Frontiers in Psychiatry (Jul 2022)

EEG-FCV: An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation

  • Hong Zeng,
  • Hong Zeng,
  • Yanping Jin,
  • Qi Wu,
  • Deng Pan,
  • Feifan Xu,
  • Yue Zhao,
  • Hua Hu,
  • Wanzeng Kong,
  • Wanzeng Kong

DOI
https://doi.org/10.3389/fpsyt.2022.928781
Journal volume & issue
Vol. 13

Abstract

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Electroencephalogram (EEG)-based tools for brain functional connectivity (FC) analysis and visualization play an important role in evaluating brain cognitive function. However, existing similar FC analysis tools are not only visualized in 2 dimensions (2D) but also are highly prone to cause visual clutter and unable to dynamically reflect brain connectivity changes over time. Therefore, we design and implement an EEG-based FC visualization framework in this study, named EEG-FCV, for brain cognitive state evaluation. EEG-FCV is composed of three parts: the Data Processing module, Connectivity Analysis module, and Visualization module. Specially, FC is visualized in 3 dimensions (3D) by introducing three existing metrics: Pearson Correlation Coefficient (PCC), Coherence, and PLV. Furthermore, a novel metric named Comprehensive is proposed to solve the problem of visual clutter. EEG-FCV can also visualize dynamically brain FC changes over time. Experimental results on two available datasets show that EEG-FCV has not only results consistent with existing related studies on brain FC but also can reflect dynamically brain FC changes over time. We believe EEG-FCV could prompt further progress in brain cognitive function evaluation.

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