Name
Title | ||
|---|---|---|
FCLAB: An EEGLAB module for performing functional connectivity analysis on single-subject EEG data |
Abstract | ||
|---|---|---|
Functional connectivity (FC) analysis constitutes a fundamental neuroscientific approach that has been extensively used for the investigation of brain's connectivity and activation patterns. To that end, several software tools have been developed. This paper presents FCLAB, the only EEGLAB-based plugin, which is able to work with EEG signals in order to estimate and visualize brain functional connectivity networks based on a variety of similarity measures as well as run a complete graph analysis procedure followed by a detailed visualization of the ensuing local and global measures distribution. FCLAB entails optimization procedures for the implementation of the connectivity structures and is the result of long-term research in EEG functional connectivity. The computed functional connectivity measures have been carefully selected to reflect the state-of-art in the field. Future work focuses on extending the platform for multi-subject analysis in order to enable the implementation of statistical analysis tools. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/BHI.2018.8333378 | 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) |
Keywords | Field | DocType |
EEG,functional connectivity analysis,graph analysis | Complete graph,Data mining,Visualization,Computer science,Power graph analysis,Coherence (physics),Software,Plug-in,Electroencephalography,EEGLAB | Conference |
ISBN | Citations | PageRank |
978-1-5386-2406-7 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vasileios C. Pezoulas | 1 | 0 | 0.34 |
| Alkinoos Athanasiou | 2 | 11 | 4.30 |
| G Nolte | 3 | 535 | 50.42 |
| Michalis E. Zervakis | 4 | 94 | 17.52 |
| Antonio Fratini | 5 | 0 | 0.34 |
| Dimitrios I. Fotiadis | 6 | 941 | 121.32 |
| Manousos A. Klados | 7 | 113 | 11.23 |