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

Abstract

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.