The current review constitutes the first comprehensive look at the possibility that the
mismatch negativity (MMN, the deflection of the auditory ERP/ERF elicited by stimulus …

Abstract Dynamic Causal Modelling (DCM) is an approach first introduced for the analysis of
functional magnetic resonance imaging (fMRI) to quantify effective connectivity between …

In magneto-and electroencephalography (M/EEG), spatial modelling of sensor data is
necessary to make inferences about underlying brain activity. Most source reconstruction …

Bayesian modeling and analysis of the magnetoencephalography and
electroencephalography modalities provide a flexible framework for introducing prior …

MEG/EEG are non-invasive imaging techniques that record brain activity with high temporal
resolution. However, estimation of brain source currents from surface recordings requires …

Objective: Magnetoencephalography (MEG) is a non-invasive technique that measures the
magnetic fields of brain activity. In particular, a new type of optically pumped magnetometer …

The estimation of EEG generating sources constitutes an Inverse Problem (IP) in
Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and …

Magnetoencephalography (MEG) allows millisecond-scale non-invasive measurement of
magnetic fields generated by neural currents in the brain. However, localization of the …

Source localization in electroencephalography has received an increasing amount of
interest in the last decade. Solving the underlying ill-posed inverse problem usually requires …

We have developed a novel algorithm for integrating source localization and noise
suppression based on a probabilistic graphical model of stimulus-evoked MEG/EEG data …