| Issue |
EPJ Nonlinear Biomed. Phys.
Volume 5, 2017
|
|
|---|---|---|
| Article Number | 2 | |
| Number of page(s) | 16 | |
| Section | Physics of Biological Systems and Their Interactions | |
| DOI | https://doi.org/10.1051/epjnbp/2017001 | |
| Published online | 30 June 2017 | |
https://doi.org/10.1051/epjnbp/2017001
Review
Capturing time-varying brain dynamics
1
Department of Epileptology, University of Bonn,
Sigmund-Freud-Straße 25,
53105
Bonn, Germany
2
Helmholtz-Institute for Radiation and Nuclear Physics, University of Bonn,
Nussallee 14–16,
53115
Bonn, Germany
3
Interdisciplinary Center for Complex Systems, University of Bonn,
Brühler Straße 7,
53175
Bonn, Germany
* e-mail: klaus.lehnertz@ukbonn.de
Received:
16
December
2016
Accepted:
4
May
2017
Published online: 30 June 2017
The human brain is a complex network of interacting nonstationary subsystems, whose complicated spatial–temporal dynamics is still poorly understood. Deeper insights can be gained from recent improvements of time-series-analysis techniques to assess strength and direction of interactions together with methodologies for deriving and characterizing evolving networks from empirical time series. We here review these developments, and by taking the example of evolving epileptic brain networks, we discuss the progress that has been made in capturing and understanding brain dynamics that varies on time scales ranging from seconds to years.
Key words: brain dynamics / evolving networks / synchronization / nonstationarity / direct/indirect interactions / network characteristics / time-series analysis / EEG / epilepsy
© K. Lehnertz et al., published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.