Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/EBAC8433-7951-4E1B-97EE-83357C9E6CCE | ||
| Year | 2012 | ||
| Type of Item | Μεταπτυχιακή Διατριβή | ||
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| Bibliographic Citation | Vasiliki Iordanidou, "Time-frequency analysis of ongoing and event related potentials", Master Thesis, Department of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2012 https://doi.org/10.26233/heallink.tuc.13708 | ||
| Appears in Collections |
During the past few years there has been an increasing interest in studying andunderstanding the neural mechanisms behind cognitive brain activity. This kind ofknowledge is of great importance in many scientific areas such as clinical prognosis and diagnosis, brain computer interfaces design, etc. In this context, various methodological approaches have been suggested for the analysis of the EEG signal, which is one of the most widely used brain representations.This work explores two different approaches for the EEG analysis. In the firstapproach there is a case of ongoing EEG in which we use the power spectrum (PS) and linear coherence (LC) in order to investigate the differences in the channel activations for two mathematical thinking tasks. The goal in this case is to identify differences between the mathematical tasks through the measures of PS and LC and evaluate them through statistical testing. In the second approach there is a case of evoked EEG from a working memory experiment on which populations of control and dyslexic subjects participate. In this case, various synchronization measures are applied on the time-frequency (TF) maps of the corresponding independent components (ICs). Those measures were very important for the evaluation of the components and helped us recognize a number different cases for the generation of our ERPs. We also tried to identify differences between the two populations overall activation comparing the TF maps of the synchronizations measures and evaluate them through statistical testing. For both datasets, we had findings with statistical significance which also are in support and complementary to previous research.
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