Combining EEG and MEG for the reconstruction of epileptic activity using a calibrated realistic volume conductor model. Aydin, U., Vorwerk, J., Kupper, P., Heers, M., Kugel, H., Galka, A., Hamid, L., Wellmer, J., Kellinghaus, C., Rampp, S., & Wolters, C. *PLoS One*, 9(3):e93154, 2014. bibtex @Article{RSM:Ayd2014,
author = "U. Aydin and J. Vorwerk and P. Kupper and M. Heers and H.
Kugel and A. Galka and L. Hamid and J. Wellmer and C.
Kellinghaus and S. Rampp and C.H. Wolters",
title = "Combining EEG and MEG for the reconstruction of epileptic
activity using a calibrated realistic volume conductor
model.",
journal = "PLoS One",
year = "2014",
volume = "9",
number = "3",
pages = "e93154",
robnote = "To increase the reliability for the non-invasive
determination of the irritative zone in presurgical
epilepsy diagnosis, we introduce here a new experimental
and methodological source analysis pipeline that combines
the complementary information in EEG and MEG, and apply it
to data from a patient, suffering from refractory focal
epilepsy. Skull conductivity parameters in a six
compartment finite element head model with brain
anisotropy, constructed from individual MRI data, are
estimated in a calibration procedure using somatosensory
evoked potential (SEP) and field (SEF) data. These data
are measured in a single run before acquisition of further
runs of spontaneous epileptic activity. Our results show
that even for single interictal spikes, volume conduction
effects dominate over noise and need to be taken into
account for accurate source analysis. While cerebrospinal
fluid and brain anisotropy influence both modalities, only
EEG is sensitive to skull conductivity and conductivity
calibration significantly reduces the difference in
especially depth localization of both modalities,
emphasizing its importance for combining EEG and MEG
source analysis. On the other hand, localization
differences which are due to the distinct sensitivity
profiles of EEG and MEG persist. In case of a moderate
error in skull conductivity, combined source analysis
results can still profit from the different sensitivity
profiles of EEG and MEG to accurately determine location,
orientation and strength of the underlying sources. On the
other side, significant errors in skull modeling are
reflected in EEG reconstruction errors and could reduce
the goodness of fit to combined datasets. For combined EEG
and MEG source analysis, we therefore recommend
calibrating skull conductivity using additionally acquired
SEP/SEF data.",
bibdate = "Sun Sep 21 22:02:18 2014",
pmcid = "PMC3966892",
}

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Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.","bibdate":"Sun Sep 21 22:02:18 2014","pmcid":"PMC3966892","bibtex":"@Article{RSM:Ayd2014,\n author = \"U. Aydin and J. Vorwerk and P. Kupper and M. Heers and H.\n Kugel and A. Galka and L. Hamid and J. Wellmer and C.\n Kellinghaus and S. Rampp and C.H. Wolters\",\n title = \"Combining EEG and MEG for the reconstruction of epileptic\n activity using a calibrated realistic volume conductor\n model.\",\n journal = \"PLoS One\",\n year = \"2014\",\n volume = \"9\",\n number = \"3\",\n pages = \"e93154\",\n robnote = \"To increase the reliability for the non-invasive\n determination of the irritative zone in presurgical\n epilepsy diagnosis, we introduce here a new experimental\n and methodological source analysis pipeline that combines\n the complementary information in EEG and MEG, and apply it\n to data from a patient, suffering from refractory focal\n epilepsy. Skull conductivity parameters in a six\n compartment finite element head model with brain\n anisotropy, constructed from individual MRI data, are\n estimated in a calibration procedure using somatosensory\n evoked potential (SEP) and field (SEF) data. These data\n are measured in a single run before acquisition of further\n runs of spontaneous epileptic activity. Our results show\n that even for single interictal spikes, volume conduction\n effects dominate over noise and need to be taken into\n account for accurate source analysis. While cerebrospinal\n fluid and brain anisotropy influence both modalities, only\n EEG is sensitive to skull conductivity and conductivity\n calibration significantly reduces the difference in\n especially depth localization of both modalities,\n emphasizing its importance for combining EEG and MEG\n source analysis. On the other hand, localization\n differences which are due to the distinct sensitivity\n profiles of EEG and MEG persist. In case of a moderate\n error in skull conductivity, combined source analysis\n results can still profit from the different sensitivity\n profiles of EEG and MEG to accurately determine location,\n orientation and strength of the underlying sources. On the\n other side, significant errors in skull modeling are\n reflected in EEG reconstruction errors and could reduce\n the goodness of fit to combined datasets. 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