed-loop</italic> protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research.</p>