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In vivo measurement of the brain and skull resistivities using an EIT-based method and the combined analysis of SEF/SEP data
Results of "in vivo" measurements of the skull and brain resistivities are presented for six subjects. Results are obtained using two different methods, based on spherical head models. The first method uses the principles of electrical impedance tomography (EIT) to estimate the equivalent...
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Published in: | IEEE transactions on biomedical engineering 2003-09, Vol.50 (9), p.1124-1127 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Results of "in vivo" measurements of the skull and brain resistivities are presented for six subjects. Results are obtained using two different methods, based on spherical head models. The first method uses the principles of electrical impedance tomography (EIT) to estimate the equivalent electrical resistivities of brain (ρ/sub brain/), skull (ρ/sub skull/) and skin (ρ/sub skin/) according to S. Goncalves et al., Physiol. Meas., vol. 21, p. 379-93 (2000).. The second one estimates the same parameters through a combined analysis of the evoked somatosensory cortical response, recorded simultaneously using magnetoencephalography (MEG) and electroencephalography (EEG). The EIT results, obtained with the same relative skull thickness (0.05) for all subjects, show a wide variation of the ratio ρ/sub skull//ρ/sub brain/ among subjects (average =72, SD=48%). However, the ρ/sub skull//ρ/sub brain/ ratios of the individual subjects are well reproduced by combined analysis of somatosensory evoked fields (SEF) and somatosensory evoked potentials (SEP). These preliminary results suggest that the ρ/sub skull//ρ/sub brain/ variations over subjects cannot be disregarded in the EEG inverse problem (IP) when a spherical model is used. The agreement between EIT and SEF/SEP points to the fact that whatever the source of variability, the proposed EIT-based method |
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ISSN: | 0018-9294 1558-2531 |
DOI: | 10.1109/TBME.2003.816072 |