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

Y. Lai, W. Van Drongelen, L. Ding, K. E. Hecox, V. L. Towle, D. M. Frim, Bin He

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152 Scopus citations


The present study aims to accurately estimate the in vivo brain-to-skull conductivity ratio by means of cortical imaging technique. Simultaneous extra- and intra-cranial potential recordings induced by subdural current stimulation were analyzed to get the estimation. The effective brain-to-skull conductivity ratio was estimated in vivo for 5 epilepsy patients. The estimation was performed using multi-channel simultaneously recorded scalp and cortical electrical potentials during subdural electrical stimulation. The cortical imaging technique was used to compute the inverse cortical potential distribution from the scalp recorded potentials using a 3-shell head volume conductor model. The brain-to-skull conductivity ratio, which leads to the most consistent cortical potential estimates with respect to the direct intra-cranial measurements, is considered to be the effective brain-to-skull conductivity ratio. The present estimation provided consistent results in 5 human subjects studied. The in vivo effective brain-to-skull conductivity ratio ranged from 18 to 34 in the 5 epilepsy patients. The effective brain-to-skull conductivity ratio can be estimated from simultaneous intra- and extra-cranial potential recordings and the averaged value/standard deviation is 25±7. The present results provide important experimental data on the brain-to-skull conductivity ratio, which is of significance for accurate brain source localization using piece-wise homogeneous head models.

Original languageEnglish (US)
Pages (from-to)456-465
Number of pages10
JournalClinical Neurophysiology
Issue number2
StatePublished - Feb 2005

Bibliographical note

Funding Information:
The authors wish to thank Xin Zhang for useful discussions, Ying Ni for assistance in data preparation, and Yingchun Zhang for assistance in the implementation of computer codes for the 4-spheres model. This work was supported in part by NIH R01EB00178, NSF BES-0218736, NSF BES-0411898, and NSF CAREER Award BES-9875344.


  • Brain mapping
  • Brain-to-skull conductivity ratio
  • Cortical imaging
  • High-resolution EEG
  • Inverse problem
  • Skull conductivity


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