title: Independent Vector Analysis for SSVEP Signal Enhancement, Detection, and Topographical Mapping.
abstract: Steady state visual evoked potentials (SSVEPs) have been identified as an effective solution for brain computer interface (BCI) systems as well as for neurocognitive investigations. SSVEPs can be observed in the scalp-based recordings of electroencephalogram signals, and are one component buried amongst the normal brain signals and complex noise. We present a novel method for enhancing and improving detection of SSVEPs by leveraging the rich joint blind source separation framework using independent vector analysis (IVA). IVA exploits the diversity within each dataset while preserving dependence across all the datasets. This approach is shown to enhance the detection of SSVEP signals across a range of frequencies and subjects for BCI systems. Furthermore, we show that IVA enables improved topographic mapping of the SSVEP propagation providing a promising new tool for neuroscience and neurocognitive research.
authors.affiliation: Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA. demge1@umbc.edu.
authors.forename: Darren K
authors.identifier: 0000-0003-0038-9602
authors.initials: DK
authors.lastname: Emge
authors.affiliation: SIGnal processing and MAchine learning (SIGMA) lab, ESPCI ParisTech, 10, rue Vauquelin, 75231, Paris Cedex 05, France.
authors.forename: François-Benoît
authors.initials: FB
authors.lastname: Vialatte
authors.affiliation: SIGnal processing and MAchine learning (SIGMA) lab, ESPCI ParisTech, 10, rue Vauquelin, 75231, Paris Cedex 05, France.
authors.forename: Gérard
authors.initials: G
authors.lastname: Dreyfus
authors.affiliation: Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA.
authors.forename: Tülay
authors.initials: T
authors.lastname: Adalı
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D062207:Brain-Computer Interfaces; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D007839:Functional Laterality; D064368:Healthy Volunteers; D006801:Humans; D017603:Signal Detection, Psychological / Q000502:physiology*
keywords: Brain computer interface (BCI); Independent vector analysis (IVA); Steady state visual evoked potentials (SSVEP)