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Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings
- Source :
- Clinical Neurophysiology. 116:456-465
- Publication Year :
- 2005
- Publisher :
- Elsevier BV, 2005.
-
Abstract
- Objective 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. Methods 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. Results 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. Conclusions 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. Significance 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.
- Subjects :
- Male
Materials science
Models, Neurological
Conductivity
Electroencephalography
Brain mapping
Standard deviation
Physiology (medical)
medicine
Humans
Computer Simulation
Child
Epilepsy
medicine.diagnostic_test
Skull
Electric Conductivity
Brain
Anatomy
Human brain
Electromagnetic source imaging
Electric Stimulation
Sensory Systems
Electrophysiology
medicine.anatomical_structure
Neurology
Scalp
Female
Neurology (clinical)
Algorithms
Biomedical engineering
Subjects
Details
- ISSN :
- 13882457
- Volume :
- 116
- Database :
- OpenAIRE
- Journal :
- Clinical Neurophysiology
- Accession number :
- edsair.doi.dedup.....082e397458dea52aac1c2947e3385a98
- Full Text :
- https://doi.org/10.1016/j.clinph.2004.08.017