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Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

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DMV Tagung 2011 - <strong>Köln</strong>, 19. - 22. September<br />

Ann-Katrin Becher<br />

<strong>Universität</strong> <strong>zu</strong> <strong>Köln</strong><br />

Phase Synchronization in a network of inhibitory and excitatory coupled oscillators<br />

The phenomenon of phase synchronization plays a crucial role in many systems of biology, physics and<br />

neurosciences which can be modelled by phase coupled oscillators. One popular model that exhibits<br />

phase synchronization is the Kuramoto system.<br />

In this talk a similar model of phase coupled oscillators is introduced describing a network with both<br />

excitatory and inhibitory interactions. The phase dynamics are modelled by a Kuramoto-like system<br />

without symmetries with regard to coupling. The coexistence of inhibitory and excitatory interactions and<br />

the asymmetry of coupling give rise to several different scenarios of synchronization. Excitatory coupling<br />

can result in “in phase” oscillations. In contrast inhibitory coupled oscillators tend to oscillate “anti-phase”.<br />

Therefore a combination of both types of coupling can lead to transitional states or coexistence of stable<br />

in phase and anti-phase oscillations. In the talk the phase model is introduced and some of the results<br />

concerning the excitatory-inhibitory-synchronization behavior are presented.<br />

Sevda Ça ˘gırıcı<br />

Mathematical <strong>Institut</strong>e, University of Cologne<br />

Amplitude Dynamics in the Model of Two Nonlinear Coupled Oscillators<br />

We analyse a system of two nonlinear coupled oscillators describing amplitude and phase dynamics,<br />

which can be seen as a four dimensional model of two neurons. The major point of our investigations is to<br />

study the influence of the inhibitory synaptic coupling between neurons upon the amplitude dynamics. In<br />

addition we show some results of our model with external stimulus which corresponding to real EEG-Data<br />

from auditory processing in shizophrenia.<br />

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