ArticleFrontiers in psychiatry2022
EEG-FCV: An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 8 citations in OpenAlex.
- Enhanced diagnostics for generalized anxiety disorder: leveraging differential channel and functional connectivity features based on frontal EEG signals.Scientific reports · 2024Article
- Augmented Recognition of Distracted Driving State Based on Electrophysiological Analysis of Brain Network.Cyborg and bionic systems (Washington, D.C.) · 2024Article
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8 authors at 2 institutions in 1 country.
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Abstract
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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