Signal detection theory analysis of category-based visual search in natural movies

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Author
Tutaysalgır, Osman
Advisor
Çukur, Tolga
Date
2016-09Publisher
Bilkent University
Language
English
Type
Thesis
Metadata
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http://hdl.handle.net/11693/32288Abstract
The human brain changes its inner hierarchy and connection strength between the
neurons in order to apprehend the real world. In visual search, It is thought that
the human brain changes the sensitivity of neurons in the favor of the attended
object. Here, we investigate these tuning shifts of the voxels in signal detection
theory perspective. Brain activities of human subjects were recorded while they
were watching a natural movie. To assess the attentional e ect on the human
brain, the decoding procedure was employed on the BOLD responses and the
natural movie stimuli. Decoding procedure tries to predict the stimuli that form
the BOLD responses. In order to bridge the gap between the stimuli and BOLD
responses, logistic regression which is a classi cation algorithm is applied to form
models of the subjects' brain. The model performances were assessed with dprime,
ROC and AUC parameters.
Our results suggest that category-selective regions in the human brain boost
their detection performances further for the objects that they are not inherently
selective.