Abstract
The use of mathematical models for electroencephalography (EEG) analysis has been going on for many years, and currently they are starting to find a place both in clinical practice and in parallel with other methods for evaluation of brain activity. The use and interpretation of these methods are not possible without knowledge of the basic mechanisms and processes that underlie the results obtained from their application. The advantages of the quantitative methods, the processes underlying their presentation, and the optimal parameters used, such as the number of electrodes and time intervals, have been evaluated. Attention has been paid to the advantages of the individual possibilities for EEG signal analysis—absolute and relative power as well as coherence. An analysis of these defined quantities provides an opportunity to enter into the intimate mechanisms underlying specific psychopathological phenomena.
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Panov, G. (2023). Quantitative EEG Analysis: Introduction and Basic Principles. In: Stoyanov, D., Draganski, B., Brambilla, P., Lamm, C. (eds) Computational Neuroscience. Neuromethods, vol 199. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3230-7_5
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DOI: https://doi.org/10.1007/978-1-0716-3230-7_5
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