title: Brain-Computer Interfaces for Detection and Localization of Targets in Aerial Images.
abstract: The N2pc event-related potential (ERP) appears on the opposite side of the scalp with respect to the visual hemisphere where an object of interest is located. We explored the feasibility of using it to extract information on the spatial location of targets in aerial images shown by means of a rapid serial visual presentation (RSVP) protocol using single-trial classification.
  
  
  
  Images were shown to 11 participants at a presentation rate of 5 Hz while recording electroencephalographic signals. With the resulting ERPs, we trained linear classifiers for single-trial detection of target presence and location. We analyzed the classifiers' decisions and their raw output scores on independent test sets as well as the averages and voltage distributions of the ERPs.
  
  
  
  The N2pc is elicited in RSVP presentation of complex images and can be recognized in single trials (the median area under the receiver operating characteristic curve was 0.76 for left versus right classification). Moreover, the peak amplitude of this ERP correlates with the horizontal position of the target within an image. The N2pc varies significantly depending on handedness, and these differences can be used for discriminating participants in terms of their preferred hand.
  
  
  
  The N2pc is elicited during RSVP presentation of real complex images and contains analogue information that can be used to roughly infer the horizontal position of targets. Furthermore, differences in the N2pc due to handedness should be taken into account when creating collaborative brain-computer interfaces.
authors.affiliation: School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.
authors.forename: Ana
authors.initials: A
authors.lastname: Matran-Fernandez
authors.affiliation: School Computer ScienceUniversity of Essex.
authors.forename: Riccardo
authors.initials: R
authors.lastname: Poli
mesh_terms: D000465:Algorithms; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006801:Humans; D000069550:Machine Learning; D008297:Male; D010364:Pattern Recognition, Visual / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013028:Space Perception / Q000502:physiology*; D013647:Task Performance and Analysis; D055815:Young Adult