title: An online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation.
abstract: OBJECTIVE
  In this work we present--for the first time--the online operation of an electroencephalogram (EEG) brain-computer interface (BCI) system based on covert visuospatial attention (CVSA), without relying on any evoked responses. Electrophysiological correlates of pure top-down CVSA have only recently been proposed as a control signal for BCI. Such systems are expected to share the ease of use of stimulus-driven BCIs (e.g. P300, steady state visually evoked potential) with the autonomy afforded by decoding voluntary modulations of ongoing activity (e.g. motor imagery).
  
  
  METHODS
  Eight healthy subjects participated in the study. EEG signals were acquired with an active 64-channel system. The classification method was based on a time-dependent approach tuned to capture the most discriminant spectral features of the temporal evolution of attentional processes. The system was used by all subjects over two days without retraining, to verify its robustness and reliability.
  
  
  RESULTS
  We report a mean online accuracy across the group of 70.6 ± 1.5%, and 88.8 ± 5.8% for the best subject. Half of the participants produced stable features over the entire duration of the study. Additionally, we explain drops in performance in subjects showing stable features in terms of known electrophysiological correlates of fatigue, suggesting the prospect of online monitoring of mental states in BCI systems.
  
  
  CONCLUSIONS
  This work represents the first demonstration of the feasibility of an online EEG BCI based on CVSA. The results achieved suggest the CVSA BCI as a promising alternative to standard BCI modalities.
authors.affiliation: Chair in Non-Invasive Brain-Machine Interface, École Polytecnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: L
authors.initials: L
authors.lastname: Tonin
authors.forename: R
authors.initials: R
authors.lastname: Leeb
authors.forename: A
authors.initials: A
authors.lastname: Sobolewski
authors.forename: J del R
authors.initials: Jdel R
authors.lastname: Millán
mesh_terms: D000328:Adult; D001288:Attention / Q000502:physiology*; D062207:Brain-Computer Interfaces; D003463:Cues; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods*; D055724:Electrophysiological Phenomena / Q000502:physiology; D005074:Evoked Potentials, Visual / Q000502:physiology; D005221:Fatigue / Q000503:physiopathology; D005260:Female; D005403:Fixation, Ocular / Q000502:physiology; D006801:Humans; D008297:Male; D009862:Online Systems; D011597:Psychomotor Performance / Q000502:physiology; D015203:Reproducibility of Results; D013028:Space Perception / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult