Name
Abstract | ||
|---|---|---|
There has been special interest lately in using graph theory to study brain networks, as it provides the theoretic and visualization means to study the ”disconnection syndrome” for schizophrenia. In this work we try to visualize the graphs derived from electroencephalografic (EEG) signals using several graph drawing techniques and incorporate them smoothly into an easy-to-use framework. The aim is to reveal and evaluate important properties of brain networks. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11946465_16 | ISBMDA |
Keywords | Field | DocType |
important property,disconnection syndrome,special interest,brain network,visualizing brain network,easy-to-use framework,graph theory,graph drawing | Graph theory,Graph drawing,Graph,Visualization,Computer science,Geometric networks,Theoretical computer science,Artificial intelligence,Machine learning,Graph (abstract data type),Schizophrenia,Electroencephalography | Conference |
Volume | ISSN | ISBN |
4345 | 0302-9743 | 3-540-68063-2 |
Citations | PageRank | References |
1 | 0.38 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Theofanis Oikonomou | 1 | 13 | 3.05 |
| Vangelis Sakkalis | 2 | 110 | 23.68 |
| Ioannis G. Tollis | 3 | 1240 | 162.75 |
| Sifis Micheloyannis | 4 | 14 | 4.00 |