Name
Abstract | ||
|---|---|---|
In [1], we developed two methods to automatically identify the contribution of the recording reference signal from multi-channel intracranial Electroencephalography (iEEG) recordings. In this study, we subtract the reference recording contribution to iEEG and obtain corrected iEEG. We then investigate three commonly used iEEG metrics: spectral power, phase synchrony, and magnitude squared coherence (MSC) for common referential iEEG, corrected iEEG and bipolar montage iEEG. We find significant differences among the three iEEG metrics, and are able to determine the contribution from the recording reference to each metric. Generally, reference signals with smaller amplitude yield lower phase synchrony and reference signals with larger amplitude increase phase synchrony. Reference signals with spectral peaks increase coherence. Reference signal with low power may have no significant impact on calculated coherence. Bipolar EEG usually yields small phase synchrony or MSC values and may obscure the actual phase synchrony or MSC values between two local sources. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72393-6_150 | ISNN (2) |
Keywords | Field | DocType |
ieeg metrics,actual phase synchrony,bipolar montage ieeg,recording reference,common referential ieeg,reference signal,recording reference signal,reference recording contribution,corrected ieeg,msc value,phase synchrony,electroencephalography | Magnitude squared coherence,Pattern recognition,Computer science,Coherence (physics),Spectral density,Artificial intelligence,Intracranial Electroencephalography,Independent component analysis,Amplitude,Electroencephalography | Conference |
Volume | ISSN | Citations |
4492 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanqing Hu | 1 | 452 | 42.72 |
| Matt Stead | 2 | 36 | 4.65 |
| Andrew B. Gardner | 3 | 84 | 8.02 |
| Gregory A Worrell | 4 | 107 | 18.00 |