Abstract

Migraine is one of the primary headache disorders in a group of the ten most prevalent and disabling diseases. There are some valuable computational models of this disease which considered the onset and spatial patterns of migraine pain. Here we focus on dynamical transitions of this cyclic disease using the subnetworks which are essential in its complex network. Regarding the dynamical diseases theory, we propose a dynamical network biomarker for this disease that can predict the upcoming prodromal phase for clinical use. in this research, we use the bifurcation diagram as a tool to show the prediction of the model as the considered physiological parameter of the model changes. Copyright (C) EPLA, 2018