Application of Brain Oscillations in Neuropsychiatric by E. Başar, C. Başar-Eroĝlu, A. Özerdem, P.M. Rossini and G.G.

By E. Başar, C. Başar-Eroĝlu, A. Özerdem, P.M. Rossini and G.G. Yener (Eds.)

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Additional resources for Application of Brain Oscillations in Neuropsychiatric Diseases: Selected Papers from “Brain Oscillations in Cognitive Impairment and Neurotransmitters” Conference, Istanbul, Turkey, 29 April–1 May 2011

Example text

Table 1 summarizes the methods included in the “systems theory” of brain-state analysis. , 2001a, b). Our group first applied the system theory methods to brain waves by using the conventional methods. , 2001). In addition to the systems theory methods, newly emerging methods of analyzing EROs include studies of nonlinearities and the incorporation of the concept of chaos, which aim to further increase understanding of the properties of the system. Among the applications described in the following sections, spectral signal analysis constitutes one of the most important and most commonly used analytical tools for the evaluation of neurophysiological signals.

5) This characteristic and the concept of response susceptibility led to the conclusion (6) (7) (8) (9) that the oscillatory activity that forms the EEG governs the most general transfer functions in the brain (Bas¸ar, 1990). Oscillatory neural tissues that are selectively distributed in the whole brain are activated upon sensory–cognitive input. The oscillatory activity of neural tissues may be described through a number of response parameters. Different tasks, and the functions that they elicit, are represented by different configurations of parameters.

C) It is also almost imperative to compute evoked or event-related power spectra before deciding on the application of adaptive digital filters. Depending on the type of cognitive tasks, event-related spectra can show modification in frequency windows of ERO. Most critical is the choice of frequency windows in cognitive impairment. Patients can show highly altered frequency windows or frequency shifts. The choice of rigid filters in conventional EEG bands can lead to errors. In this final part of the chapter, the outlined strategies, methods, and conclusions are based on experiences from our research group, related to AD, BD, and schizophrenia.

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