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Computational EEG Analysis pp 83–123Cite as

EEG Source Imaging and Multimodal Neuroimaging

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Abstract

During most common applications, the signals produced by cortical dipoles are detected at the scalp level. While these measurements can be highly informative and feature optimal temporal resolution, their spatial detection is hindered by the conduction through the tissues of the head. A deeper understanding of cortical sources can be provided by source imaging techniques. These methods first create mathematical models of the head, assigning appropriate properties to each layer. Brain activity is then calculated based on these assigned models and the observed EEG measurements, greatly improving the spatial resolution of EEG measurement and providing insights regarding otherwise hidden cortical dynamics. Source Imaging approaches can be further enhanced by integrating a second imaging modality. This is particularly useful with imaging methods that feature high spatial resolution or whose signals are not blurred by transduction. In the following chapter, we provide a detailed introduction to the general principles and basic algorithms of source imaging techniques. The discussion then expands to explore how other modalities can interact with these techniques to improve our results. At its conclusion, readers should have a good idea on how EEG data can be expanded to provide cortical insight.

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Authors and Affiliations

  1. Department of Biomedical Engineering, University of Houston, Houston, USA

    Yingchun Zhang

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  1. Yingchun Zhang
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  1. Department of Biomedical Engineering, Hanyang University, Seongdong-gu, Seoul, Korea (Republic of)

    Chang-Hwan Im

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Zhang, Y. (2018). EEG Source Imaging and Multimodal Neuroimaging. In: Im, CH. (eds) Computational EEG Analysis. Biological and Medical Physics, Biomedical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-0908-3_5

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