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Impact of skull sutures, spongiform bone distribution, and aging skull conductivities on the EEG forward and inverse problems

McCann, Hannah May and Beltrachini, Leandro 2022. Impact of skull sutures, spongiform bone distribution, and aging skull conductivities on the EEG forward and inverse problems. Journal of Neural Engineering 19 , 016014. 10.1088/1741-2552/ac43f7

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Abstract

Source imaging is a principal objective for electroencephalography (EEG), the solutions of which require forward problem (FP) computations characterising the electric potential distribution on the scalp due to known sources. Additionally, the EEG-FP is dependent upon realistic, anatomically correct volume conductors and accurate tissue conductivities, where the skull is particularly important. Skull conductivity, however, deviates according to bone composition and the presence of adult sutures. The presented study therefore analyses the effect the presence of adult sutures and differing bone composition have on the EEG-FP and inverse problem (IP) solutions. Utilising a well-established head atlas, detailed head models were generated including compact and spongiform bone and adult sutures. The true skull conductivity was considered as inhomogeneous according to spongiform bone proportion and sutures. The EEG-FP and EEG-IP were solved and compared to results employing homogeneous skull models, with varying conductivities and omitting sutures, as well as using a hypothesised aging skull conductivity model. Significant localised FP errors, with relative error up to 85%, were revealed, particularly evident along suture lines and directly related to the proportion of spongiform bone. This remained evident at various ages. Similar EEG-IP inaccuracies were found, with the largest (maximum 4.14 cm) across suture lines. It is concluded that modelling the skull as an inhomogeneous layer that varies according to spongiform bone proportion and includes differing suture conductivity is imperative for accurate EEG-FP and source localisation calculations. Their omission can result in significant errors, relevant for EEG research and clinical diagnosis.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Physics and Astronomy
Additional Information: Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.
Publisher: IOP Publishing
ISSN: 1741-2560
Date of First Compliant Deposit: 7 January 2022
Date of Acceptance: 16 December 2021
Last Modified: 22 Feb 2022 13:48
URI: https://orca.cardiff.ac.uk/id/eprint/146454

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