An iterative subspace denoising algorithm for removing electroencephalogram ocular artifacts.

Background: Electroencephalogram (EEG) measurements are always contaminated by non-cerebral signals, which disturb EEG interpretability. Among the different artifacts, ocular artifacts are the most disturbing ones. In previous studies, limited improvement has been obtained using frequency-based methods.

Nonstationary brain source separation for multiclass motor imagery.

This paper describes a method to recover task-related brain sources in the context of multiclass brain--computer interfaces (BCIs) based on noninvasive EEG. We extend the method joint approximate diagonalization (JAD) for spatial filtering using a maximum likelihood framework. This generic formulation: 1) bridges the gap between the common spatial patterns (CSPs) and blind source separation of nonstationary sources; and 2) leads to a neurophysiologically adapted version of JAD, accounting for the successive activations/deactivations of brain sources during motor imagery (MI) trials.

On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics.

Over the last ten years blind source separation (BSS) has become a prominent processing tool in the study of human electroencephalography (EEG). Without relying on head modeling BSS aims at estimating both the waveform and the scalp spatial pattern of the intracranial dipolar current responsible of the observed EEG. In this review we begin by placing the BSS linear instantaneous model of EEG within the framework of brain volume conduction theory.

Topographical dynamics of brain connections for the design of asynchronous brain-computer interfaces.

This article presents a new processing method to design brain-computer interfaces (BCIs). It shows how to use the perturbations of the communication between different cortical areas due to a cognitive task. For this, the network of the cerebral connections is built from correlations between cortical areas at specific frequencies and is analyzed using graph theory.