Literature DB >> 17492058

Estimation of in vivo brain-to-skull conductivity ratio in humans.

Yingchun Zhang1, Wim van Drongelen, Bin He.   

Abstract

The electrical conductivity value of the human skull is important for biophysics research of the brain. In the present study, the human brain-to-skull conductivity ratio was estimated through in vivo experiments utilizing intra-cranial electrical stimulation in two epilepsy patients. A realistic geometry inhomogeneous head model including the implanted silastic grids was constructed with the aid of the finite element method, and used to estimate the conductivity ratio. Averaging over 49 sets of measurements, the mean value and standard deviation of the brain-to-skull conductivity ratio were found to be 18.7 and 2.1, respectively.

Entities:  

Year:  2006        PMID: 17492058      PMCID: PMC1867457          DOI: 10.1063/1.2398883

Source DB:  PubMed          Journal:  Appl Phys Lett        ISSN: 0003-6951            Impact factor:   3.791


  8 in total

1.  Estimating cortical potentials from scalp EEG's in a realistically shaped inhomogeneous head model by means of the boundary element method.

Authors:  B He; Y Wang; D Wu
Journal:  IEEE Trans Biomed Eng       Date:  1999-10       Impact factor: 4.538

2.  The conductivity of the human skull: results of in vivo and in vitro measurements.

Authors:  T F Oostendorp; J Delbeke; D F Stegeman
Journal:  IEEE Trans Biomed Eng       Date:  2000-11       Impact factor: 4.538

3.  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

4.  A second-order finite element algorithm for solving the three-dimensional EEG forward problem.

Authors:  Y C Zhang; S A Zhu; Bin He
Journal:  Phys Med Biol       Date:  2004-07-07       Impact factor: 3.609

5.  A computationally efficient method for accurately solving the EEG forward problem in a finely discretized head model.

Authors:  Lora A Neilson; Mikhail Kovalyov; Zoltan J Koles
Journal:  Clin Neurophysiol       Date:  2005-10       Impact factor: 3.708

6.  Current distribution in the brain from surface electrodes.

Authors:  S Rush; D A Driscoll
Journal:  Anesth Analg       Date:  1968 Nov-Dec       Impact factor: 5.108

7.  Demonstration of useful differences between magnetoencephalogram and electroencephalogram.

Authors:  D Cohen; B N Cuffin
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1983-07

8.  Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings.

Authors:  Y Lai; W van Drongelen; L Ding; K E Hecox; V L Towle; D M Frim; B He
Journal:  Clin Neurophysiol       Date:  2005-02       Impact factor: 3.708

  8 in total
  46 in total

1.  Modeling of the human skull in EEG source analysis.

Authors:  Moritz Dannhauer; Benjamin Lanfer; Carsten H Wolters; Thomas R Knösche
Journal:  Hum Brain Mapp       Date:  2010-08-05       Impact factor: 5.038

2.  EEG-fMRI reciprocal functional neuroimaging.

Authors:  Lin Yang; Zhongming Liu; Bin He
Journal:  Clin Neurophysiol       Date:  2010-04-08       Impact factor: 3.708

3.  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

4.  EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks.

Authors:  Bradley J Edelman; Bryan Baxter; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2015-08-12       Impact factor: 4.538

5.  fMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints.

Authors:  Zhongming Liu; Bin He
Journal:  Neuroimage       Date:  2007-10-12       Impact factor: 6.556

6.  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

7.  Parallel implementation of the accelerated BEM approach for EMSI of the human brain.

Authors:  Y Ataseven; Z Akalin-Acar; C E Acar; N G Gençer
Journal:  Med Biol Eng Comput       Date:  2008-02-26       Impact factor: 2.602

8.  Corticolimbic mechanisms in the control of trial and error learning.

Authors:  Phan Luu; Matthew Shane; Nikki L Pratt; Don M Tucker
Journal:  Brain Res       Date:  2008-10-14       Impact factor: 3.252

9.  Cortical imaging of event-related (de)synchronization during online control of brain-computer interface using minimum-norm estimates in frequency domain.

Authors:  Han Yuan; Alexander Doud; Arvind Gururajan; Bin He
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-10       Impact factor: 3.802

10.  The relationship between conductivity uncertainties and EEG source localization accuracy.

Authors:  Gang Wang; Lin Yang; Gregory Worrell; Bin He
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009
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