Abstract
In this paper, different linear and nonlinear methodologies for the estimation of cortical connectivity from neuroelectric and hemodynamic measurements are reviewed and applied on common data set in order to highlight similarities and differences in the results. Different effective and functional connectivity methods were applied to motor and cognitive data sets, including structural equation modeling (SEM), directed transfer function (DTF), partial directed coherence (PDC), and direct directed transfer function (dDTF). Comparisons were made between the results in order to understand if, for a same dataset, effective and functional connectivity estimators can return the same cortical connectivity patterns. An application of a nonlinear method [phase synchronization index (PSI)] to similar executed and imagined movements was also reviewed. Connectivity patterns estimated with the use of the neuroelectric information and of the information from the multimodal integration of neuroelectric and hemodynamic data were also compared. Results suggests that the estimation of the cortical connectivity patterns performed with the linear methods (SEM, DTF, PDC, dDTF) or with the nonlinear method (PSI) on movement related potentials returned similar cortical networks. Differences in cortical connectivity were noted between the patterns estimated with the use of multimodal integration and those estimated by using only the neuroelectric data.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 224-233 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Volume | 17 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 2009 |
Bibliographical note
Funding Information:Manuscript received January 19, 2008; revised May 06, 2008; accepted June 01, 2008. First published December 09, 2008; current version published July 06, 2009. This work was supported in part by the National Science Foundation under Grant NSF BES-0411898 and in part by the National Institutes of Health under Grant NIH EB007920 and Grant NIH EB00178. This work was also supported in part by the Minister for Foreign Affairs, Division for Scientific and Technological Development, in the framework of a bilateral project between Italy and China, and the European COST Action NEUROMATH BM0601. This paper reflects only the authors’ views, and funding agencies are not liable for any use that may be made of the information contained herein.
Keywords
- Directed transfer function (DTF)
- Functional cortical connectivity
- High-resolution EEG
- Partial directed coherence (PDC)
- Structural equation modeling (SEM)