Feedback control of complex oscillatory systems
In the present dissertation paper an approach which ensures an efficient control of such diverse systems as noisy or chaotic oscillators and neural ensembles is developed. This approach is implemented by a simple linear feedback loop. The dissertation paper consists of two main parts. One part of the work is dedicated to the application of the suggested technique to a population of neurons with a goal to suppress their synchronous collective dynamics. The other part is aimed at investigating linear feedback control of coherence of a noisy or chaotic self-sustained oscillator. First we start with a problem of suppressing synchronization in a large population of interacting neurons. The importance of this task is based on the hypothesis that emergence of pathological brain activity in the case of Parkinson's disease and other neurological disorders is caused by synchrony of many thousands of neurons. The established therapy for the patients with such disorders is a permanent high-frequency electrical stimulation via the depth microelectrodes, called Deep Brain Stimulation (DBS). In spite of efficiency of such stimulation, it has several side effects and mechanisms underlying DBS remain unclear. In the present work an efficient and simple control technique is suggested. It is designed to ensure suppression of synchrony in a neural ensemble by a minimized stimulation that vanishes as soon as the tremor is suppressed. This vanishing-stimulation technique would be a useful tool of experimental neuroscience; on the other hand, control of collective dynamics in a large population of units represents an interesting physical problem. The main idea of suggested approach is related to the classical problem of oscillation theory, namely the interaction between a self-sustained (active) oscillator and a passive load (resonator). It is known that under certain conditions the passive oscillator can suppress the oscillations of an active one. In this thesis a much more complicated case of active medium, which itself consists of thousands of oscillators is considered. Coupling this medium to a specially designed passive oscillator, one can control the collective motion of the ensemble, specifically can enhance or suppress it. Having in mind a possible application in neuroscience, the problem of suppression is concentrated upon. Second, the efficiency of suggested suppression scheme is illustrated by considering more complex case, i.e. when the population of neurons generating the undesired rhythm consists of two non-overlapping subpopulations: the first one is affected by the stimulation, while the collective activity is registered from the second one. Generally speaking, the second population can be by itself both active and passive; both cases are considered here. The possible applications of suggested technique are discussed. Third, the influence of the external linear feedback on coherence of a noisy or chaotic self-sustained oscillator is considered. Coherence is one of the main properties of self-oscillating systems and plays a key role in the construction of clocks, electronic generators, lasers, etc. The coherence of a noisy limit cycle oscillator in the context of phase dynamics is evaluated by the phase diffusion constant, which is in its turn proportional to the width of the spectral peak of oscillations. Many chaotic oscillators can be described within the framework of phase dynamics, and, therefore, their coherence can be also quantified by the way of the phase diffusion constant. The analytical theory for a general linear feedback, considering noisy systems in the linear and Gaussian approximation is developed and validated by numerical results.
Rückkopplungskontrolle, Neuronale Synchronisation, globale Kupplung, Kohärenz, verrauschte Oszillatoren, Feedback control, Neuronal synchrony, Global coupling, Coherence, Noisy oscillators
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