Browsing by Author "Bayram, Ali."

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    Investigation of oscillatory mechanisms and thalamo-cortical circuitry of the visual system by simultaneous EEG-fMRI
    (Thesis (Ph.D.)-Bogazici University. Institute of Biomedical Engineering, 2015., 2015.) Bayram, Ali.; Ademoğlu, Ahmet.
    Neural oscillation is an indispensable phenomena in the functioning of the cortical networks. Evoked neural oscillations triggered by external rhythmic stimulation mimic spontaneous ongoing oscillations, thus could shed light on the intrinsic specialization and tuning of the cortical networks. In this thesis, ickering light stimulation is used to constitute steady state for a wide range of temporal frequencies (6-46 Hz) during simultaneous electroencephalography (EEG) and blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) scans of 40 healthy volunteers. Firstly, thalamo cortical loop of the visual system is the subject of interest. Our ndings prove that high correlation between the frequency response characteristics of the lateral geniculate nucleus (LGN) and the primary visual cortex (V1) supports the oscillatory tuning property of the thalamo cortical interactions. Secondly, contribution of oscillations in the modeling of hemodynamic response is discussed based on the sensitivity of BOLD components (phasic and tonic) to temporal frequency. Our results show that, tonic BOLD component is decreasing more sharply than phasic component with increasing frequencies pointing higher dependency of tonic BOLD response to the stimulation frequency. Finally, EEG informed fMRI analysis is conducted for the sake of testing resonance phenomena. The correlation maps between the BOLD responses and the steady state visually evoked potential (SSVEP) amplitudes show signi cant correlation for the beta and gamma bands but not for alpha band. This result supports the view that the global amplitude maximum of the SSVEP in the alpha band is due to the synchronization without synaptic activity (BOLD) increase.|Keywords : Electroencephalography, Functional magnetic resonance imaging, Oscillator networks, Steady state visually evoked potentials, BOLD transients, Resonance phenomena, EEG informed fMRI analysis.
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    Spatial analysis of event related brain potentials (ERP) by wavelet transform
    (Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2005., 2005.) Bayram, Ali.; Ademoğlu, Ahmet.; Demiralp, Tamer.
    Localization of the cognitive activity in the brain is one of the major problems inneuroscience. Current techniques for neuro-imaging are based on fMRI, PET, and ERPrecordings. The highest temporal resolution, which is crucial for temporal localization of activities, is achieved by ERP, but spatial resolution of scalp topography is low. To overcomethe limitation of scalp topography, several current-density estimation techniques weredeveloped whose goal is to find the locations of the three-dimensional (3D) intracerebral activities by solving an inverse problem. However, scalp topologies constituted by multiplesources which makes the inverse problem more complicated. The overall objective of thisthesis is to perform spatial analysis of scalp topography by 2-D wavelet transform and isolatespatial frequency components. This analysis could give us less complex scalp maps for sourcedetection. In this thesis, in order to see the topographic variations in neurocognitive processes, the ERP recordings were spatially enhanced by interpolation as a first step. At the secondstep, main topologies of ERP recordings were investigated by hierarchical clusteringalgorithm. Thirdly, different spatial frequencies of these main topologies were separated by 2-D wavelet transform. Finally, main topological maps and topographic maps of different spatial frequencies derived from them were used to find corresponding cortical activities(cortical activity maxima) by LORETA (Low Resolution Electromagnetic Tomography).Assessment of our spatial analyzing results was made according to the current densityestimation results.|Keywords: ERP, scalp topography, spatial analysis, 2-D wavelet, LORETA.