Nonlinear Recurrent Dynamics and Long-Term Nonstationarities in EEG Alpha Cortical Activity: Implications for Choosing Adequate Segment Length in Nonlinear EEG Analyses
| Autor: | Cerquera, Alexander, Vollebregt, Madelon A., Arns, Martijn, Afd Psychologische functieleer, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF) |
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| Přispěvatelé: | Afd Psychologische functieleer, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Male
02 engineering and technology Electroencephalography NEURAL NETWORK METHODOLOGY 0302 clinical medicine DETERMINISM EEG recurrence rate Mathematics medicine.diagnostic_test Epoch (reference date) Dynamics (mechanics) Segment length Brain Signal Processing Computer-Assisted General Medicine Middle Aged scaling index DEPRESSION SHORT-TIME SERIES WAVELET-CHAOS METHODOLOGY EEG nonstationarities Neurology Female Eeg alpha Adult 0206 medical engineering Clinical Neurology Alpha (ethology) DIAGNOSIS Time 03 medical and health sciences Young Adult medicine SEIZURE Humans FRACTALITY cortical oscillations Aged Depressive Disorder Major COMPLEXITY EEG signal processing business.industry Pattern recognition 020601 biomedical engineering Lempel-Ziv complexity Term (time) Nonlinear system Nonlinear Dynamics Neurology (clinical) Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | Clinical EEG and Neuroscience, 49(2), 71. SAGE Publications Inc. Clinical Eeg and Neuroscience, 49(2), 71-78. EEG and Clinical Neuroscience Society (ECNS) |
| ISSN: | 1550-0594 |
| Popis: | Nonlinear analysis of EEG recordings allows detection of characteristics that would probably be neglected by linear methods. This study aimed to determine a suitable epoch length for nonlinear analysis of EEG data based on its recurrence rate in EEG alpha activity (electrodes Fz, Oz, and Pz) from 28 healthy and 64 major depressive disorder subjects. Two nonlinear metrics, Lempel-Ziv complexity and scaling index, were applied in sliding windows of 20 seconds shifted every 1 second and in nonoverlapping windows of 1 minute. In addition, linear spectral analysis was carried out for comparison with the nonlinear results. The analysis with sliding windows showed that the cortical dynamics underlying alpha activity had a recurrence period of around 40 seconds in both groups. In the analysis with nonoverlapping windows, long-term nonstationarities entailed changes over time in the nonlinear dynamics that became significantly different between epochs across time, which was not detected with the linear spectral analysis. Findings suggest that epoch lengths shorter than 40 seconds neglect information in EEG nonlinear studies. In turn, linear analysis did not detect characteristics from long-term nonstationarities in EEG alpha waves of control subjects and patients with major depressive disorder patients. We recommend that application of nonlinear metrics in EEG time series, particularly of alpha activity, should be carried out with epochs around 60 seconds. In addition, this study aimed to demonstrate that long-term nonlinearities are inherent to the cortical brain dynamics regardless of the presence or absence of a mental disorder. |
| Databáze: | OpenAIRE |
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