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- W2075134920 abstract "Nonlinear dynamics are currently proposed to explain the progressive course of recurrent mood disorders starting with isolated episodes and ending with accelerated irregular (“chaotic”) mood fluctuations. Such a low-dimensional disease model is attractive because of its principal accordance with biological models for affective disorders, i.e. the kindling and biological rhythms model. However, most natural systems are nonlinear and noisy and several studies in the neuro- and physical sciences have demonstrated interesting cooperative behaviors arising from interacting random and deterministic dynamics. In the present study we consider the effects of noise on a neurodynamical model for the timecourse of affective disorders (Huber et al.: Biological Psychiatry 1999;46:256–262). We describe noise effects on temporal patterns and mean episode frequencies of various in computo disease states. Our simulations demonstrate that noise can cause unstructured randomness or can maximize periodic order. The frequency of episode occurence can increase with noise but it can also remain unaffected or even can decrease. We show further that noise can make visible bifurcations before they would normally occur under deterministic conditions and we quantify this behavior with a recently developed statistical method (Omberg et al. 1999, preprint). All these effects depend critically on both, the dynamic state and the noise intensity. Implications for neurobiology and course of mood disorders are discussed." @default.
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- W2075134920 date "2000-04-01" @default.
- W2075134920 modified "2023-09-26" @default.
- W2075134920 title "236. Noise effects in a neurodynamical model for disease states of mood disorders" @default.
- W2075134920 doi "https://doi.org/10.1016/s0006-3223(00)00500-x" @default.
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