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search.filters.applied.f.access: openAccess × Author: Kurths, J. × End date: 2019 × Start date: 2010 × Subject: human × Subject: mathematical model × WGL Institute: PIK ×

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Now showing 1 - 3 of 3
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    Order patterns networks (orpan) - A method to estimate time-evolving functional connectivity from multivariate time series
    (Lausanne : Frontiers Research Foundation, 2012) Schinkel, S.; Zamora-López, G.; Dimigen, O.; Sommer, W.; Kurths, J.
    Complex networks provide an excellent framework for studying the function of the human brain activity. Yet estimating functional networks from measured signals is not trivial, especially if the data is non-stationary and noisy as it is often the case with physiological recordings. In this article we propose a method that uses the local rank structure of the data to define functional links in terms of identical rank structures. The method yields temporal sequences of networks which permits to trace the evolution of the functional connectivity during the time course of the observation. We demonstrate the potentials of this approach with model data as well as with experimental data from an electrophysiological study on language processing.
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    Cortical hot spots and labyrinths: Why cortical neuromodulation for episodic migraine with aura should be personalized
    (Lausanne : Frontiers Research Foundation, 2015) Dahlem, M.A.; Schmidt, B.; Bojak, I.; Boie, S.; Kneer, F.; Hadjikhani, N.; Kurths, J.
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    Towards dynamical network biomarkers in neuromodulation of episodic migraine
    (Berlin : De Gruyter, 2013) Dahlem, M.A.; Rode, S.; May, A.; Fujiwara, N.; Hirata, Y.; Aihara, K.; Kurths, J.
    Computational 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.