title: A multi-task learning approach for the extraction of single-trial evoked potentials.
abstract: Evoked potentials (EPs) are of great interest in neuroscience, but their measurement is difficult as they are embedded in background spontaneous electroencephalographic (EEG) activity which has a much larger amplitude. The widely used averaging technique requires the delivery of a large number of identical stimuli and yields only an "average" EP which does not allow the investigation of the possible variability of single-trial EPs. In the present paper, we propose the use of a multi-task learning method (MTL) for the simultaneous extraction of both the average and the N single-trial EPs from N recorded sweeps. The technique is developed within a Bayesian estimation framework and uses flexible stochastic models to describe the average response and the N shifts between the single-trial EPs and this average. Differently from other single-trial estimation approaches proposed in the literature, MTL can provide estimates of both the average and the N single-trial EPs in a single stage. In the present paper, MTL is successfully assessed on both synthetic (100 simulated recording sessions with N=20 sweeps) and real data (11 subjects with N=20 sweeps) relative to a cognitive task carried out for the investigation of the P300 component of the EP.
authors.affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6/B, 35131 Padova, Italy.
authors.forename: Costanza
authors.initials: C
authors.lastname: D'Avanzo
authors.forename: Anahita
authors.initials: A
authors.lastname: Goljahani
authors.forename: Gianluigi
authors.initials: G
authors.lastname: Pillonetto
authors.forename: Giuseppe
authors.initials: G
authors.lastname: De Nicolao
authors.forename: Giovanni
authors.initials: G
authors.lastname: Sparacino
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods*; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008962:Models, Theoretical; D011930:Reaction Time; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013997:Time Factors