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Real-time estimation of dynamic functional connectivity networks.
- Source :
- Human Brain Mapping; Jan2017, Vol. 38 Issue 1, p202-220, 19p
- Publication Year :
- 2017
-
Abstract
- Two novel and exciting avenues of neuroscientific research involve the study of task-driven dynamic reconfigurations of functional connectivity networks and the study of functional connectivity in real-time. While the former is a well-established field within neuroscience and has received considerable attention in recent years, the latter remains in its infancy. To date, the vast majority of real-time fMRI studies have focused on a single brain region at a time. This is due in part to the many challenges faced when estimating dynamic functional connectivity networks in real-time. In this work, we propose a novel methodology with which to accurately track changes in time-varying functional connectivity networks in real-time. The proposed method is shown to perform competitively when compared to state-of-the-art offline algorithms using both synthetic as well as real-time fMRI data. The proposed method is applied to motor task data from the Human Connectome Project as well as to data obtained from a visuospatial attention task. We demonstrate that the algorithm is able to accurately estimate task-related changes in network structure in real-time. Hum Brain Mapp 38:202-220, 2017. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10659471
- Volume :
- 38
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Human Brain Mapping
- Publication Type :
- Academic Journal
- Accession number :
- 120127422
- Full Text :
- https://doi.org/10.1002/hbm.23355