Measuring Large-Scale Synchronization with Human MEG and EEG

Challenges and Solutions

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Abstract

Specific kinds of neuronal interactions, such as phase coupling of neuronal oscillations, are likely to be essential systems-level mechanisms for coordinating neuronal communication, integration, and segregation. The functional roles of these interactions during cognitive tasks in healthy humans can be investigated with magneto- and electroencephalography (MEG/EEG), the only means for noninvasive electrophysiological recordings of human cortical activity. While advances in source modeling have opened new avenues for assessing inter-areal interactions with MEG/EEG, several factors limit the accuracy and inferential value of such analyses. In this chapter, we provide an overview of common source analysis strategies for mapping inter-areal interactions with MEG/EEG. Linear mixing between sources, as caused by volume conduction and signal mixing, is the principal confounder in connectivity analysis and always leads to false positive observations. We discuss the sensitivity of different interaction metrics to directly and indirectly caused false positives and conclude with approaches to mitigate these problems. In conclusion, MEG and EEG are becoming increasingly useful for assessing inter-areal neuronal interaction in humans.
Original languageEnglish
Title of host publicationMultimodal Oscillation-based Connectivity Theory
EditorsSatu Palva
Number of pages18
Place of PublicationCham
PublisherSpringer International Publishing
Publication dateJan 2016
Pages1-18
ISBN (Print)978-3-319-32263-6
ISBN (Electronic)978-3-319-32265-0
DOIs
Publication statusPublished - Jan 2016
MoE publication typeA3 Book chapter

Fields of Science

  • 3112 Neurosciences

Cite this

Siebenhuhner, F., Lobier, M. A. M., Wang, S. H., Palva, S. O., & Palva, J. M. (2016). Measuring Large-Scale Synchronization with Human MEG and EEG: Challenges and Solutions. In S. Palva (Ed.), Multimodal Oscillation-based Connectivity Theory (pp. 1-18). Cham: Springer International Publishing . https://doi.org/10.1007/978-3-319-32265-0_1
Siebenhuhner, Felix ; Lobier, Muriel Anne Marie ; Wang, Sheng Hua ; Palva, Satu Orvokki ; Palva, Jaakko Matias. / Measuring Large-Scale Synchronization with Human MEG and EEG : Challenges and Solutions. Multimodal Oscillation-based Connectivity Theory. editor / Satu Palva. Cham : Springer International Publishing , 2016. pp. 1-18
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Siebenhuhner, F, Lobier, MAM, Wang, SH, Palva, SO & Palva, JM 2016, Measuring Large-Scale Synchronization with Human MEG and EEG: Challenges and Solutions. in S Palva (ed.), Multimodal Oscillation-based Connectivity Theory. Springer International Publishing , Cham, pp. 1-18. https://doi.org/10.1007/978-3-319-32265-0_1

Measuring Large-Scale Synchronization with Human MEG and EEG : Challenges and Solutions. / Siebenhuhner, Felix; Lobier, Muriel Anne Marie; Wang, Sheng Hua; Palva, Satu Orvokki; Palva, Jaakko Matias.

Multimodal Oscillation-based Connectivity Theory. ed. / Satu Palva. Cham : Springer International Publishing , 2016. p. 1-18.

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

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AU - Palva, Jaakko Matias

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AB - Specific kinds of neuronal interactions, such as phase coupling of neuronal oscillations, are likely to be essential systems-level mechanisms for coordinating neuronal communication, integration, and segregation. The functional roles of these interactions during cognitive tasks in healthy humans can be investigated with magneto- and electroencephalography (MEG/EEG), the only means for noninvasive electrophysiological recordings of human cortical activity. While advances in source modeling have opened new avenues for assessing inter-areal interactions with MEG/EEG, several factors limit the accuracy and inferential value of such analyses. In this chapter, we provide an overview of common source analysis strategies for mapping inter-areal interactions with MEG/EEG. Linear mixing between sources, as caused by volume conduction and signal mixing, is the principal confounder in connectivity analysis and always leads to false positive observations. We discuss the sensitivity of different interaction metrics to directly and indirectly caused false positives and conclude with approaches to mitigate these problems. In conclusion, MEG and EEG are becoming increasingly useful for assessing inter-areal neuronal interaction in humans.

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Siebenhuhner F, Lobier MAM, Wang SH, Palva SO, Palva JM. Measuring Large-Scale Synchronization with Human MEG and EEG: Challenges and Solutions. In Palva S, editor, Multimodal Oscillation-based Connectivity Theory. Cham: Springer International Publishing . 2016. p. 1-18 https://doi.org/10.1007/978-3-319-32265-0_1