Name
Title | ||
|---|---|---|
Predicting EEG single trial responses with simultaneous fMRI and relevance vector machine regression. |
Abstract | ||
|---|---|---|
The combination of electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) has been proposed as a tool to study brain dynamics with both high temporal and high spatial resolution. Integration through EEG-fMRI trial-by-trial coupling has been proposed as a method to combine the different data sets and achieve temporal expansion of the fMRI data (Eichele et al., 2005). To fully benefit of this type of analysis simultaneous EEG-fMRI acquisitions are necessary (Debener et al., 2006). |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.neuroimage.2010.07.068 | NeuroImage |
Keywords | Field | DocType |
mental imagery,time series prediction,electroencephalography,relevance vector machine,multivariate regression | Pattern recognition,Functional magnetic resonance imaging,Regression,Multivariate statistics,Psychology,Mental image,Artificial intelligence,Relevance vector machine,Cognition,EEG-fMRI,Electroencephalography | Journal |
Volume | Issue | ISSN |
56 | 2 | 1053-8119 |
Citations | PageRank | References |
10 | 0.63 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Federico De Martino | 1 | 325 | 20.34 |
| Aline W. de Borst | 2 | 12 | 1.71 |
| Giancarlo Valente | 3 | 127 | 10.62 |
| Rainer Goebel | 4 | 110 | 8.39 |
| Elia Formisano | 5 | 778 | 58.91 |