Popülasyon alıcı bölgeler modeli ile görsel korteks haritalandırılması: İMRG ve uyaran parametrelerinin ayarlanması ve alıcı bölge büyüklüğü incelemeleri

Autor: Erkat, O. Batuhan
Přispěvatelé: Boyacı, Hüseyin
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Popis: Cataloged from PDF version of article. Thesis (M.S.): Bilkent University, Department of Neuroscience, İhsan Doğramacı Bilkent University, 2019. Includes bibliographical references (leaves 76-83). Human visual cortex has been studied extensively since blood oxygen-level dependent (BOLD) signal was discovered by magnetic resonance imaging (MRI) researchers in 1990's [1]. It was not long after that, the researchers achieved to map human visual cortex with functional MRI [2, 3, 4]. In recent past, population receptive eld (pRF) method was proposed by Dumoulin and Wandell for receptive eld mapping [5]. Compared to phase-encoded methods, their model added a size parameter to receptive elds, referring to the extent of visual eld region processed by neuronal populations. fMRI sequences from Human Connectome Project [6] that used accelerated imaging to scan the whole brain of subjects at ultra-high resolutions were adapted to conduct retinotopy experiments in our institute, National Magnetic Resonance Center, Ankara. pRF maps estimated with three types of stimuli were compared. A local pRF estimation method was tested for a speci c region on visual eld to achieve greater detail in pRF maps. Subject speci c hemodynamic response function (HRF) was estimated in a separate experiment to enhance the pRF estimation analysis. Moreover, pRF size di erences were compared between stimuli, hemispheres, and visual processing streams. The results implied that stimulation by natural images yields reliable maps in higher level visual regions, and therefore was selected as the best stimulation protocol. pRF sizes were higher in right hemisphere, and in dorsal processing stream. In addition, a guideline has been prepared for vision researchers to conduct pRF analysis. by O. Batuhan Erkat M.S.
Databáze: OpenAIRE