Name
Abstract | ||
|---|---|---|
The electroencephalogram (EEG) is an electrophysiological monitoring method that allows us to glimpse the electrical activity of the brain. Neural oscillations patterns are perhaps the best salient feature of EEG as they are rhythmic activities of the brain that can be generated by interactions across neurons. Large-scale oscillations can be measured by EEG as the different oscillation patterns reflected within the different frequency bands, and can provide us with new insights into brain functions. In order to understand how information about the rhythmic activity of the brain during visuomotor/imagined cognitive tasks is encoded in the brain we precisely quantify the different features of the oscillatory patterns considering the Shannon-Fisher plane HxF. This allows us to distinguish the dynamics of rhythmic activities of the brain showing that the Beta band facilitate information transmission during visuomotor/imagined tasks. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/e20090660 | ENTROPY |
Keywords | Field | DocType |
EEG signals,brain oscillation patterns,bandt and pompe methodology,Fisher information and Shannon entropy | Pattern recognition,Artificial intelligence,Statistics,Electroencephalography,Mathematics,Motor imagery | Journal |
Volume | Issue | ISSN |
20 | 9 | 1099-4300 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Román Baravalle | 1 | 0 | 0.34 |
| Osvaldo A. Rosso | 2 | 58 | 13.07 |
| Fernando Montani | 3 | 10 | 2.09 |