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Simultaneous EEG and fMRI: Recording, analysis, and application

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Ullsperger,  Markus
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Ullsperger, M., & Debener, S. (Eds.). (2010). Simultaneous EEG and fMRI: Recording, analysis, and application. Oxford: Oxford University Press. doi:10.1093/acprof:oso/9780195372731.001.0001.


Cite as: https://hdl.handle.net/21.11116/0000-0003-2559-0
Abstract
Systemic interactions in brain networks have been successfully studied in vivo using non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), for many years. The rate-limiting step, however, is that each method can only map selective aspects of brain function, while missing other key aspects. Furthermore, the inferences on neuronal processes and information flow are often rather indirect. By simultaneously combining both methods, the researcher is better able to make optimal use of their specific advantages while compensating for their disadvantages. In recent years, research has shifted and expanded, from demonstrating technical feasibility, to methodological issues of artifact control, new ways of analyzing and integrating data, and to applications for scientific and clinical questions. Combined EEG and fMRI methods now cover everything from physiological questions on the bases of the two recorded signals, to more specific questions on the mechanisms of certain cognitive and pathological functions like epileptic brain activity. Simultaneous EEG and fMRI provides the interested researcher with the tools to establish a simultaneous EEG-fMRI laboratory, as well as for those scientists who are interested in integrating electrophysiological and hemodynamic data. As evidenced by the diversity of topics presented, this is a dynamically developing field in which several approaches are being tested, validated, and compared. Chapters are dedicated to the physiological bases of the measured signals, technical setup, sources of artifacts and data de-noising, various approaches of data analysis and fusion, as well as applications. In addition, open questions and directions for future research are outlined.