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Summary and Conclusions The Fractal Dimensions of Function

We have shown computer models of biological rhythms in mood disorders and [Pg.222]

There are the very variable rhythms in the occurrence of disease episodes with considerable changes of disease intervals during the course of disease progression from years to months to weeks and even to days and hours. Such global behavioral rhythms are manifestations of the mental disease while the mood of mentally stable, healthy persons rather randomly fluctuates mainly following the environmental influences with mostly stochastic up and downs. [Pg.222]

We have emphasized the fact that the progression of mental diseases, especially major depression, is associated with significant disturbances in the circadian rhythms of autonomous functions, especially sleep-wake cycles and hormone release. These rhythms are naturally occurring but are distorted in affective disorders. The most clear distortions are often seen in the ultradian components in specific phases of the circadian cycle, e.g. in the morning peak of cortisol release or in the REM to nonREM transition during the sleep state. [Pg.222]

We have considered that all these systems are under neuronal control. While the relation between neural activity and different mood states is unknown so far, it is well established that physiologically relevant transitions in autonomous functions like sleep-wake cycles and cortisol release are associated with signifi- [Pg.222]

We have shown computer simulations from all these different levels First, we modeled the time course of affective disorders and showed that clinical observation can be mimicked in remarkable details with a combination of oscillatory dynamics and noise. Second, we presented an initial, still very basic, model of circadian cortisol release which nevertheless provided new insights also into eventual disease relevant alterations. Third, we showed single neuron and neuronal network simulations to elucidate the relevant interdependencies between ionic conductances and network interactions with regard to neuronal synchronization at different dynamic, also heterogeneous states. [Pg.223]


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