Estimation of Brain Electrical Sources using Multi-level Source Space Model

This paper describes a proposal for a new source space model called the multilevel source space model for the efficient and precise estimation of brain electrical activities. Unlike conventional source models, the proposed one generates both high- and low-resolution brain models which represent gray matter of a human cerebral cortex. The model can then be used to estimate brain electrical sources in a multiresolutive way. The usefulness of the proposed model has been verified using realistic simulations with real brain noise and anatomy

[1]  E. Halgren,et al.  Dynamic Statistical Parametric Mapping Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity , 2000, Neuron.

[2]  Jean-Francois Mangin,et al.  A multiresolution framework to MEG/EEG source imaging , 2001, IEEE Trans. Biomed. Eng..

[3]  Chang-Hwan Im,et al.  Multiresolutive reconstruction of magnetoencephalography source distribution , 2004 .

[4]  J. E. Moran,et al.  Multi-Resolution FOCUSS: A Source Imaging Technique Applied to MEG Data , 2005, Brain Topography.

[5]  M. Hämäläinen,et al.  Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data , 1989, IEEE Transactions on Biomedical Engineering.

[6]  John W Belliveau,et al.  Monte Carlo simulation studies of EEG and MEG localization accuracy , 2002, Human brain mapping.

[7]  Thomas R. Knösche,et al.  An fMRI-Constrained MEG Source Analysis with Procedures for Dividing and Grouping Activation , 2002, NeuroImage.

[8]  Norio Fujimaki,et al.  fMRI‐constrained MEG source imaging and consideration of fMRI invisible sources , 2005, Human brain mapping.

[9]  Anders M. Dale,et al.  Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain , 2004, NeuroImage.

[10]  N. Schaul,et al.  The fundamental neural mechanisms of electroencephalography. , 1998, Electroencephalography and clinical neurophysiology.

[11]  A. Oosterom.  The use of the spatial covariance in computing pericardial potentials , 1999 .

[12]  Bin He,et al.  Low resolution brain electromagnetic tomography in a realistic geometry head model: a simulation study , 2005, Physics in medicine and biology.

[13]  Karl J. Friston,et al.  Anatomically Informed Basis Functions for EEG Source Localization: Combining Functional and Anatomical Constraints , 2002, NeuroImage.

[14]  Olivier David,et al.  Time-Coherent Expansion of MEG/EEG Cortical Sources , 2002, NeuroImage.

[15]  A. Dale,et al.  Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach , 1993, Journal of Cognitive Neuroscience.