Name
Title | ||
|---|---|---|
Characterization of network structure in stereoEEG data using consensus-based partial coherence. |
Abstract | ||
|---|---|---|
Coherence is a widely used measure to determine the frequency-resolved functional connectivity between pairs of recording sites, but this measure is confounded by shared inputs to the pair. To remove shared inputs, the ‘partial coherence’ can be computed by conditioning the spectral matrices of the pair on all other recorded channels, which involves the calculation of a matrix (pseudo-) inverse. It has so far remained a challenge to use the time-resolved partial coherence to analyze intracranial recordings with a large number of recording sites. For instance, calculating the partial coherence using a pseudoinverse method produces a high number of false positives when it is applied to a large number of channels. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.neuroimage.2018.06.011 | NeuroImage |
Keywords | Field | DocType |
Coherence,Partial coherence,Consensus,Connectivity | Inverse,Network dynamics,Pattern recognition,Matrix (mathematics),Permutation,Moore–Penrose pseudoinverse,Psychology,Cognitive psychology,Communication channel,Coherence (physics),Artificial intelligence,False positive paradox | Journal |
Volume | ISSN | Citations |
179 | 1053-8119 | 0 |
PageRank | References | Authors |
0.34 | 16 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marije ter Wal | 1 | 4 | 1.18 |
| Pasquale Cardellicchio | 2 | 0 | 0.34 |
| Giorgio Lo Russo | 3 | 38 | 5.89 |
| Veronica Pelliccia | 4 | 2 | 1.41 |
| P Avanzini | 5 | 0 | 0.68 |
| Guy A. Orban | 6 | 17 | 1.10 |
| Paul H. E. Tiesinga | 7 | 4 | 0.84 |