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Volume 2017, Article ID 9078541, 13 pages
Research Article

Monitoring Effective Connectivity in the Preterm Brain: A Graph Approach to Study Maturation

1Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
2imec, Leuven, Belgium
3Department of Development and Regeneration, Neonatal Intensive Care Unit, UZ Leuven, Leuven, Belgium
4Department of Development and Regeneration, Child Neurology, UZ Leuven, Leuven, Belgium

Correspondence should be addressed to M. Lavanga; eb.nevueluk.tase@agnavalm

Received 12 May 2017; Revised 28 July 2017; Accepted 6 September 2017; Published 17 October 2017

Academic Editor: Mirjana Popović

Copyright © 2017 M. Lavanga et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Ofelie De Wel, Mario Lavanga, Anneleen Dereymaeker, Katrien Jansen, Gunnar Naulaers, Alexander Caicedo Dorado, and Sabine van Huffel, “Complexity analysis of neonatal EEG using multiscale entropy: Applications in brain maturation and sleep stage classification,” Entropy, vol. 19, no. 10, 2017. View at Publisher · View at Google Scholar
  • Elizabeth Shumbayawonda, Alberto Fernández, Michael P. Hughes, and Daniel Abásolo, “Investigation of Changes in Causality Throughout Life—A Magnetoencephalogram Study Using Granger Causality and Transfer Entropy,” World Congress on Medical Physics and Biomedical Engineering 2018, vol. 68/2, pp. 233–236, 2018. View at Publisher · View at Google Scholar
  • De Wel, Caicedo, Jansen, Dereymaeker, Van Huffel, Lavanga, and Naulaers, “A brain-age model for preterm infants based on functional connectivity,” Physiological Measurement, vol. 39, no. 4, 2018. View at Publisher · View at Google Scholar