title: Understanding migraine using dynamic network biomarkers.
abstract: BACKGROUND
  Mathematical modeling approaches are becoming ever more established in clinical neuroscience. They provide insight that is key to understanding complex interactions of network phenomena, in general, and interactions within the migraine-generator network, in particular.
  
  
  OBJECTIVE
  In this study, two recent modeling studies on migraine are set in the context of premonitory symptoms that are easy to confuse for trigger factors. This causality confusion is explained, if migraine attacks are initiated by a transition caused by a tipping point.
  
  
  CONCLUSIONS
  We need to characterize the involved neuronal and autonomic subnetworks and their connections during all parts of the migraine cycle if we are ever to understand migraine. We predict that mathematical models have the potential to dismantle large and correlated fluctuations in such subnetworks as a dynamic network biomarker of migraine.
authors.affiliation: Department of Physics, Nonlinear Dynamics, Cardiovascular Physics, Humboldt-Universität zu Berlin, Germany dahlem@physik.hu-berlin.de.
authors.forename: Markus A
authors.initials: MA
authors.lastname: Dahlem
authors.affiliation: Department of Physics, Nonlinear Dynamics, Cardiovascular Physics, Humboldt-Universität zu Berlin, Germany Potsdam Institute for Climate Impact Research, Germany Institute for Complex Systems and Mathematical Biology, University of Aberdeen, UK.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Kurths
authors.affiliation: Department of Neurology, Leiden University Medical Centre, the Netherlands.
authors.forename: Michel D
authors.initials: MD
authors.lastname: Ferrari
authors.affiliation: Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Japan.
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Aihara
authors.affiliation: Department of Aquatic Ecology & Water Quality Management, Wageningen University, the Netherlands.
authors.forename: Marten
authors.initials: M
authors.lastname: Scheffer
authors.affiliation: Center for Experimental Medicine, Department of Systems Neuroscience, Universitätsklinikum Hamburg-Eppendorf, Germany.
authors.forename: Arne
authors.initials: A
authors.lastname: May
mesh_terms: D015415:Biomarkers; D032882:Comprehension; D006801:Humans; D008881:Migraine Disorders / Q000175:diagnosis* / Q000523:psychology*; D008962:Models, Theoretical; D016571:Neural Networks, Computer
chemical_list: D015415:Biomarkers
keywords: Migraine; premonitory symptoms; tipping point; triggers