An Electroencephalography (EEG) inverse solution technique can be seen as a way to add spatial information to extra-cranial measurements. In other words, it is a mathematical/physical way to expand the dimensionality of scalp measurements so as to embed intra-cranial spatial information. This paper presents the new sLORETA-FOCUSS approach estimating the current density distribution in the brain...

This paper discusses the location bias and the spatial resolution in the reconstruction of a single dipole source by various spatial filtering techniques used for neuromagnetic imaging. We first analyze the location bias for several representative adaptive and non-adaptive spatial filters using their resolution kernels. This analysis theoretically validates previously reported empirical finding...

In this paper we present a new localization method SMS-LORETA (Simultaneous Multiple SourcesLow Resolution Brain Electromagnetic Tomography), capable to locate efficiently multiple simultaneous sources. The new method overcomes some of the drawbacks of sLORETA (standardized Low Resolution Brain Electromagnetic Tomography). The key idea of the new method is the iterative search for current dipol...

19 scalp electrode (EEG) and 8 intra-cranial electrode (iEEG) are recorded simultaneously with a common reference. EEG data is subjected to independent component analysis (ICA) and localisation of components in grey matter is estimated by the sLORETA inverse solution. Correlation between the time series of two independent components and intra-cranial recordings is very high (computed over 23552...

This paper deals with the EEG/MEG neuroimaging problem: given measurements of scalp electric potential differences (EEG: electroencephalogram) and extracranial magnetic fields (MEG: magnetoencephalogram), find the 3D distribution of the generating electric neuronal activity. This problem has no unique solution. Only particular solutions with “good” localization properties are of interest, since...

BACKGROUND Standardized low-resolution electromagnetic tomography (sLORETA) is a new quantitative EEG method for determining distribution of neuronal electrical activity in the form of three-dimensional images of current density of the cerebral cortex. Unlike standard quantitative EEG, it allows noninvasive and detailed localization of neuronal generators responsible for surface EEG with zero l...

BACKGROUND Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized. METHODS EEG data were ge...

Electroencephalography (EEG) has enjoyed considerable attention over the past century and has been applied for diagnosis of epilepsy, stroke, traumatic brain injury and other disorders where 3D localization of electrical activity in the brain is potentially of great diagnostic value. In this study we evaluate the precision and accuracy of spatial localization of electrical activity in the brain...

In biomagnetic inverse problem, the estimated signal source distribution is practically required to provide with sharpness, smoothness, bias-free, high resolution, etc. Some of the requirements conflict each other. We propose the newly developed biomagnetic signal source estimation method, the minimum leadfield-variance beamformer (MLVB) with the voxel-wise orthonormal leadfield (VWOL) for comp...