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Yayın Cognitive decision investigation with combined EEG gamma oscillations and eyetracking (EOG)(Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, 2024-09-13) Sara, Ayça Burçak; Demirer, Rüştü Murat; Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, Elektronik Mühendisliği Yüksek Lisans Programı; Işık University, School of Graduate Studies, Electronics Engineering M.S. ProgramWith the progress in technology, the integration of neuroscience and sensory has assumed a very crucial role in discovering or unraveling cognitive functions. This thesis explores how EEG gamma oscillations and EOG eye tracking signals relate to cognitive decisions. Cognitive decision making, which encompasses attention, memory, and problem-solving abilities, is inherent in human functioning and hence grasping cognition enhances several fields including psychology, neuroscience, decision-making theories, among others. The study builds on the EEGEyeNet dataset to understand the coupling between the EEG activity and eye movements in decision making tasks, for 356 subjects in total. The contribution of high frequency gamma oscillations to saccadic eye movements is therefore investigated using additional EEG and EOG analysis techniques such as CPSD and phase space analysis. The findings clearly show that at a lower frequency band, the results are partially in line with the assumption that EEG and EOG activity is partially coordinated to the extent of decision-making task, while at high frequency bands, the EEG and EOG signals are partially asynchronous. This could suggest that this independence is the result of dissociated cognitive and neural substrates that control brain function and eye motion during processes that involve decision-making. The overall conclusions of this thesis help to advance the knowledge of how EEG and EOG signals can be combined for the investigation of cognitive decision-making processes. The study equally provides evidence towards the pliability and possibility of integrating these together for analysis of the neurological drivers of decision making while at the same time creating further research suggestions grounded on the accomplishment of achieving a blend of multiple physiological data feeds. Which could in turn bring about better cognitive models and better methods of rectifying poor decision making. It is hoped that this study will serve as a useful resource for other scholars from cognitive psychology, neuroscience, and human computer interaction where it may help advance studies on brain processes related to eye movement and decision making.
