The Effect of context luminance on contrast perception

Download

index.pdf

Date

2014

Author

Pamir, Zahide

Metadata

Show full item record

Item Usage Stats

192
views

72
downloads

The present study has employed psychophysics and functional magnetic resonance imaging (fMRI) methodologies. The aim of the study is to investigate the role of bottom-up and top-down processing of luminance in contrast perception. In particular, since it is thought that visual illusions occur as a result of top-down processing by means of visual context, the present study investigates how luminance in context affects contrast perception by using brightness illusion. In other words, the purpose of the study is to understand whether physical or perceived properties of luminance dictate contrast perception. An illusory stimulus which was especially created for the present study was used in the experiments. Two psychophysical experiment series and one fMRI experiment series was conducted. In the first experimental series, brightness value of the illusory stimulus was measured with several methods and experimental designs to be sure that illusion is strong enough. In the second experiment series, contrast perception was measured by locating a rectified square-wave grating on the illusory stimulus. In the fMRI experiment series, neuronal correlates of psychophysical results were investigated. Results show that perceived properties of luminance has an effect on contrast perception. Furthermore, fMRI findings showed complicated results both favouring physical and perceptual properties in different conditions.

Subject Keywords

Visual perception., Brightness perception., Contrast sensitivity (Vision)., Context effects (Psychology)., Magnetic resonance imaging.

URI

http://etd.lib.metu.edu.tr/upload/12617622/index.pdf
https://hdl.handle.net/11511/23778

Collections

Graduate School of Informatics, Thesis

Suggestions

OpenMETU
Core

Statistical disease detection with resting state functional magnetic resonance imaging Öztürk, Ebru; İlk Dağ, Özlem; Department of Statistics (2017) Most of the functional magnetic resonance imaging (fMRI) data are based on a particular task. The fMRI data are obtained while the subject performs a task. Yet, it's obvious that the brain is active even when the subject is not performing a task. Resting state fMRI (R-fMRI) is a comparatively new and popular technique for assessing regional interactions when a subject is not performing a task. This study focuses on classifying subjects as healthy or diseased with the diagnosis of schizophrenia by analyzing ...
An Information theoretic representation of brain connectivity for cognitive state classification using functional magnetic resonance imaging Önal, Itır; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2013) In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various info...
Improving the sub-cortical gm segmentation using evolutionary hierarchical region merging Çiftçioğlu, Mustafa Ulaş; Gökçay, Didem; Department of Medical Informatics (2011) Segmentation of sub-cortical Gray Matter (GM) structures in magnetic resonance brain images is crucial in clinic and research for many purposes such as early diagnosis of neurological diseases, guidance of surgical operations and longitudinal volumetric studies. Unfortunately, the algorithms that segment the brain into 3 tissues usually suffer from poor performance in the sub-cortical region. In order to increase the detection of sub-cortical GM structures, an evolutionary hierarchical region merging approa...
Convolutional neural network based brain MRI segmentation Baydar, Bora; Akar, Gözde; Department of Electrical and Electronics Engineering (2018) Visualization of the inner parts of human body is crucial in modern medicine and magnetic resonance imaging(MRI) is one of the widely used medical imaging methods. Manual analysis of MRIs, however, wastes the valuable time of experts. Development of an automatic segmentation method for brain MRIs can save time spent by the experts and can avoid human error factor. In this thesis, convolutional neural network (CNN) based methods are applied on brain MRI segmentation problem. The basic architectures used are ...
Functional magnetic resonance imaging (fMRI) simulator Arslankoz, Kamil; Gökçay, Didem; Department of Medical Informatics (2015) Functional magnetic resonance imaging (fMRI) utilizes the change in the oxygenation of blood to predict active areas in the brain. fMRI consists of multiple low resolution whole brain images, for which, the contrast difference in corresponding voxels among all images are studied. In this study, an fMRI simulator has been developed which generates customized 4D fMRI data that can be used as a ground truth for comparing/benchmarking different fMRI analysis methods. This simulator can be also used for educatio...

Citation Formats

Z. Pamir, “The Effect of context luminance on contrast perception,” M.S. - Master of Science, Middle East Technical University, 2014.