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International Journal of Clinical Medicine and Bioengineering
Frequency: Quarterly Published by lIKll

Open Access
 IJCMB 2021/12
Vol.1, Iss.1 : 53-62

Measuring Electromagnetic Oscillatory Brainwaves and Networks: Methodological Considerations

Chun-Chuan Chen1, Karl J. Friston2 and Po-Lei Lee3*

1Department of Biomedical Sciences and Engineering, National Central University, Taoyuan, Taiwan
2The Wellcome Department of Cognitive Neurology, Institute of Neurology, Queen Square, London, United Kingdom
3Department of Electrical Engineering, National Central University, Taoyuan, Taiwan

Received:N/A; Revised:N/A; Accepted:N/A; Published:December 30, 2021
Ever since the first discovery of human brain waves in 1929, brain rhythm has been attracting interest in the field of neuroscience. The integration of distributed brain functions similar to small-scale circuits for the same task in a larger scale network which oscillations facilitate offers a means to study the brain at work. Importantly, changes in synchronized brain oscillations may reveal important aspects of pathophysiology. For example, excess beta rhythms are characteristic of Parkinson's brain. However, various spatial distributions and frequencies of neuronal oscillations and nonlinear and complicated neuronal processes make it difficult to understand neuronal messages, and it is needed to find an appropriate model. Thus, we present a brief review of techniques used in characterizing frequency-related local fluctuations and interactions between neuronal assemblies by measuring electroencephalography (EEG) or MEG. Specifically, we focus on the objectives of these methods, including: (1) inferential versus non-inferential, (2) linear versus nonlinear, (3) uni-versus multi-variate, and (4) power modulation versus phase-synchrony. Three practical issues – that are typically confronted when applying these methods – are also discussed. This article aims to provide readers who are not familiar with current methods an accessible overview – that may help the neuroscientists to interpret the similar findings of this study.

Keywords:  Oscillations, Brainwaves, Networks; MEG, EEG, Analytic Method, Connectivity, Synchronization

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Citation:Chen, C.C.; J., K.; Lee, P.L.Measuring Electromagnetic Oscillatory Brainwaves and Networks: Methodological Considerations. International Journal of Clinical Medicine and Bioengineering 2021, 1, 53-62.

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Copyright: © 2021  The Author(s). Published with license by IIKII, Singapore. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.