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Computational EEG Analysis pp 125–145Cite as

Methods for Functional Connectivity Analysis

Part of the Biological and Medical Physics, Biomedical Engineering book series (BIOMEDICAL)

Abstract

The purpose of this chapter is to provide comprehensive and useful guidelines for the methods of the functional connectivity analysis (FCA) for electroencephalogram (EEG) and its application. After presenting the detailed procedure for the FCA, we described various methods for quantifying functional connectivity. The problem of volume conduction and the means to diminish its confounding effects on the FCA was thoroughly reviewed. As a useful preprocessing for the FCA, spatial filtering of the time-series measured on the scalp or transformation to current densities on cortical surface were described. We also reviewed ongoing efforts toward developing FC measures which are inherently robust to the volume conduction problem. Finally, we illustrated the procedures for determining significance of the FC among specific pair of regions, which exploit surrogate data generation or the characteristics of event-related data.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Yonsei University, Wonju, South Korea

    Jeong Woo Choi & Kyung Hwan Kim

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  1. Jeong Woo Choi
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Correspondence to Kyung Hwan Kim .

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

    Chang-Hwan Im

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Choi, J.W., Kim, K.H. (2018). Methods for Functional Connectivity Analysis. 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_6

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