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Inter-subject variability of skull conductivity and thickness in calibrated realistic head models

Antonakakis Marios, Schrader Sophie, Aydin Ümit, Khan Asad, Gross Joachim, Zervakis Michail, Wolters Carsten H., Rampp, Stefan 1975-

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Year 2020
Type of Item Peer-Reviewed Journal Publication
Bibliographic Citation M. Antonakakis, S. Schrader, Ü. Aydin, A. Khan, J. Gross, M. Zervakis, S. Rampp and C. H. Wolters, “Inter-subject variability of skull conductivity and thickness in calibrated realistic head models”, NeuroImage, vol. 223, Dec. 2020. doi: 10.1016/j.neuroimage.2020.117353
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Skull conductivity has a substantial influence on EEG and combined EEG and MEG source analysis as well as on optimized transcranial electric stimulation. To overcome the use of standard literature values, we propose a non-invasive two-level calibration procedure to estimate skull conductivity individually in a group study with twenty healthy adults. Our procedure requires only an additional run of combined somatosensory evoked potential and field data, which can be easily integrated in EEG/MEG experiments. The calibration procedure uses the P20/N20 topographies and subject-specific realistic head models from MRI. We investigate the inter-subject variability of skull conductivity and relate it to skull thickness, age and gender of the subjects, to the individual scalp P20/N20 surface distance between the P20 potential peak and the N20 potential trough as well as to the individual source depth of the P20/N20 source. We found a considerable inter-subject variability for (calibrated) skull conductivity (8.44 ± 4.84 mS/m) and skull thickness (5.97 ± 1.19 mm) with a statistically significant correlation between them (rho = 0.52). Age showed a statistically significant negative correlation with skull conductivity (rho = -0.5). Furthermore, P20/N20 surface distance and source depth showed large inter-subject variability of 12.08 ± 3.21 cm and 15.45 ± 4.54 mm, respectively, but there was no significant correlation between them. We also found no significant differences among gender subgroups for the investigated measures. It is thus important to take the inter-subject variability of skull conductivity and thickness into account by means of using subject-specific calibrated realistic head modeling.

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