Effect of structural complexities in head modeling on the accuracy of EEG source localization in neonates

Significance 

Monitoring cognitive functions using advanced networks has started to play a pivotal role in understanding neuroscientific data. Moreover, studies assessing interregional functional and effective connectivity have become staples of the neuroimaging literature. Of the many techniques available, electroencephalography (EEG) has been widely used as a non-invasive technique to investigate brain functional activities under physiological and pathological conditions such as epilepsy, psychiatric and developmental disorders. Technically, EEG monitoring technique involves recording the brain’s electrical activity. Over the past few decades, EEG has widely advanced credit to the development of EEG source localization that aid by localizing the underlying sources of brain activity. In adults, errors pertaining to head modeling have been acknowledged to build up to several centimeters and in return, the accuracy of source localization has been extensively investigated. Previous studies have investigated skull segmentation using region growing, thresholding and morphological operations. Nonetheless, few studies have investigated the effect of head modeling errors on EEG/ magnetoencephalography forward and inverse modeling in full term.

French researchers at the Université de Picardie Jules Verne: Dr. Hamed Azizollahi, Dr. Ardalan Aarabi and led by Professor Fabrice Wallois previously performed a sensitivity analysis to investigate the effect of inaccuracies in geometry and electrical properties of different neonatal head tissues on EEG forward solutions. Their results demonstrated the impact of modeling cerebrospinal fluid, fontanels, gray matter and white matter on EEG forward solutions.  In an new study, Professor Fabrice Wallois and his team proposed to advance on their prior study by performing numerical simulations to investigate the effect of head modeling errors including cerebrospinal fluid and fontanel exclusion and gray/white matter distinction on the accuracy of EEG source localization in full term neonates. Their work is currently published in the Journal of Neural Engineering.

In their approach, simulations were performed by distributing dipole sources over the entire cortex, oriented normally to the surface of the cortex. Scalp potentials were calculated by using finite element volume conductor head models generated as reference and test models. The researchers further explored the relationship between forward solutions and source localization errors caused by each effect to investigate the extent to which localization errors could be predicted from forward modeling errors.

Their results showed that the exclusion of cerebrospinal fluid from the head model could cause significant localization errors mostly for sources closer to the inner surface of the skull. With a less pronounced effect compared to the cerebrospinal fluid exclusion, the discrimination between grey and white matter also widely affected all sources, especially those located in deeper structures. The exclusion of the fontanels from the head model led to source localization errors for sources located in areas beneath the fontanels. In addition, their findings clearly showed that the cerebrospinal fluid inclusion and grey/white matter distinction in EEG inverse modeling can substantially reduce EEG source localization errors. Moreover, fontanels should be included in neonatal head models, particularly in source localization applications, in which sources of interest are located beneath or in vicinity of fontanels.

In summary, the study presented an in-depth investigation of the effect of exclusion of cerebrospinal fluid and fontanels, and grey/white matter distinction on the accuracy of EEG source localization in neonates. Remarkably, the finding outlined have practical implications for a better understanding of the impact of head model complexities on the accuracy of EEG source localization in neonates. In a statement to Advances in Engineering, Professor Fabrice Wallois mentioned that their finding highlighted on the importance of head model structural complexities on EEG source localization in neonates.

Effect of structural complexities in head modeling on the accuracy of EEG source localization in neonates - Advances in Engineering

Reference

Hamed Azizollahi, Ardalan Aarabi, Fabrice Wallois. Effect of structural complexities in head modeling on the accuracy of EEG source localization in neonates. Journal of Neural Engineering: volume 17 (2020) 056004.

Go To Journal of Neural Engineering

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