Literature DB >> 12169243

Boundary element method-based cortical potential imaging of somatosensory evoked potentials using subjects' magnetic resonance images.

B He1, X Zhang, J Lian, H Sasaki, D Wu, V L Towle.   

Abstract

A boundary element method-based cortical potential imaging technique has been developed to directly link the scalp potentials with the cortical potentials with the aid of magnetic resonance images of the subjects. First, computer simulations were conducted to evaluate the new approach in a concentric three-sphere inhomogeneous head model. Second, the corresponding cortical potentials were estimated from the patients' preoperative scalp somatosensory evoked potentials (SEPs) based on the boundary element models constructed from subjects' magnetic resonance images and compared to the postoperative direct cortical potential recordings in the same patients. Simulation results demonstrated that the cortical potentials can be estimated from the scalp potentials using different scalp electrode configurations and are robust against measurement noise. The cortical imaging analysis of the preoperative scalp SEPs recorded from patients using the present approach showed high consistency in spatial pattern with the postoperative direct cortical potential recordings. Quantitative comparison between the estimated and the directly recorded subdural grid potentials resulted in reasonably high correlation coefficients in cases studied. Amplitude difference between the estimated and the recorded potentials was also observed as indexed by the relative error, and the possible underlying reasons are discussed. The present numerical and experimental results validate the boundary element method-based cortical potential imaging approach and demonstrate the feasibility of the new approach in noninvasive high-resolution imaging of brain electric activities from scalp potential measurement and magnetic resonance images.

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Year:  2002        PMID: 12169243     DOI: 10.1006/nimg.2002.1127

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  25 in total

1.  A cortical potential imaging study from simultaneous extra- and intracranial electrical recordings by means of the finite element method.

Authors:  Yingchun Zhang; Lei Ding; Wim van Drongelen; Kurt Hecox; David M Frim; Bin He
Journal:  Neuroimage       Date:  2006-05-02       Impact factor: 6.556

2.  Noninvasive cortical imaging of epileptiform activities from interictal spikes in pediatric patients.

Authors:  Yuan Lai; Xin Zhang; Wim van Drongelen; Michael Korhman; Kurt Hecox; Ying Ni; Bin He
Journal:  Neuroimage       Date:  2010-07-17       Impact factor: 6.556

3.  Ictal source analysis: localization and imaging of causal interactions in humans.

Authors:  Lei Ding; Gregory A Worrell; Terrence D Lagerlund; Bin He
Journal:  Neuroimage       Date:  2006-11-16       Impact factor: 6.556

4.  A wavelet-based time-frequency analysis approach for classification of motor imagery for brain-computer interface applications.

Authors:  Lei Qin; Bin He
Journal:  J Neural Eng       Date:  2005-08-15       Impact factor: 5.379

Review 5.  Integration of EEG/MEG with MRI and fMRI.

Authors:  Zhongming Liu; Lei Ding; Bin He
Journal:  IEEE Eng Med Biol Mag       Date:  2006 Jul-Aug

6.  A new magnetic resonance electrical impedance tomography (MREIT) algorithm: the RSM-MREIT algorithm with applications to estimation of human head conductivity.

Authors:  Nuo Gao; S A Zhu; Bin He
Journal:  Phys Med Biol       Date:  2006-05-31       Impact factor: 3.609

7.  Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex.

Authors:  Chang-Hwan Im; Arvind Gururajan; Nanyin Zhang; Wei Chen; Bin He
Journal:  J Neurosci Methods       Date:  2006-11-13       Impact factor: 2.390

8.  Sparse source imaging in electroencephalography with accurate field modeling.

Authors:  Lei Ding; Bin He
Journal:  Hum Brain Mapp       Date:  2008-09       Impact factor: 5.038

9.  Cortical potential imaging using L-curve and GCV method to choose the regularisation parameter.

Authors:  Narayan P Subramaniyam; Outi Rm Väisänen; Katrina E Wendel; Jaakko Av Malmivuo
Journal:  Nonlinear Biomed Phys       Date:  2010-06-03

10.  Identification of epileptogenic foci from causal analysis of ECoG interictal spike activity.

Authors:  C Wilke; W van Drongelen; M Kohrman; B He
Journal:  Clin Neurophysiol       Date:  2009-07-17       Impact factor: 3.708

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