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IBEC Seminar: Ralph G. Andrzejak
Tuesday, February 3, 2015 @ 10:00 am–11:00 am
Application of nonlinear signal analysis to electroencephalographic recordings from epilepsy patients
Tenure Associate Professor · Department of Information and Communication Technologies · Universitat Pompeu Fabra
Nonlinear time series analysis allows characterizing dynamical systems in which nonlinearity gives rise to a complex, seemingly irregular temporal evolution. Importantly, these nonlinear techniques can extract information from real-world experimental signals that cannot be resolved by classical linear techniques, such as spectral analysis. Nonlinear time series analysis can, for example, help to discriminate nonlinear deterministic and linear stochastic dynamics or to characterize directional interactions between dynamics. In application to signals measured from the brain, this analysis can contribute to the understanding of brain functions and dysfunctions. It can thereby advance cognitive neuroscience and neurology.
In this seminar, I will at first illustrate some fundamental concepts of nonlinear time series analysis. Subsequently, we will review some basic facts about the disease epilepsy, epilepsy surgery and intracranial electroencephalographic recordings (EEG) from epilepsy patients. I will then show an application of nonlinear time series analysis to EEG recordings from the seizure-free interval of epilepsy patients undergoing pre-surgical diagnostics. Results of this application allowed us to localize the seizure generating brain area without the necessity of observing actual seizure activity – a finding of clear clinical relevance.