Electrical Neuroimaging with Irrotational Sources.

This paper discusses theoretical aspects of the modeling of the sources of the EEG (i.e., the bioelectromagnetic inverse problem or source localization problem).

Spatiotemporal scales and links between electrical neuroimaging modalities.

Recordings of brain electrophysiological activity provide the most direct reflect of neural function. Information contained in these signals varies as a function of the spatial scale at which recordings are done: from single cell recording to large scale macroscopic fields, e.g.

EEG/MEG source imaging: methods, challenges, and open issues.

We present the four key areas of research-preprocessing, the volume conductor, the forward problem, and the inverse problem-that affect the performance of EEG and MEG source imaging. In each key area we identify prominent approaches and methodologies that have open issues warranting further investigation within the community, challenges associated with certain techniques, and algorithms necessitating clarification of their implications. More than providing definitive answers we aim to identify important open issues in the quest of source localization.

Methods for determining frequency- and region-dependent relationships between estimated LFPs and BOLD responses in humans.

The relationship between electrophysiological and functional magnetic resonance imaging (fMRI) signals remains poorly understood. To date, studies have required invasive methods and have been limited to single functional regions and thus cannot account for possible variations across brain regions. Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0-256 Hz) throughout the entire brain volume.

Electrophysiological correlates of affective blindsight.

An EEG investigation was carried out in a patient with complete cortical blindness who presented affective blindsight, i.e. who performed above chance when asked to guess the emotional expressions on a series of faces.

Bayesian models of mentalizing.

Surprisingly effortless is the human capacity known as "mentalizing", i.e., the ability to explain and predict the behavior of others by attributing to them independent mental states, such as beliefs, desires, emotions or intentions.

Modern electrophysiological methods for brain-computer interfaces.

Modern electrophysiological studies in animals show that the spectrum of neural oscillations encoding relevant information is broader than previously thought and that many diverse areas are engaged for very simple tasks. However, EEG-based brain-computer interfaces (BCI) still employ as control modality relatively slow brain rhythms or features derived from preselected frequencies and scalp locations. Here, we describe the strategy and the algorithms we have developed for the analysis of electrophysiological data and demonstrate their capacity to lead to faster accurate decisions based on linear classifiers.

How single-trial electrical neuroimaging contributes to multisensory research.

This study details a method to statistically determine, on a millisecond scale and for individual subjects, those brain areas whose activity differs between experimental conditions, using single-trial scalp-recorded EEG data. To do this, we non-invasively estimated local field potentials (LFPs) using the ELECTRA distributed inverse solution and applied non-parametric statistical tests at each brain voxel and for each time point. This yields a spatio-temporal activation pattern of differential brain responses.

Improving the performance of linear inverse solutions by inverting the resolution matrix.

This paper proposes a new strategy for improving the localization capabilities of linear inverse solutions, based on the relationship between the real solution and the estimated solution as described by the resolution matrix equation. Specifically, we present two alternatives based on either the partial or total inversion of the resolution matrix and applied them to the minimum norm solution, which is known for its poor performance in three-dimensional (3-D) localization problems. The minimum norm transformed inverse showed a clear improvement in 3-D localization.

Electrical neuroimaging based on biophysical constraints.

This paper proposes and implements biophysical constraints to select a unique solution to the bioelectromagnetic inverse problem. It first shows that the brain's electric fields and potentials are predominantly due to ohmic currents. This serves to reformulate the inverse problem in terms of a restricted source model permitting noninvasive estimations of Local Field Potentials (LFPs) in depth from scalp-recorded data.

Propagation of interictal epileptiform activity can lead to erroneous source localizations: a 128-channel EEG mapping study.

The relationship between interictal epileptiform activity and the epileptogenic zone is complex. Despite the fact that intraspike propagation may occur, the peak of the spike is often used as indicator of the site of ictal onset. In this investigation, spatio-temporal segmentation was used to demonstrate this intraspike propagation and to determine at which time point the voltage pattern corresponded best to the epileptogenic zone.