title: Functional Brain Connectivity as a New Feature for P300 Speller.
abstract: The brain is a large-scale complex network often referred to as the "connectome". Cognitive functions and information processing are mainly based on the interactions between distant brain regions. However, most of the 'feature extraction' methods used in the context of Brain Computer Interface (BCI) ignored the possible functional relationships between different signals recorded from distinct brain areas. In this paper, the functional connectivity quantified by the phase locking value (PLV) was introduced to characterize the evoked responses (ERPs) obtained in the case of target and non-targets visual stimuli. We also tested the possibility of using the functional connectivity in the context of 'P300 speller'. The proposed approach was compared to the well-known methods proposed in the state of the art of "P300 Speller", mainly the peak picking, the area, time/frequency based features, the xDAWN spatial filtering and the stepwise linear discriminant analysis (SWLDA). The electroencephalographic (EEG) signals recorded from ten subjects were analyzed offline. The results indicated that phase synchrony offers relevant information for the classification in a P300 speller. High synchronization between the brain regions was clearly observed during target trials, although no significant synchronization was detected for a non-target trial. The results showed also that phase synchrony provides higher performance than some existing methods for letter classification in a P300 speller principally when large number of trials is available. Finally, we tested the possible combination of both approaches (classical features and phase synchrony). Our findings showed an overall improvement of the performance of the P300-speller when using Peak picking, the area and frequency based features. Similar performances were obtained compared to xDAWN and SWLDA when using large number of trials.
authors.affiliation: Department of electrical and computer engineering, ULFG1, Tripoli, Lebanon.|Azm center for research in biotechnology and its applications, EDST, Tripoli, Lebanon.
authors.forename: Aya
authors.initials: A
authors.lastname: Kabbara
authors.affiliation: Department of electrical and computer engineering, ULFG1, Tripoli, Lebanon.|Azm center for research in biotechnology and its applications, EDST, Tripoli, Lebanon.
authors.forename: Mohamad
authors.initials: M
authors.lastname: Khalil
authors.affiliation: Department of electrical and computer engineering, ULFG1, Tripoli, Lebanon.|Azm center for research in biotechnology and its applications, EDST, Tripoli, Lebanon.
authors.forename: Wassim
authors.initials: W
authors.lastname: El-Falou
authors.affiliation: Mazloum Hospital, Tripoli, Lebanon.
authors.forename: Hassan
authors.initials: H
authors.lastname: Eid
authors.affiliation: INSERM, U1099, F-35000, Rennes, France.|Université de Rennes 1, LTSI, F-35000, Rennes, France.
authors.forename: Mahmoud
authors.initials: M
authors.lastname: Hassan
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D062207:Brain-Computer Interfaces; D004566:Electrodes; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D009415:Nerve Net / Q000502:physiology*; D055815:Young Adult