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dc.contributor.authorAnastasios, Giannopoulos-
dc.date.accessioned2023-11-23T06:44:30Z-
dc.date.available2023-11-23T06:44:30Z-
dc.date.issued2023-11-21-
dc.identifier.urihttp://artemis.cslab.ece.ntua.gr:8080/jspui/handle/123456789/18937-
dc.description.abstractThis PhD thesis was composed based on a series of technical and experimental modules, mainly aimed at presenting and applying advanced brain signal processing methods in a variety of clinical experiments. Throughout this thesis, the central goal was to develop an integrated and automated sequence of steps towards the (partial) decipherment of the most complex system found in nature: the human brain. The dominant purpose of the techniques presented was to demonstrate the synergy between Engineering, Statistics and Neuroscience in order to draw conclusions about the cognitive response of the human brain. It is worth noting that the procedure applied in each of the chapters dealing with specific experiments is of general purpose, therefore it can be reused in a variety of clinical or non-brain studies. Clearly, modifications to the methods of analysis are likely to be required, depending on the particular technical or theoretical changes resulting from the particular experiment. In the first chapter, the basic techniques of recording brain signals were presented, highlighting the main features and advantages of the Electroencephalogram (EEG) technique. In the second chapter, a standard sequence of steps towards noise mitigation in EEG signals was given, as well as standard processing techniques. The third chapter presents all those statistical techniques needed to validate results and draw conclusions in EEG studies. In the fourth chapter, the evoked potentials during the brain activity of past or future self-viewing were studied in order to elucidate whether or not past and future thinking share common brain resources. In chapter five, using the PPI/PPF experiment, three different studies on the sensorimotor system were presented. The latter is involved in any process involving the manifestation of a form of startle-motion and sensory stimuli. Next, we examined the neural correlates of BDD by investigating the electrophysiological responses to PPI and PPF auditory stimuli. Using a similar experiment, we studied startle responses in children and adolescents. Finally, in chapter six, we investigated the sensitivity of BDD patients to visual illusory phenomena and their corresponding brain connectivity patterns while making judgments about the corresponding visual stimuli.en_US
dc.languageelen_US
dc.subjectElectroencephalographyen_US
dc.subjectCognitive Electrophysiologyen_US
dc.subjectTime-Frequency Analysisen_US
dc.subjectEvent-related Potentialsen_US
dc.subjectNeuroimagingen_US
dc.subjectStatistical Analysisen_US
dc.subjectGraph Theoryen_US
dc.subjectBody Dysmorphic Disorderen_US
dc.titleElectroencephalographic Signal Processing and Analysis Techniques for Evaluating the Cognitive Response of Human Brainen_US
dc.description.pages212en_US
dc.contributor.supervisorΚαψάλης Χρήστοςen_US
dc.departmentΤομέας Συστημάτων Μετάδοσης Πληροφορίας και Τεχνολογίας Υλικώνen_US
dc.description.notesStandarization and Deployment of a generalized brain signal processing techniques for assessing the brain electrical activity, biomarker identification, development of advanced techniques for statistics, brain differences between clinical and control groups, study on the brain signature of Body Dysmorphic Disorder, research on Prepulse Inhibition of the Sensorimotor System, research on the Decision-making process about Optical Illusions from the brain perspectiveen_US
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