CC BY-NC-ND 3.0 UnportedDahlem, M.A.Rode, S.May, A.Fujiwara, N.Hirata, Y.Aihara, K.Kurths, J.2020-08-012020-08-012013https://doi.org/10.34657/3889https://oa.tib.eu/renate/handle/123456789/5260Computational methods have complemented experimental and clinical neurosciences and led to improvements in our understanding of the nervous systems in health and disease. In parallel, neuromodulation in form of electric and magnetic stimulation is gaining increasing acceptance in chronic and intractable diseases. In this paper, we firstly explore the relevant state of the art in fusion of both developments towards translational computational neuroscience. Then, we propose a strategy to employ the new theoretical concept of dynamical network biomarkers (DNB) in episodic manifestations of chronic disorders. In particular, as a first example, we introduce the use of computational models in migraine and illustrate on the basis of this example the potential of DNB as early-warning signals for neuromodulation in episodic migraine.enghttps://creativecommons.org/licenses/by-nc-nd/3.0/610BiomarkersCentral pattern generatorHodgkin-Huxley modelsMigraineNeuromodulationNonlinear dynamicsPainSpreading depressionbiological markerdynamical network biomarkerpotassium ionsodium ionunclassified drugbrain ischemiacentral pattern generatorchannel gatingchronic diseasedeteriorationdisease markerelectrostimulationepisodic migraineganglionHodgkin Huxley equationhumanion conductancemagnetic stimulationmathematical modelmembrane potentialmigraine with auramigraine without auranerve cell networkneuromodulationnonlinear systemphotophobiaprimary headachepriority journalprodromal symptompterygopalatine ganglionreviewspreading cortical depressionsuperior salivatory nucleustranscranial direct current stimulationtranscranial magnetic stimulationtranscutaneous nerve stimulationtransformed migraineArticle