Evolving networks in the human epileptic brain
arXiv:1309.4039 · doi:10.1016/j.physd.2013.06.009
Abstract
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.
In press (Physica D)
References in corpus (19)
- Recurrence Plots for the Analysis of Complex Systems
- Synchronization in complex networks
- From time series to complex networks: the visibility graph
- Network Physiology reveals relations between network topology and physiological function
- Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods
- Evolving functional network properties and synchronizability during human epileptic seizures
- Microtesla MRI of the human brain combined with MEG
- Efficient and exact sampling of simple graphs with given arbitrary degree sequence
- Inference of Time-Evolving Coupled Dynamical Systems in the Presence of Noise
- Generalized Bose-Fermi statistics and structural correlations in weighted networks
- Network synchronization: Spectral versus statistical properties
- From brain to earth and climate systems: Small-world interaction networks or not?
- Many Attractors, Long Chaotic Transients, and Failure in Small-World Networks of Excitable Neurons
- Rich-club vs rich-multipolarization phenomena in weighted networks
- Surrogate-assisted analysis of weighted functional brain networks
- Recurrent events of synchrony in complex networks of pulse-coupled oscillators
- Multistability, local pattern formation, and global collective firing in a small-world network of non-leaky integrate-and-fire neurons
- Link and subgraph likelihoods in random undirected networks with fixed and partially fixed degree sequence
- Inferring complex networks from time series of dynamical systems: Pitfalls, misinterpretations, and possible solutions
Cited by in corpus (20)
- Coupling functions: Universal insights into dynamical interaction mechanisms
- Understanding the dynamics of biological and neural oscillator networks through exact mean-field reductions: a review
- FitzHugh-Nagumo oscillators on complex networks mimic epileptic-seizure-related synchronization phenomena
- Assortative mixing in functional brain networks during epileptic seizures
- Centrality-based identification of important edges in complex networks
- Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data
- How important is the seizure onset zone for seizure dynamics?
- No evidence for critical slowing down prior to human epileptic seizures
- Can spurious indications for phase synchronization due to superimposed signals be avoided?
- Recurrence Quantification Analysis of Dynamic Brain Networks
- Assessing directionality and strength of coupling through symbolic analysis: an application to epilepsy patients
- Identifying delayed directional couplings with symbolic transfer entropy
- Identifying edges that facilitate the generation of extreme events in networked dynamical systems
- Ordinal methods for a characterization of evolving functional brain networks
- A perturbation-based approach to identifying potentially superfluous network constituents
- Delta-alpha cross-frequency coupling for different brain regions
- Complexity and irreducibility of dynamics on networks of networks
- Impact of lag information on network inference
- Comparative analysis of time irreversibility and amplitude irreversibility based on joint permutation
- Identification of epileptic regions from electroencephalographic data: Feigenbaum graphs